JP2011250810A - Radiographic image generation system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a radiographic image generation system that makes it possible to display quickly thinned data on a screen.SOLUTION: The radiographic image generation system 30 is provided with a radiographic image detector 1, a console 31, an offset correction value generation means 31, and a radiation generation device 34. The console 31 displays on a display unit at least one of the following images; the image that is formed in accordance with the thinned data based on thinned data f(x, y) or real imaging data F(x, y), the image that is formed after the image-processing of thinned data generated in accordance with the thinned data or real imaging data by carrying out gain correction processing and offset correction processing based on an offset correction value for the thinned data or the thinned data generated in accordance with the real imaging data, and the image that is formed after image processing in which gain correction processing and offset correction processing based on an offset correction value are carried out for the real imaging data.

Description

  The present invention relates to a radiation image generation system.

  In a radiation image detector in which a solid-state imaging device called a so-called flat panel detector (FPD) is two-dimensionally arranged, a photoconductive substance such as a-Se (amorphous selenium) is used as the detection device. Radiation energy is directly converted into electric charge, and this electric charge is read out as an electric signal for each pixel by a signal reading switch element such as TFT (Thin Film Transistor) arranged two-dimensionally. An indirect system that converts light into light by a scintillator or the like, converts the light into electric charge by a photoelectric conversion element such as a two-dimensionally arranged photodiode, and reads it as an electric signal by a TFT or the like is well known.

  In either method, it is necessary to correct the photographed image data by performing gain correction, offset correction, or the like on the photographed image data obtained by detecting the radiation transmitted through the subject by the radiation image detector. It is known.

In general, in the correction of actual image data, as shown in the following equation (1), the actual image data output from each radiation detection element (the coordinates in the sensor panel unit are (x, y)) of the radiation image detector. By subtracting the offset correction value O (x, y) from F (x, y) and multiplying the difference by the gain correction value G (x, y), the final image data F _O (x, y) is obtained. Correction is performed in such a way as to obtain. Note that the image data F _O (x, y) generated based on the actual image data F (x, y) output from one radiation detection element of the radiation image detector is a captured image (that is, a radiation image). Since this corresponds to image data for one pixel, the radiation detection element may be referred to as a pixel hereinafter.
F _O (x, y) = (F (x, y) −O (x, y)) × G (x, y) (1)

  As described above, in the correction of the actual image data, since it is necessary to obtain the offset correction value O (x, y) and the gain correction value G (x, y), the radiological image detector is periodically calibrated. In general, the offset correction value O (x, y) and the gain correction value G (x, y) whose characteristics may change with time are updated.

However, in this method, the temperature of each element in the radiographic image detector when calibration is performed matches the temperature of each element in the radiographic image detector when radiographic imaging is performed. As a precondition, if the temperature of each element in the radiation image detector at the time of calibration differs from the temperature of each element in the radiation image detector at the time of radiographic imaging, it is temperature dependent. There is a problem that the offset correction value O (x, y) having a high characteristic is deviated from an appropriate value and the SN ratio of the final image data F _O (x, y) is deteriorated.

  In order to solve this problem, an output value (hereinafter referred to as a dark read value D (x, y) from each radiation detection element in a state in which radiation is not irradiated immediately before or immediately after imaging for each radiographic imaging. The dark read value may be referred to as a dark image.) Is detected, and the offset correction value O (x, y) in the radiographic image capturing may be calculated. This is a process for obtaining the offset correction value O (x, y) under the same temperature conditions as possible as the temperature characteristics of the radiation detection element at the time when the actual image data F (x, y) is obtained by radiographic imaging. is there.

  However, as in the case of acquiring the actual image data F (x, y), when acquiring the dark read value D (x, y), various electric noises, that is, the dark current noise of the photodiode, the TFT transient, etc. Noise, TFT thermal noise, TFT leak noise, thermal noise caused by parasitic capacitance of the data line that reads charges from the TFT, amplifier noise inside the readout circuit, quantization noise caused by A / D conversion, etc. are affected. Even if the dark read value D (x, y) is read under temperature conditions, the dark read value D (x, y) has fluctuations (variations) in signal values due to these electrical noises.

  Therefore, even if the dark reading value D (x, y) is read immediately before or after radiographic imaging, the read dark reading value D (x, y) is offset, that is, offset correction in imaging conditions such as the temperature condition. It cannot necessarily be said that it is the true value of the value O (x, y). Therefore, dark reading is performed a plurality of times immediately before and after radiographic imaging to calculate the average value of each dark reading value D (x, y), and the average value is adopted as the offset correction value O (x, y). Is often performed (see, for example, Patent Documents 1 to 3).

This is to calculate the average value of the dark read values D (x, y) read out a plurality of times under the same temperature conditions as the temperature characteristics of the radiation detection element or the like in the radiographic imaging immediately before or after the radiographic imaging. For example, since the fluctuation of the dark reading value D (x, y) is reduced or offset, the average value is equal to or at least equal to the true value of the offset correction value O (x, y) under the photographing conditions. This is based on the idea of close values. Then, if the photographed image data F (x, y) is corrected using the offset correction value O (x, y) that is the average value, the SN of the final image data F _O (x, y) after correction is corrected. The ratio can be good.

  On the other hand, image processing such as correction processing such as offset correction has been conventionally performed by a processing device such as an image processor or a console that is different from an imaging device such as a radiation image detector (for example, , See Patent Document 4). In recent years, portable radiographic image detectors have been developed that have built-in batteries and that transmit and receive live-action image data F (x, y) and the like with an external processing device or the like wirelessly without using a cable. (For example, see Patent Document 5).

  In addition, in the radiation image detector, defective pixels that cannot output normal pixel values may occur during the manufacturing process. For example, as an example of a defective pixel, a pixel that constantly outputs a large pixel value (for example, a pixel whose signal value always reaches a saturation level), or a pixel that constantly outputs only a small pixel value (for example, There are pixels that always output only a zero level signal value), and pixels that always output only a constant signal value (a pixel whose output pixel value does not change even when irradiated with radiation).

  These defective pixels may occur during the TFT manufacturing process, or may occur when a photoelectric conversion element is formed on the TFT. The radiation image detector is required to appropriately change the pixel value in proportion to the irradiated radiation dose, but in these defective pixels, a normal pixel value change corresponding to the irradiated radiation dose cannot be expected.

If such a defective pixel occurs in the diagnostic image, it may cause a misdiagnosis or interfere with the diagnostic action. If there is a defective pixel, the defective pixel is interpolated using surrounding pixel values. It is required to perform processing so that defective pixels cannot be visually recognized in the final image data F _O (x, y).

  In order to perform such correction processing, the pixel position of the defective pixel must be known in advance. Such defective pixels are detected by performing post-manufacturing shipping inspections or inspections involving radiation irradiation during regular calibration, and the pixel positions of the detected defective pixels are registered in the defective pixel map ( For example, see Patent Document 6). This defective pixel map is constructed for each radiographic image detector, and thereafter operated and managed in association with individual radiographic image detectors.

When performing the above-described offset correction and gain correction, the defective pixel map is also referred to and managed so that the pixel value of the defective pixel is not erroneously used for offset correction or gain correction.
US Pat. No. 5,452,338 US Pat. No. 6,222,901 U.S. Pat. No. 7,041,955 JP-A-11-113889 JP-A-7-140255 Japanese Patent Laid-Open No. 2001-8198

  As an example of a defective pixel, a pixel that constantly outputs a large pixel value (for example, a pixel whose signal value always reaches a saturation level), or a pixel that constantly outputs only a small pixel value (for example, a signal value that always remains) Is a pixel that outputs only zero level values), and pixels that always output only a constant signal value (pixels whose output pixel values do not change even when irradiated with radiation) are increased, but these defective pixels are very It can be easily detected.

However, although not belonging to any of the above, there is a pixel (hereinafter referred to as an abnormal pixel) that outputs an abnormal signal value with a certain probability. Since these pixels are not registered in the defective pixel map, there is a risk that a pixel having an abnormal value is generated in the final image data F _O (x, y) with a certain probability, which hinders diagnosis. It was.

  Further, in the defective pixel determination method so far, when the defective pixel is determined, the defective pixel is detected using the image information irradiated with radiation. There has been a problem that the number of images used for determining defective pixels is limited to several to at most ten. Therefore, even if a defective pixel that outputs an abnormal value on a regular basis can be detected, an abnormal pixel that occurs with a certain probability cannot be captured, or when a defective pixel is determined using statistical values such as standard deviation, It was difficult to obtain good statistics. For this reason, if the number of times of radiation irradiation is increased, the productivity is lowered and the production cost is increased.

  Also, such defective pixels and abnormal pixels tend to increase over time, so it is not safe to register defective pixels at the time of shipment from the factory. When a new defective pixel or abnormal pixel is found after calibration, the pixel position is preferably registered in the defective pixel map or appropriately processed as an abnormal pixel. However, even in the calibration work performed after installation at the user site, the user is periodically obliged to perform multiple times of radiation irradiation, and there is a problem that the work load of the user increases.

  In addition, when a defective pixel or an abnormal pixel is determined by a calibration process, a method for determining a defective pixel or an abnormal pixel in consideration of a temperature variation of each element in the radiation image detector has not been proposed. It was difficult to accurately determine defective pixels and abnormal pixels without being affected.

  On the other hand, in a portable radiographic image detector that has a built-in battery and transmits data to an external device wirelessly, it takes a relatively long time to transmit real image data captured by radiographic imaging to the external device. Actual image data that is data for all pixels of the radiation image detector as an image for determining whether or not re-imaging is necessary by confirming the photographing position of the subject in the radiation image. In some cases, the system is configured such that thinned data in which the amount of data is reduced by thinning out the actual image data can be transmitted.

  In such a system, the thinned data is transmitted from the radiation image detector in a short time, and the thinned image data is instantaneously displayed on the display screen of the console. In addition, it is possible to immediately determine whether or not re-imaging is necessary by checking the thinned data displayed by the radiologist or the like. As described above, the thinned data is required to be displayed on the screen quickly.

  In addition, since it is necessary to transmit the actual image data in the end, it is troublesome twice for the engineer to operate after transmitting the thinned-out data. Therefore, the transmission is performed only once for the actual image data. However, even in this operation, it is desirable to display a reshooting necessity confirmation required image so that the necessity of reshooting can be quickly confirmed.

  Furthermore, finally, it is necessary to provide a good diagnostic image that has been subjected to image processing including gradation processing according to each imaging region, including correction for abnormal / defective pixels.

  The present invention has been made in order to solve the above-described problems, and a radiographic image capable of quickly displaying an image for confirming the necessity of re-imaging (thinning data in a general operation) on a screen. An object is to provide a generation system. It is another object of the present invention to provide a radiographic image generation system that can accurately eliminate the influence of abnormal pixels and defective pixels from final diagnostic image data.

In order to solve the above-described problem, the radiation image generation system of the present invention includes:
A plurality of radiation detection elements arranged two-dimensionally;
In radiographic imaging, real image data is acquired from the plurality of radiation detection elements, and in dark reading performed in a state where radiation is not irradiated, signal value acquisition means for acquiring dark reading values from the plurality of radiation detection elements;
Control means capable of creating thinned-out data based on the photographed image data;
Communication means capable of transmitting the actual image data, the dark reading value, and the thinned data;
A radiation image detector comprising:
An image processing unit that performs image processing on the actual image data and the thinned data transmitted from the radiation image detector;
A display unit that displays the actual image data, the image based on the thinned-out data, or an image after performing image processing on them;
A console having
Based on the dark reading value, an offset correction value in the radiographic image capturing in the radiographic image detector is generated based on the dark reading value output from the radiation detecting element of the radiographic image detector. Offset correction value generation means;
A radiation generator for irradiating the radiation image detector with radiation;
With
The radiation image detector includes the dark reading value in the dark reading performed at least once before or after the radiographic image capturing, the actual image data based on the radiographic image capturing, and the thinned data based on the actual image data. And at least one of the above to the console,
The console includes a gain correction process and the offset for an image based on the thinned data or the thinned data created based on the photographed image data, or on the thinned data or the thinned data created based on the photographed image data. An offset correction process based on a correction value is performed, an image after image processing is applied to the thinned data or the thinned data created based on the actual photographed image data, or a gain correction process and the offset correction value for the actual photographed image data At least one of the images after the image processing subjected to the offset correction processing based on the above is displayed on the display unit.

  According to the radiation image generation system of the system as in the present invention, it is possible to display image data for confirming the necessity of re-imaging in a short time according to the facility operation mode. Further, after confirming the necessity of re-imaging, the offset correction value for correcting the actual image data of the radiation detection element is associated in advance with the dark reading value output from the radiation detection element and the radiation detection element. Since it is calculated using the dark reading values output from a plurality of radiation detection elements, it is sufficiently accurate even when dark reading is performed about once before or after radiographic imaging. Thus, it is possible to obtain a correct offset correction value, correct the characteristic variation for each pixel (radiation detection element), and generate final diagnostic image data with a good S / N ratio. Furthermore, by using the abnormal pixel determination method and defective pixel determination method specific to the present invention, the final image data can be accurately excluded to generate good final diagnostic image data. It becomes possible to do.

  Embodiments of a radiation image generation system according to the present invention will be described below with reference to the drawings. However, the present invention is not limited to the following illustrated examples.

[Basic configuration of radiation image detector]
First, a basic configuration of a radiation image detector used in the radiation image generation system of the present invention will be described.

As shown in FIG. 1, the radiation image detector (flat panel detector) 1 includes a housing 2 that protects the inside, and radiates irradiated radiation to the inside of the radiation incident surface X of the housing 2. A scintillator layer (not shown) for conversion into (1) is formed. As the scintillator layer, for example, a layer formed using a phosphor in which a luminescent center substance is activated in a matrix such as CsI: Tl, Gd ₂ O ₂ S: Tb, ZnS: Ag, or the like can be used.

  As shown in the equivalent circuit diagram of FIG. 2, on the surface side opposite to the surface on which the radiation of the scintillator layer is incident, there are a plurality of elements that convert light output from the scintillator layer into electrical signals as radiation detection elements. The sensor panel section 4 is provided in which the photodiodes 14 are two-dimensionally arranged. The charge (signal value) output from one photodiode 14 forms one pixel. Further, as will be described in detail later, each photodiode 14 is connected to a TFT 15 which is a signal reading switch element.

  In the following, the case where the so-called indirect radiation image detector 1 that converts radiation into light by the scintillator layer and detects it by a photoelectric conversion element such as a photodiode as described above will be described. In addition to this, it is also possible to use a so-called direct-type radiation image detector that directly converts the radiation incident on the detection element without passing through the scintillator layer into an electrical signal. The invention can be applied.

  Hereinafter, detection elements used in these types of radiation image detectors are collectively referred to as radiation detection elements. That is, for example, in the indirect radiation image detector 1 as in the present embodiment, the radiation detection element includes one photodiode 14, a TFT 15 connected thereto, and a portion corresponding to the photodiode 14 in the scintillator layer. For example, a direct radiation image detector includes a detection element and a switch element such as a TFT connected thereto.

  The radiation image detector 1 includes a battery 21 (see FIG. 2). As shown in FIG. 1, in this embodiment, an antenna device 3 that is a wireless communication unit is embedded in the battery replacement lid member 10 provided on the side surface portion of the housing 2 of the radiation image detector 1. Is provided. Further, a power switch 11 of the radiation image detector 1, an indicator 12 for displaying various operation statuses, an input button 23 for inputting instructions from the user, and the like are provided on the side surface portion of the housing 2. .

  As shown in FIG. 2, in the vicinity of the sensor panel unit 4, a reading unit 5 that reads an output value of each radiation detection element of the sensor panel unit 4 is provided. The reading unit 5 includes a control unit 6 including a microcomputer, a storage unit 7 including a ROM (Read Only Memory) and a RAM (Random Access Memory), a flash memory, a scan driving circuit 8, a reading circuit 9, and the like. ing.

  As shown in FIG. 3, the plurality of radiation detection elements arranged two-dimensionally on the sensor panel unit 4 respectively have a position x in the row direction and a position y in the column direction of the radiation detection elements in the sensor panel unit 4. The coordinates (x, y) for each component are assigned in advance as the number (x, y) of the radiation detection element. Hereinafter, when individual radiation detection elements are specified, they are referred to as radiation detection elements (x, y).

  In FIG. 3, 8 × 16 radiation detection elements (x, y) are illustrated, but this is a simplified representation, and actually more radiation detection elements (x, y). ) Are two-dimensionally arranged and assigned numbers. In addition, the coordinates (x, y) (that is, the radiation detection element number (x, y)) may be referred to as a pixel number (x, y) or a pixel position (xy).

  The configurations of the sensor panel unit 4 and the reading unit 5 will be further described. As shown in the equivalent circuit diagram of FIG. 2, one electrode of each radiation detection element (x, y) of the sensor panel unit 4 is used for signal readout. The source electrode of the TFT 15 which is the switch element is connected. In addition, a bias line Lb is connected to the other electrode of each radiation detection element (x, y), and the bias line Lb is connected to a bias power supply 16, and each radiation detection element (x, y) is connected from the bias power supply 16. A bias voltage is applied to y).

  The gate electrode of each TFT 15 is connected to a scanning line Ll extending from the scanning drive circuit 8, and the drain electrode of each TFT 15 is connected to a signal line Lr. Each signal line Lr is connected to an amplifier circuit 17 in the readout circuit 9, and an output line of each amplifier circuit 17 is connected to an analog multiplexer 19 via a sample hold circuit 18. The analog multiplexer 19 is connected to an A / D converter 20, and the reading circuit 9 is connected to the control means 6 via the A / D converter 20. A storage means 7 is connected to the control means 6.

  In the radiation image detector 1, in radiation image capturing for capturing a subject (not shown), when radiation transmitted through the subject enters the scintillator layer, light is irradiated from the scintillator layer to the sensor panel unit 4, and the amount of light irradiation received Accordingly, electric charges are accumulated in the radiation detection element (x, y).

  When the radiographic image capturing is completed and the actual image data is read from the radiographic image detector 1 as an electrical signal, a read voltage is applied from the scanning line Ll to the gate electrode of the TFT 15 to open the gate of each TFT 15, The charge accumulated from the detection element (x, y) through the TFT 15 is taken out as an electric signal to the signal line Lr. Then, the electric signal is amplified by the amplifier circuit 17 and output from the analog multiplexer 19 to the control means 6 via the A / D converter 20 in sequence.

  The control means 6 associates the amplified electrical signal output from the radiation detection element (x, y) with the number (x, y) of the radiation detection element (ie, pixel) described above, and captures the actual image data F (x, y). It is stored in the storage means 7 as y).

  By sequentially scanning the scanning lines Ll to which the readout voltage is applied to the TFT 15 and performing the above readout processing for each scanning line Ll, electrical signals are respectively read from all the radiation detection elements (x, y) of the sensor panel unit 4, Each electric signal is associated with a pixel number (x, y) and stored in the storage means 7 as each photographed image data F (x, y).

  As described above, the radiation image detector 1 includes the sensor panel unit 4 in which a plurality of radiation detection elements (x, y) are two-dimensionally arranged, the control means 6, the scanning drive circuit 8, the readout circuit 9, and the like. The read unit 5 or the like forms image data acquisition means for acquiring the actual image data F (x, y).

  Further, the image data acquisition means of the radiation image detector 1 not only acquires the actual image data F (x, y) as described above, but also performs dark reading.

  In the dark reading, after resetting a plurality of radiation detection elements (x, y) of the radiation image detector 1 to release charges, the gate of each TFT 15 is closed and the radiation image detector 1 is not irradiated with radiation. Keep on. Then, after a predetermined time has elapsed (usually, after the same time as the charge accumulation time in the radiation detection element (x, y) at the time of radiation irradiation), a readout voltage is applied from the scanning line Ll to the gate electrode of the TFT 15. The gate of the TFT 15 is opened, the charge (dark charge) accumulated in each radiation detection element (x, y) is taken out to the signal line Lr, and the output value is amplified by the amplifier circuit 17 in the same manner as described above. Are sequentially output to the control means 6 via the A / D converter 20.

  In this way, the electrical signal output from each radiation detection element (x, y) that is not exposed to radiation is the dark read value. The control means 6 stores each electrical signal output from each radiation detection element (x, y) in association with each pixel number (x, y) as a dark read value D (x, y) in the storage means 7. It is supposed to be. The scanning line Ll for applying the read voltage to the TFT 15 is sequentially scanned, and the dark read value D (x, y) is read from all the radiation detection elements (x, y).

  As described above, in the radiation image detector 1, each radiation detection element (x, y) is calibrated in order to grasp the output value characteristic variation from each radiation detection element (x, y). In a normal case, in the calibration, the radiation image detector 1 is irradiated with radiation without a subject being present, and based on the actual image data F (x, y) output from each radiation detection element (x, y). A gain correction value is calculated for each radiation detection element (x, y).

  In the calibration, dark reading is also performed a plurality of times, and in the dark reading, the dark reading value D (x, y) is output from each radiation detection element (x, y) without irradiating the radiation image detector 1 with radiation. Then, an offset correction value is calculated for each radiation detection element (x, y) based on the output dark read value D (x, y).

  Furthermore, in order to obtain an offset correction value under the same imaging conditions as the imaging conditions such as the temperature characteristics of the radiation detection element (x, y) at the time when the actual image data F (x, y) is obtained by radiographic imaging, For each radiographic image capture, the dark read value D (x, y) output from each radiation detection element (x, y) is detected a plurality of times in a state where no radiation is irradiated immediately before or immediately after the radiographing, and the average value thereof is detected. As described above, may be calculated as an offset correction value in radiographic imaging.

[Principle of offset correction value acquisition of each radiation detection element of the radiation image detector]
Prior to the description of the radiation image generation system according to the present invention, the principle for obtaining an offset correction value for each radiation detection element (each pixel) of the radiation image detector will be described.

  In order to correct the photographed image data F (x, y) output from each radiation detection element (x, y) according to the above equation (1), an offset correction value (hereinafter referred to as O (x, y)). The true value of is required. However, as described above, the data actually obtained by performing the dark reading is the dark reading value D (x, y) that fluctuates (fluctuates or has an error) due to the influence of the electric noise or the like described above. The true value of the offset correction value O (x, y) cannot be obtained directly.

  Therefore, conventionally, as described above, a plurality of darks output from one radiation detection element (x, y) by performing dark reading multiple times in succession immediately before and immediately after radiographic imaging. A method of calculating an average value of the read values D (x, y) and mitigating or canceling fluctuations and setting the average value as an offset correction value O (x, y) was adopted.

Specifically, assuming that dark reading is performed K times, as shown in FIG. 4, the dark reading value output from the radiation detection element (x, y) in the k-th (k = 1 to K) dark reading is obtained. Assuming D _k (x, y), for example, as shown in FIG. 5, each dark read value D _k (x, y) output from the radiation detection element (x, y) in each dark reading is an average value D. It is known to fluctuate so as to form a normal distribution of _kave (x, y) and standard deviation σ _Dk (x, y). This is because when the dark reading is repeatedly performed on the one radiation detection element (x, y), the obtained dark reading value fluctuates (fluctuates) at every reading even though the pixel position is the same. Therefore, this fluctuation is defined as “temporal fluctuation”. The standard deviation of the fluctuation distribution (standard deviation σ _Dk (x, y) in the case of the dark reading value D _k (x, y)) is usually used as a statistical index representing the magnitude of fluctuation.

Further, since the average value D _kave (x, y) is an average value on the time axis of each dark reading value D _k (x, y), this average value is defined as a “temporal average value”. If the average value D _kave (x, y) is used as the offset correction value O (x, y) of the radiation detection element (x, y), the value of each dark read value D _k (x, y) Since temporal fluctuations can be reduced or offset, in general, the temporal average value of each dark reading value D _k (x, y) may be used as the offset correction value O (x, y). Many. The offset correction value O (x, y) is shown in the following equation (2).

The dark reading value D _k (x, y) fluctuates with the standard deviation σ _Dk (x, y). When this is averaged K times, the fluctuation magnitude is generally 1 / √K. That is, the offset correction value O (x, y) has a distribution having a fluctuation of standard deviation {1 / √K · σ _Dk (x, y)}. Therefore, the above equation (2) indicates that the value of fluctuation 1 / √K is used as the offset correction value rather than using the dark read value D _k (x, y) itself as the offset correction value. Show.

  However, when the offset correction value O (x, y) is calculated in this way, dark reading and transmission of the dark reading value must be performed a plurality of times, and thus there is a problem that power is consumed. That's right.

  In order to avoid this problem, a plurality of dark readings are performed at the time of calibration, and the offset correction value O (x, y) calculated in advance using the above equation (2) is used. When the temperature of each element in the radiographic image detector at the time of performing and the temperature of each element in the radiographic image detector at the time of performing radiographic imaging are different, the offset correction value O (x, y) is appropriate. As described above, there is a problem of deviating from a certain value.

  Therefore, a description will be given of an offset correction method together with a calibration method and a temperature compensation method.

  Since the calibration method and temperature compensation method taken up in this description are also used in the defective pixel determination method in the present invention, the basic concept thereof will be discussed in the following description. The offset correction method is described by performing dark reading at least once just before or immediately after radiographic imaging, even if the dark reading is performed only once. , Y) is used. However, the defective pixel determination method in the present invention is not limited to the offset correction method described below.

  This method (a method of calculating an offset correction value O (x, y) with high accuracy even if dark reading is performed at least once before or immediately after radiographic imaging, and even if dark reading is performed only once. ) Is as follows.

First, at the time of calibration, for each pixel position (x, y) corresponding to each radiation detection element (x, y), a plurality of dark images d _k (x, y) under a predetermined temperature condition without temperature change. (Hereinafter, the dark reading value d _k (x, y) is distinguished from the dark reading value D (x, y) obtained by one dark reading performed immediately before or immediately after radiographic imaging as described above.) And an offset correction value δ (x, y) (hereinafter, finally obtained offset correction value O (x, y)) using a plurality of acquired dark images d _k (x, y). In order to distinguish from y), an offset correction value δ (x, y) is obtained). It is assumed that the temperature characteristics of each pixel position (x, y) are the same while the dark image d _k (x, y) is acquired.

  At this time, a temperature compensation variable is defined to represent the amount of change accompanying the temperature change of the signal value at each pixel position (x, y) when the offset correction value δ (x, y) is obtained, and this is defined for each pixel. Calculate and store for each position (x, y).

  Here, the positioning of the temperature compensation variable will be described. The temperature compensation variable is not intended to measure the temperature itself of the radiation detection element (x, y) at each pixel position (x, y). What we want to know is not the temperature itself of each radiation detection element (x, y), but the signal at each pixel position (x, y) due to the temperature change of each element such as the radiation detection element (x, y) or an electric circuit. Because the value has changed (for example, even if the temperature of each radiation detection element (x, y) itself changes), the signal value of the pixel corresponding to that radiation detection element (x, y) changes. If it is not, there is no problem even if it is considered that there was no temperature change of the radiation detection element (x, y).), By the temperature change of each element such as the radiation detection element (x, y) or an electric circuit, It is desirable that the variable be a variable that quantitatively suggests how the signal value at each pixel position (x, y) has changed.

  Next, just before or immediately after radiographic imaging, dark reading is performed only once to obtain a dark reading value D (x, y). At this time, the temperature compensation variable similar to the above is calculated and stored for each pixel position (x, y) for the dark read value D (x, y).

Next, the temperature compensation variable at each pixel position (x, y) when the offset correction value δ (x, y) is obtained and the temperature at each pixel position (x, y) of the dark read value D (x, y). Comparing the compensation variables, based on the result, the offset correction value δ (x, y) obtained in advance is converted into the offset correction value O (x, y) in the temperature environment when the radiation imaging is actually performed. The final image data F _O (x, y) is used for calculation.

  Normally, when the offset correction value O (x, y) acquired at the past calibration is used, the dark reading value D (x, y) acquired immediately before or after the radiographic image capturing is affected by temperature fluctuation. This is often used as the offset correction value O (x, y) (that is, O (x, y) = D (x, y)). On the other hand, in this method, the dark read value D (x, y) acquired every time radiographic imaging is not directly used as the offset correction value itself, but the temperature at each pixel position in the temperature environment when radiography is performed. The point used for calculation of the compensation variable is different from the conventional method. Then, instead of using the offset correction value δ (x, y) calculated in advance using a plurality of dark images as it is, using the above-described temperature compensation variable, the time point when the radiographic image is actually taken is reached. The point that it is used as the offset correction value O (x, y) after performing the temperature correction is a point that the conventional method does not have.

  The advantages of this method are as follows.

First of all, an offset correction value δ (x, y) serving as a reference for calculating an offset correction value O (x, y) used to obtain final image data F _O (x, y). However, since it is calculated from a plurality of dark images d _k (x, y) under a predetermined temperature condition that can be regarded as having no temperature change, error components (temporal fluctuations in signal values) such as electrical noise are canceled out. In addition, the value is close to the true offset correction value. Therefore, the final image data F with a small correction error and a good S / N ratio as compared with the case where the single dark read value D (x, y) itself acquired at the time of radiographic imaging is used as the offset correction value. _O (x, y) can be obtained.

Secondly, by calculating a temperature compensation variable for each pixel position (x, y), pixel value variations due to temperature changes are individually corrected for each pixel position (x, y). No matter how the signal value of the pixel position (x, y) is affected by the temperature change, this is corrected, and final image data F _O (x, y) having a good SN ratio is obtained. is there. This temperature correction for each pixel can be performed by acquiring a dark image only once.

  What is important here is what is used for the temperature compensation variable for each pixel position (x, y). Although it is sufficient if a temperature sensor can be built in each pixel position (x, y) in advance, this method is not practical. Although it is conceivable to incorporate a realistic number of temperature sensors in the radiation image detector 1, it is not possible to achieve accurate temperature correction for each pixel position (x, y). What is desired is not the temperature itself of the radiation detection element (x, y) but the temperature change of each element such as the radiation detection element (x, y) or an electric circuit at each pixel position (x, y). It is how the signal value has changed.

From the above, the requirements for temperature compensation variables are considered to be the following four items.
Requirement 1) Variable required for each pixel unit (or for each small area unit close to a pixel).
Requirement 2) A variable that can grasp changes in signal value due to temperature changes.
Requirement 3) A variable obtained from the dark image D (x, y).
Requirement 4) Variables with little temporal fluctuation.

  As a temperature compensation variable that satisfies the requirements of these four items, the present inventor has calculated the average value (or median value, etc.) of the pixel values of the peripheral pixels with respect to the pixel of interest (x, y) of the dark read value D (x, y). I paid attention to.

  The result of each element such as the radiation detection element (x, y) and the electric circuit being affected by the temperature change is reflected in the dark read value D (x, y). What we want to know is how the signal value of each pixel has changed due to the temperature change of each element such as the radiation detection element (x, y) and the electric circuit. It makes sense to use (x, y) and satisfies requirements 1-3.

  Next, whether or not the selected temperature compensation variable satisfies requirement 4 will be described with reference to FIG.

  As shown in FIG. 6, for example, as a plurality of radiation detection elements (x, y), the one radiation detection element (x, y), that is, in a 5 × 5 square region centered on the pixel position (x, y). The signal values at a plurality of pixel positions (x−2, y−2) to (x + 2, y + 2) existing in are used for temperature compensation variable calculation. A method of selecting a radiation detection element (x, y) other than the one radiation detection element (x, y) will be discussed later.

However, the dark read values D (x−2, y + 2) output from the 25 radiation detection elements (x−2, y−2) to (x + 2, y + 2) including the one radiation detection element (x, y). The distribution of temporal fluctuations of the signal values y-2) to D (x + 2, y + 2) is not always the distribution as shown in FIG. 5, but actually, for example, as shown in FIG. to, the average value mu _D and the standard deviation sigma _D is different distributions are common.

In this method, as shown in the following equation (3), all dark read values D output from the radiation detection elements (x−2, y−2) to (x + 2, y + 2) in the one dark read. An average value W (x, y) of (x−2, y−2) to D (x + 2, y + 2) is calculated and adopted as a temperature compensation variable. In this case, the average value (temperature compensation variable) W (x, y) is a spatial average value for the pixel position (x, y) of the dark read value D (x, y). N in the formula (3) is 25 (= 5 × 5) in this case.

  Here, it is considered whether or not the spatial average value W (x, y) as the temperature compensation variable satisfies the requirement 4).

Since each of the dark reading values D (x−2, y−2) to D (x + 2, y + 2) is an independent variable, and its fluctuation is random in terms of time and space, the dark reading value D The temporal average value of temporal fluctuations of (x, y) is expressed as μ _D (x, y), the standard deviation of the temporal fluctuation distribution is expressed as σ _D (x, y), and the temperature compensation variable W (x, y) ) Is represented by μ _W (x, y), and the standard deviation of the temporal fluctuation distribution is represented by σ _W (x, y).
(See FIG. 8).

Here, if σ _D (x, y) does not include a defective pixel having a very large value (abnormal value) or many abnormal pixels,
σ _W (x, y) <σ _D (x, y)
The following relational expression holds.

For example, assuming that each value of σ _D (x−2, y−2) to σ _D (x + 2, y + 2) is different, but taking an average, it is almost equal to σ _D (x, y). )
Σ _W (x, y) is 1 / √N of the value of σ _D (x, y). In the case of N = 25, 1 / √N = 1/5. Therefore, the temperature compensation variable W (x, y) has a dark reading D (x, Compared to y), the distribution is 1/5. That is, as shown in FIG. 8, the distribution is narrow (standard deviation is small) and satisfies requirement 4).

As an extreme example, among the pixel positions (x−2, y−2) to (x + 2, y + 2), the dark reading value temporally at the pixel position of (N−1) other than the target pixel (x, y). It is assumed that the standard deviation value of fluctuation has a magnitude N times the standard deviation value σ _D (x, y) of temporal fluctuation of the dark read value D (x, y) at the target pixel position. If N> 2,
And
σ _W (x, y) <σ _D (x, y)
Is established.

If N = 25,
SQRT [{1+ (N−1) · N} / N ² ]
= SQRT {(1 + 24 × 25) / (25 × 25)}
≒ 0.981
So,
σ _W (x, y) ≈0.981 · σ _D (x, y) <σ _D (x, y)
Normally, each value of σ _D (x−2, y−2) to σ _D (x + 2, y + 2) is different, but taking an average takes a value substantially equal to σ _D (x, y). It can be said that the method satisfies requirement 4).

The distribution of the spatial average value W (x, y) as the temperature compensation variable is a plurality of radiation detection elements 14 (hereinafter referred to as predetermined regions) in a square region centered on the one radiation detection element (x, y). The greater the number of radiation detection elements 14 _{R in} the sense of the radiation detection elements 14 belonging to R, that is, the larger the value of N, the spatial average value W (x, y) as a temperature compensation variable. ) Of the time fluctuation standard deviation σ _W (x, y) becomes small. This means that when σ _W (x, y) takes a sufficiently small value,
W (x, y) ≈μ _W (x, y) (6)
It can be approximated.

That is, dark read value D (x-2, y- 2) output from the immediately preceding or one dark read the radiation detecting element 14 _R, which is performed immediately after the radiation image capturing ~D (x + 2, y + 2) ( hereinafter, in the sense that dark read value output from the radiation detecting element 14 _R belonging to a predetermined region R is denoted as dark read value D _R.), the time distribution of the temporal fluctuations as illustrated in FIG. 7 The average value of the target fluctuations μ _D (x−2, y−2) to μ _D (x + 2, y + 2) fluctuates around, but the spatial average value (temperature compensation variable) W ( As x, y), a value approximately equal to the temporal average value μ _W (x, y) of the distribution of the spatial average value (temperature compensation variable) W (x, y) is calculated.

Thus, the one of the radiation detecting element (x, y) be the average value mu _D and the standard deviation sigma _D of the distribution of the temporal fluctuations of the dark read value D _R to be output from the radiation detection elements 14 _R are different, including the (see FIG. 7), by calculating their spatial mean value (temperature compensation variable) W (x, y), the temporal fluctuation of the dark read value D _R output from the radiation detection elements 14 _R is valid The spatial variation (temperature compensation variable) W (x, y) is almost equal to the average value μ _W (x, y) of the distribution of temporal fluctuations. Can do.

  In other words, the average value of temporal fluctuations that cannot be obtained unless a plurality of dark readings are performed is the spatial average value W (x, y) of the dark reading values D (x, y) obtained by one dark reading. y) can be substituted with a small error.

  Here, the radiation detection elements (x ′, y ′) other than the one radiation detection element (x, y) when calculating the temperature compensation variable W (x, y) for the one radiation detection element (x, y). ) Will be described.

In the radiation detection element (x, y), the radiation detection element (x, y) is usually output when the temperature of the radiation detection element (x, y) or the reading circuit for reading out the signal value is low. The dark read value D (x, y) is a small value, and as the temperature T of the radiation detection element (x, y) increases, the output dark read value D (x, y) also increases. It is known. Therefore, for example, the average value μ _D (x, y) of the temporal fluctuation distribution of the dark read value D (x, y) output from each radiation detection element (x, y) as shown in FIG. As the temperature rises, it shifts to the right on the graph in the figure.

  Further, for example, when the power of the radiation image detector 1 is turned on, the temperature of the sensor panel unit 4 gradually increases. However, each radiation detection element (x, y) on the sensor panel unit 4 and elements of the readout circuit The temperature variation is not uniform. For example, the radiation detection element (x, y) at the center of the sensor panel unit 4 in which a large number of radiation detection elements (x ′, y ′) are present around the sensor panel unit 4 The radiation detection element (x, y) in the peripheral portion has a different temperature variation method, and the temperature variation method differs if the readout IC constituting the readout circuit is different. Even within the same readout IC, if the amplifier circuit 17 is different, the manner of temperature variation is different.

  In such a situation, other than the one radiation detection element (x, y) when calculating the spatial average value (temperature compensation variable) W (x, y) for one radiation detection element (x, y). As the radiation detection element (x ′, y ′), for example, when a radiation detection element (x ′, y ′) far from the one radiation detection element (x, y) on the sensor panel unit 4 is selected, its temperature It is predicted that the fluctuation is different from the temperature fluctuation of the one radiation detection element (x, y).

  Therefore, for example, as shown in FIG. 7, the dark reading value D (x ′, y ′) output from each radiation detection element (x ′, y ′) in the left-right direction depends on the temperature of the distribution of temporal fluctuations. The degree of shift is different from the degree of shift of the temporal fluctuation distribution of the dark reading value D (x, y) of the one radiation detection element (x, y), and the relative positions on the graph are respectively It fluctuates depending on the temperature of the pixel position.

In this way, the distribution of temporal fluctuations of the dark reading value D (x, y) of the radiation detection element (x, y) and the distribution of temporal fluctuations of the other radiation detection elements (x ′, y ′) depending on the temperature. If the position on the graph is relatively shifted depending on the temperature of each pixel position, as shown in FIG. 9, the spatial average value (temperature compensation variable) W (x, y) The distribution becomes broad and a distribution with a small standard deviation σ _W (x, y) as shown in FIG. 8 cannot be obtained. Therefore, the spatial average value (temperature compensation variable) W (x, y) calculated according to the above equation (3) is the temporal average value μ _{W of the} spatial average value (temperature compensation variable) W (x, y). The beneficial effect of being approximately equal to (x, y) cannot be used.

  Therefore, in this method, the spatial average value (temperature compensation variable) W (x, y) for one radiation detection element (x, y) from the result of one dark reading performed immediately before or after radiographic imaging. As a radiation detection element (x ′, y ′) other than the one radiation detection element (x, y) for calculating the radiation detection, a radiation detection that changes in temperature in the same manner as the one radiation detection element (x, y). The element (x ′, y ′) is selected in advance and is associated with the one radiation detection element (x, y) in advance.

At this time, it is not necessary to select all the radiation detection elements (x, y) on the sensor panel unit 4 in the same manner, and the selection method may be different for each radiation detection element. As a selection method, for example, as described above, a plurality of radiation detection elements (x, y) _R existing in an n × n square region centered on the one radiation detection element (x, y) are selected. Although it can be used, as shown in FIGS. 16 (A) to 16 (C) and FIGS. 19 (C) and 19 (D) which will be described later, the square region does not necessarily have the one radiation detection element (x, y). It does not have to be set to exist in the center.

  In addition, in this embodiment, the size of the square area is 5 × 5 or 7 × 7 (refer to the description in FIGS. 24 to 26 to be described later for an example of 7 × 7), but is limited to this size. Not what you want. As long as the size is larger than 1 × 1, it may be 2 × 2, 3 × 3, or 9 × 9 or larger. In addition, a rectangular area can be set instead of the square area, or an indefinite area can be used.

Further, the radiation detection elements (x ′, y ′) other than the one radiation detection element (x, y) are radiation detection elements that change in temperature in the same manner as the one radiation detection element (x, y). Well, it is scattered on the sensor panel unit 4 instead of the radiation detection elements (x, y) _R existing in the spatially continuous region including the one radiation detection element (x, y) as described above. It may be a radiation detection element (x, y). The detection element group exhibiting the same temperature characteristics can be grasped in advance during factory inspection or the like. It can also be reset after the establishment of the facility.

  Next, the relationship between the spatial average value W (x, y) used as the temperature compensation variable and the true value of the offset correction value O (x, y) of the one radiation detection element (x, y). explain.

  In the dark reading performed once just before or immediately after radiographic imaging, as shown in FIG. 10, one dark reading value including temporal fluctuation is received from one radiation detection element (x, y). Only D (x, y) is obtained, and the true value of the offset correction value O (x, y) is not known. Further, each dark read value D () output from each of the radiation detection elements (x−2, y−2) to (x + 2, y + 2) associated with the one radiation detection element (x, y). x−2, y−2) to D (x + 2, y + 2) also include temporal fluctuations, and based on them, the offset correction value O (1) of the one radiation detection element (x, y) is directly selected. The true value of x, y) cannot be obtained.

  Therefore, in this method, as will be described in detail below, the dark detection is performed a plurality of times at the time of past calibration (performed before radiography of the current subject), and the one radiation detection element (x, y) A dark reading value d (x, y) output from itself is obtained, and first, a plurality of dark reading values d (x, y) output from one radiation detection element (x, y) are obtained. A temporal average value δ (x, y) is calculated.

  Further, as a temperature compensation variable, from each of the plurality of radiation detection elements (x, y) in the square region centered on the one radiation detection element (x, y) in each dark reading at the time of past calibration. Spatial average value of dark reading value d to be output (hereinafter, spatial average value W (x, y) as a temperature compensation variable obtained by one dark reading performed immediately before or after the above radiographic imaging) In order to distinguish them from each other, a spatial average value as a temperature compensation variable obtained at the time of calibration is expressed as w (x, y)), and a spatial average value w (x, The time average value ω (x, y) for a plurality of times of y) is calculated.

  The temporal average value δ (x, y) of the dark read value d (x, y) of the one radiation detection element (x, y) itself and the spatial average value w ( (x, y) temporal average value ω (x, y) and spatial average value W (as a temperature compensation variable) obtained by one dark reading performed immediately before or after the current radiographic imaging. x, y) is used to calculate the offset correction value O (x, y) of the one radiation detection element (x, y).

  In the present invention, the term “calibration” refers not only to the calibration for updating both the gain correction value and the offset correction value that are performed regularly (for example, every month) as described above, but also compared with the gain correction value. Also included is offset calibration that is performed only when necessary, with respect to offset correction values with large dynamic temperature fluctuations.

  In other words, in the present invention, calibration refers to the dark reading value D (x, x, as necessary) when the radiation image detector 1 is shipped from the factory, introduced into the facility, or during standby when radiation is not exposed. This is an operation for acquiring and creating all or part of the data for correcting the photographed image data F (x, y) including y) in advance, rather than the calibration performed periodically as described above. It is a broad concept.

  Therefore, the calibration after introduction into the facility may also be performed with a shorter cycle (for example, every day) than the periodic calibration. In one calibration and offset calibration, dark reading is usually performed a plurality of times.

  It should be noted that if the temporal average value δ (x, y), the spatial average value w (x, y) as the temperature compensation variable, and the temporal average value ω (x, y) are calculated using too old data, Therefore, the dark reading value d (x, y) from which these values are calculated is the value obtained by the dark reading from the present to the predetermined number of times or the latest (that is, It is preferable to use a value obtained by a plurality of dark readings performed in the previous calibration or offset calibration.

  Further, the process of calculating the temporal average value δ (x, y) or the like from the dark read value d (x, y) may be performed by the radiation image detector 1 or from the radiation image detector 1 to the console 31 ( It is also possible to transmit the dark read value d (x, y) to an external device such as FIG.

Now, the temporal average value δ (x, y) of each dark read value d (x, y) of the one radiation detection element (x, y) itself obtained by the above-mentioned multiple times of dark reading is as follows. Is calculated according to the following equation (7). In the following equation (7), M represents the number of dark read values d _m (x, y) used for calculating the temporal average value δ (x, y) or the like, that is, the predetermined number of times.

As shown in FIG. 11, the dark read value d _m (x, y) is output from the one radiation detection element (x, y) in the m-th (m = 1 to M) dark read, and these values are output. When collectively expressed in a histogram, as shown in FIG. 12, the distribution is in a normal distribution with the temporal average value δ (x, y) as the center and the standard deviation σ _d (x, y). This distribution represents the temporal fluctuation of the dark reading value d _m (x, y).

Further, in the m-th (m = 1 to M) dark reading at the time of past calibration, a plurality of radiation detecting elements (x, x, y) in the square region with the one radiation detecting element (x, y) as the center. y) The spatial average value w _m (x, y) of each dark read value d _m (x, y) output from _R is calculated according to the following equation (8) similar to the above equation (3). In this case, N in the equation (8) is also 25 (= 5 × 5).

Then, the temporal average value ω (x, y) for M times of the spatial average value w _m (x, y) of each time is calculated according to the following equation (9).

As shown in FIG. 11, spatial average values w _m (x, y) are calculated in the m-th (m = 1 to M) dark reading, and these values are collectively shown in a histogram as shown in FIG. 12. As shown, the distribution is in a normal distribution with a standard deviation σ _w (x, y) centered on the temporal average value ω (x, y).

In addition, by substituting the equations (8) and (7) into the above equation (9),
As can be seen from the above, if the temporal average value δ (x, y) for each radiation detection element (x, y) in M dark readings in the past calibration is calculated, each time Even if the spatial average value w _m (x, y) is not calculated for each, the dark reading value d _m (using the temporal average value δ (x, y) for each radiation detection element (x, y) is used. A temporal average value ω (x, y) of M times of the spatial average value w _m (x, y) of x, y) can be calculated.

  Here, the temporal average value δ (x, y) of the dark read value d (x, y) output from the one radiation detection element (x, y) in a plurality of dark readings at the time of past calibration. And the temporal average value ω (x, y) of the spatial average value w (x, y) as the temperature compensation variable and one dark reading performed immediately before or after the current radiographic image capturing. The relationship between the spatial average value W (x, y) as a temperature compensation variable and the true value of the offset correction value O (x, y) of the one radiation detection element (x, y) will be considered.

In general, calibration is often performed during start-up preparation or patient preparation without performing patient imaging, and dark reading at the time of calibration is usually performed under conditions of the same preset temperature T ₀ . It can be assumed that it is done below. Therefore, the temporal average value δ (x, y) and the spatial average value w (x, y) as the temperature compensation variable regarding the one radiation detection element (x, y) obtained by dark reading at the time of past calibration. ) Is a value at the temperature T ₀ .

On the other hand, the temperature T in the vicinity of the radiation detection element (x, y) or the radiation detection element (x, y) on the sensor panel unit 4 when radiographic imaging is performed is not necessarily calibrated as shown in FIG. It is not the temperature T ₀ during the operation.

  In particular, in the radiographic image detector 1, even when the power is on, when the radiographic image detector 1 is not used for radiographic imaging, the power consumption state is set to the sleep mode automatically or manually in order to reduce power consumption. As shown in FIG. 13, the temperature T of the radiation detection element (x, y) and the like rises in the imageable mode, and the sensor panel unit 4 in the sleep mode (see the portion S in the figure). As a result, the temperature T of the radiation detection element (x, y) or the like decreases.

  Further, as described above, in the radiation detection element (x, y), the dark read value D (x, y) that is normally output when the temperature T of the radiation detection element (x, y) or the like is low is small. As the temperature T of the radiation detection element (x, y), etc. increases, the dark read value D (x, y) output also increases.

Therefore, as shown in FIG. 14, a dark read value D (x, y) output from one radiation detection element (x, y) in one dark read performed immediately before or after the current radiographic imaging. ) Estimated from the center value (average value) of the temporal fluctuation distribution and the dark reading output from the radiation detection element (x, y) _R associated with the one radiation detection element (x, y). distribution of temporal fluctuation estimated for spatial average value W as a temperature compensation variable is the mean value of the values D _R (x, y) also increases or decreases the temperature T.

  That is, the distribution of the dark reading value D (x, y) in FIG. 14 and the distribution of the spatial average value W (x, y) as the temperature compensation variable are varied on the horizontal axis in FIG. Fluctuates left and right. In general, when the temperature T rises, the distribution tends to shift to the right on the horizontal axis, and when the temperature T falls, the distribution tends to shift to the left on the horizontal axis. The distribution of fluctuations such as the dark read value D (x, y) output from one radiation detection element (x, y) in one dark read performed immediately before or immediately after the current radiographic image capture is as follows. Since it is only estimated, it is displayed with a broken line in FIG.

However, as described above, even in that case, the temperature of the radiation detection element (x ′, y ′) _R including the one radiation detection element (x, y) similarly varies. Therefore, the position on the graph of FIG. 14 of the fluctuation distribution estimated for the dark read value D (x, y) output from the one radiation detection element (x, y) and the one radiation detection element ( x, it is estimated for radiation detection element associated with y) (x, y) spatial average value W as a temperature compensation variable is the mean value of the dark read value D _R to be output from the _R (x, y) The relative positional relationship of the temporal fluctuation distribution with respect to the position on the graph (that is, the distance between the average values of the respective distributions) should not change even if the temperature fluctuates.

By the way, if the current radiographic imaging is performed in an environment of temperature T ₀ , the average value μ _D (of the temporal fluctuation distribution estimated for the dark read value D (x, y) shown in FIG. x, y) and the average value μ _W (x, y) of the temporal fluctuation distribution estimated for the spatial average value W (x, y) as the temperature compensation variable are the past calibrations shown in FIG. Average value δ (x, y) of temporal fluctuation distribution of a plurality of dark reading values d _m (x, y) obtained by a plurality of dark readings at the time of the measurement, or the one radiation detection element (x, The average value ω (x, y) of the distribution of temporal fluctuations of the spatial average value w _m (x, y) of each dark read value d _m (x, y) output from the radiation detection element 14 _R including y) ).

Further, the above dark read values D (x, y) of the distribution of the temporal fluctuation of the average value μ _{D (x,} y) and the spatial average value W (x, y) as a temperature compensation variable temporal fluctuations Since the relative positional relationship with the average value μ _W (x, y) of the distribution does not change even when the temperature T changes as described above, the difference between the average values of the distributions, that is, the dark read value D (x , the average value of the distribution of the temporal fluctuation of _{y) μ D (x, y} ) and the spatial average value W as a temperature compensation variable (x, mean value of the distribution of the temporal fluctuation of y) mu _{W (x,} y The difference from) does not change even if the temperature T changes.

Therefore, the temporal average of the distribution of the dark reading values D (x, y) of the one radiation detection element (x, y) obtained by one dark reading performed immediately before or immediately after the current radiographic image capturing. The difference between the value μ _D (x, y) and the temporal average value μ _W (x, y) of the distribution of the spatial average value W (x, y) as the temperature compensation variable is expressed as ε (x, y) When placed (see Figure 14),
ε (x, y) = μ _D (x, y) −μ _W (x, y) (11)
Is the temporal average value δ (x) of the distribution of a plurality of dark reading values d _m (x, y) obtained by a plurality of dark readings at the time of past calibration shown in FIG. , Y) and the spatial average value w _m (x, y) of each dark read value d _m (x, y) output from the radiation detection element 14 _R including the one radiation detection element (x, y). The difference from the temporal average value ω (x, y) of the distribution of
δ (x, y) −ω (x, y)
Is equal to

That is,
ε (x, y) = μ _D (x, y) −μ _W (x, y)
= Δ (x, y) −ω (x, y) (12)
Is established.

Equation (12) is
μ _D (x, y) = ε (x, y) + μ _W (x, y) (13)
If the variable that can be calculated in advance at the time of calibration, that is, the value of ε (x, y) = δ (x, y) −ω (x, y) is known, then μ _W (x, y ) Indicates that μ _D (x, y) can be estimated.

Here, as described above, from the equation (6), W (x, y) ≈μ _W (x, y) (6)
Substituting this into equation (13) gives
μ _D (x, y) ≈ε (x, y) + W (x, y) (14)
The relationship is obtained.

If a variable that can be calculated in advance during calibration, that is, a value of ε (x, y) = δ (x, y) −ω (x, y) is known, the value is acquired later when radiographic images are taken. This means that μ _D (x, y) can be estimated if only the temperature compensation variable W (x, y) calculated from one dark image can be calculated.

Similarly to the above-described conventional case, the average value μ _D (x, y) of the temporal fluctuation distribution estimated for the dark read value _D (x, y) is exactly the radiation detection element (x, y). ) Offset correction value O (x, y) can be regarded as a true value.
O (x, y) ≈ε (x, y) + W (x, y) (15)
Can be rewritten.

  If a variable that can be calculated in advance during calibration, that is, a value of ε (x, y) = δ (x, y) −ω (x, y) is known, the value is acquired later when radiographic images are taken. This means that if only the temperature compensation variable W (x, y) calculated from one dark image can be calculated, O (x, y), that is, the true value of the offset correction value can be estimated. In other words, if a variable that can be calculated in advance at the time of calibration, that is, a value of ε (x, y) = δ (x, y) −ω (x, y) is known, If the temperature compensation variable W (x, y) for each pixel position in a single dark image is calculated no matter how the temperature of each element such as an electric circuit thereafter changes, radiation at the time of radiographic imaging This indicates that an ideal offset correction value O (x, y) in the temperature state of each element such as a detection element or an electric circuit is obtained.

Therefore, in this method,
O (x, y) = ε (x, y) + W (x, y) (16)
(Where ε (x, y) = δ (x, y) −ω (x, y))
Accordingly, the offset correction value O (x, y) of the radiation detection element (x, y) is calculated.

  As a result, a technique that becomes a framework for solving the above-described problems has been proposed.

  In the description so far, the temperature of each element in the radiation image detector 1 at the time of calibration has been assumed to be constant. However, when calibration is performed, the number of dark images acquired (the above-described M When the value of () increases, the temperature of each element in the radiation image detector 1 also varies during calibration.

As is clear from the above formulas (7) to (10), the larger the value of M, the more the temporal fluctuations of d _m (x, y) and w _m (x, y) are offset, and (16 The accuracy of ω (x, y) and δ (x, y), which influences the accuracy of the expression), is improved. The larger the value of M, the greater the value of ω (x, y) and δ (x, y). Means that it is more susceptible to temperature fluctuations.

  Therefore, the idea of temperature correction described so far is also applied to this problem.

Substituting (7) and (9) into (12),

here,
_{λ m (x, y) =} d m (x, y) -w m (x, y) ... (18)
After all,

Here, λ _m (x, y) is a temperature-corrected dark in which the temperature change of the dark read value d _m (x, y) at the time of calibration is corrected by the temperature compensation variable w _m (x, y). The reading value λ _m (x, y) can be considered.

If the temperature of each element in the radiation image detector 1 fluctuates during calibration, the distribution of d _m (x, y) becomes a very broad distribution as shown in FIG. 15. Therefore, the above (7) The temporal average value δ (x, y) of d _m (x, y) obtained by the equation cannot indicate a correct value.

Therefore, in general, when dark reading is performed a plurality of times during calibration and an average value thereof is obtained (in the past, the offset correction value is directly obtained by this method as described above), direct d _m (x, Instead of calculating the average value of y), as described above, ε (x, y) that is the average value (temporal average value) of the temperature-corrected dark read value λ _m (x, y) is obtained. In this case, it is possible to obtain an accurate dark reading temporal average value in which the temperature fluctuation is corrected. That is, ε (x, y) can be called a temporal average value of temperature-corrected dark reading.

The temperature-corrected dark reading value λ _m (x, y) and the temperature-corrected dark reading temporal average value ε (x, y) are used for dark reading at the time of calibration and also at the time of radiographic imaging. It can be applied to all operations that are performed multiple times and take the average (temporal average). Moreover, even if the value of M, which is the number of time averages, is large, it can be made less susceptible to temperature fluctuations.

  Similar temperature compensation can also be applied when obtaining the gain correction value G (x, y) during calibration. When obtaining the gain correction value G (x, y), radiation image data in a state where the subject is not placed is acquired with a predetermined radiation dose determined in advance, and offset correction is performed on this to obtain the gain correction value. In order to calculate G (x, y), if the radiographic image data acquired at this time is regarded as the actual image data F (x, y) of the present method, the gain correction subjected to the temperature correction similar to the present method is performed. Data G (x, y) can be obtained. In addition, it is preferable to similarly perform the above-described temperature correction on the offset correction value used when obtaining the gain correction value G (x, y). Thereby, a highly accurate gain correction value G (x, y) can be obtained, and as a result, good image data with a high SN ratio can be obtained.

In this method, in the distribution (see FIG. 12) of each dark read value d _m (x, y) output from the radiation detection element (x, y) in M dark readings during calibration, a temporal average is obtained. The value δ (x, y) is calculated, and further, the standard deviation σd (x, y) of the distribution is calculated,
d _m (x, y) −δ (x, y) (20)
d _m (x, y) / σd (x, y) (21)
Or
(D _m (x, y) −δ (x, y)) / σd (x, y) (22)
It is also possible to normalize each dark read value d _m (x, y) by performing the above-described calculation and configure the above processing based on each normalized dark read value.

[Example of method for selecting other radiation detection elements to be associated with radiation detection elements in advance]
As described above, in order to calculate the spatial average value W (x, y) as a temperature compensation variable for one radiation detection element (x, y), the radiation detection element (x, y) is associated in advance. The other radiation detection elements (x ′, y ′) may be any element that varies in temperature in the same manner as the one radiation detection element (x, y), and the method for selecting them is as described above. There can be various methods. Here, an example of a selection method according to the practical configuration of the radiation image detector 1 will be described.

  For example, in FIG. 6, a sufficient number of other radiation detection elements (x ′, x) in the row and column directions around one radiation detection element (x, y) on the sensor panel unit 4 of the radiation image detector 1. If there is y ′), the other radiation detection elements (x−2, y−2) to (x + 2) existing in, for example, a 5 × 5 square region centering on the one radiation detection element (x, y). , Y + 2) is shown. However, when the one radiation detection element (x, y) is in the peripheral portion of the sensor panel unit 4, the one radiation detection element (x, y) is centered in the square area of 5 × 5, for example. ) May not be located.

  Therefore, in such a case, for example, as shown in FIGS. 16A to 16C, the position of the one radiation detection element (x, y) represented by being darkly colored in the drawing is selected. Just do it.

In this case, in the calculation of the spatial average value w _m (x, y) in the dark reading at the time of calibration and the calculation of the temporal average value ω (x, y), the radiation detection element (x, The region R for y) is set in the same manner. Further, in FIGS. 16A to 16C, the numbers described above and to the left of each radiation detection element represented in a lattice pattern are the row direction of each radiation detection element (x, y) and It is a number representing the position in the column direction, and the left coordinate (x, y) represents the coordinate of the radiation detection element (x, y).

  On the other hand, as shown in FIG. 17, the readout circuit 9 (see FIG. 2) for reading out and amplifying an electrical signal from each radiation detection element (x, y) normally has 128 pixels or 256 pixels of radiation in the row direction. One readout IC 91, 92,... Is connected to each detection element (x, y), and the necessary number of them are arranged in parallel. In addition, since the temperature characteristics and noise characteristics of the readout ICs 91, 92,... On the readout circuit 9 side are not necessarily the same, the offset correction value O (x, y) of each radiation detection element (x, y) is the readout IC 91. , 92,...

  Therefore, as shown in FIG. 18, a read IC that reads an electrical signal from each radiation detection element belonging to the region R set to calculate the offset correction value O (x, y) of the radiation detection element (x, y). Are read out separately by the adjacent readout ICs 91 and 92, the values of the temperature compensation variables W (x, y) and ω (x, y) are set for each radiation detection element (x, y) belonging to the region R. There may be an error, and the offset correction value O (x, y) may not be calculated satisfactorily.

  In such a case, for example, as shown in FIGS. 19C and 19D, the radiation detection element (x, y) connected to the readout IC 91 and the radiation detection element connected to the readout IC 92, for example. Consider (x, y) separately. Then, the radiation detection element (x, y) existing in the vicinity of the boundary L between the readout ICs 91 and 92 is handled in the same manner as in the case of the peripheral portion of the sensor panel unit 4 so that one radiation detection element (x , Y), a plurality of radiation detection elements associated in advance can be selected from the radiation detection elements connected to the same readout IC 91.

  In FIGS. 19A and 19B, a plurality of radiation detection elements associated in advance with one radiation detection element (x, y) may be selected in the normal manner shown in FIG. It is shown.

[Features of defective pixel determination method and abnormal pixel determination method]
Hereinafter, features of the defective pixel determination method and abnormal pixel determination method in the present invention will be described.

  First, defective pixels are detected by carrying out post-manufacturing shipping inspections and inspections involving radiation irradiation during periodic calibration, and the pixel positions of the detected defective pixels are registered in the defective pixel map, As described above, it is operated and managed in association with the radiation image detector.

  As an example of a defective pixel, a pixel that constantly outputs a large pixel value (for example, a pixel whose signal value always reaches a saturation level), or a pixel that constantly outputs only a small pixel value (for example, a signal value that always remains) Can be easily determined for pixels that output only zero level values, and pixels that always output only constant signal values (pixels whose output pixel values do not change even when irradiated with radiation). Therefore, it is assumed that such a defective pixel has already been determined and registered in the defective pixel map.

  What is going to be solved here is an abnormal pixel that outputs an abnormal signal value at a certain probability, and whether or not these abnormal pixels are detected accurately without irradiation and whether they are defective pixels or not. Or a method of registering abnormal pixels in the defective pixel map, a method of appropriately processing abnormal pixels as abnormal pixels without registering them in the defective pixel map, or in image data irradiated with radiation This is a method for dealing with the abnormal pixels.

  Therefore, in the main method of the present invention, dark reading values (reading signals that do not require radiation irradiation) acquired during calibration or before and after radiographic imaging are used. Also, a method for determining defective pixels in consideration of temperature fluctuations of each element in the radiation image detector when determining defective pixels and abnormal pixels will be described. In addition, a method for detecting abnormal pixels from image data obtained by irradiating radiation and appropriately handling them will be described.

First, defective pixels and abnormal pixels that are desired to be solved by the present invention will be described. As shown in the equation (1), in order to obtain the final image data F _O (x, y), the offset correction value O (x, y) is subtracted from the photographed image data F (x, y), The difference is multiplied by a gain correction value G (x, y).
F _O (x, y) = (F (x, y) −O (x, y)) × G (x, y) (1)

Therefore, even if the actual image data F (x, y) has a normal pixel value, if the offset correction value O (x, y) or the gain correction value G (x, y) is abnormal, the calculation is performed. Since the final image data F _O (x, y) as a result shows an abnormal value, this is an abnormal pixel (a pixel that should be corrected originally).

Further, even if the offset correction value O (x, y) and the gain correction value G (x, y) are normal, if the value of the actual image data F (x, y) is abnormal, the calculation result is obtained. Since the final image data F _O (x, y) shows an abnormal value, this is also an abnormal pixel (a pixel that should be corrected originally).

  The pixel position (x, y) that outputs an abnormal pixel value with an offset correction value O (x, y), gain correction value G (x, y), and actual image data F (x, y) with a certain probability Abnormal pixels that are classified according to the intensity of the value (guideline indicating how abnormal) and the frequency of output of abnormal values are determined to be unacceptable or should not be permitted are registered in the defective pixel map as defective pixels. Do.

  Also, even if a pixel suddenly outputs an abnormal value, if it is determined that the intensity of the abnormal value (a guideline indicating how abnormal) or the frequency of outputting the abnormal value is an acceptable level, the abnormal pixel The same processing (correction processing, etc.) as that of the defective pixel is performed, but it is allowed not to register the defective pixel in the defective pixel map. Of course, all abnormal pixels may be registered as defective pixels in the defective pixel map.

  Here, the gain correction value G (x, y) is calculated by irradiating with radiation at the time of calibration, but the offset correction value O (x, y) can be calculated without irradiating with radiation. It is a parameter.

The inventors pay attention to the dark read value D (x, y) or dark read value d _m (x, y) used for calculation of the offset correction value, and detect abnormal pixels generated at a certain probability as dark read values. A method of finding and determining from D (x, y) or dark read value d _m (x, y) and processing as a defective pixel or an abnormal pixel (in some cases, registering an abnormal pixel as a defective pixel in a defective pixel map) I found it. The present inventors also found a method for detecting abnormal pixels in radiographic image data and appropriately processing them.

[Defective pixel determination method]
Hereinafter, first, an embodiment of a defective pixel determination method according to the present invention will be described with reference to the drawings. However, the present invention is not limited to the following illustrated examples.

  As shown in FIG. 5 and the like described above, even when the environment is at the same temperature T, the dark read value D (x, y) output from one radiation detection element (x, y) of the radiation image detector 1. A fluctuation (variation) occurs in y), and the fluctuation distribution is a normal distribution having a standard deviation σ (x, y) around the mean value μ (x, y).

  However, depending on the radiation detection element (x, y), the average value μ (x, y) of the distribution is a dark read value D (x ′, y ′) output from another radiation detection element (x ′, y ′). ) Distribution is far from the average value μ (x ′, y ′) or the fluctuation is very large, that is, the standard deviation σ (x, y) of the distribution is different from that of the other radiation detection elements (x ′, y). In some cases, it is much larger than the standard deviation σ (x ′, y ′) of the distribution of the dark reading value D (x ′, y ′) output from “′).

Therefore, in such a radiation detection element (x, y), the stability of the finally obtained image data F _O (x, y) is also deteriorated and becomes an abnormal value that can be regarded as a defective pixel. May end up. Hereinafter, the radiation detection element (x, y) that can be regarded as a defective pixel in this way is represented as a defective pixel (xs, ys).

  Further, although the standard deviation σ (x, y) of the dark read value D (x, y) falls within the normal range, there are pixels that occasionally output an abnormal value. Such pixels cannot be detected even if attention is paid only to the standard deviation σ (x, y) of the dark read value D (x, y). As described above, although the standard deviation σ (x, y) of the dark read value D (x, y) falls within the normal range, the pixel that occasionally outputs an abnormal value is also regarded as an abnormal pixel if it exceeds the allowable range. .

  Therefore, in the defective pixel determination method according to the present invention, when the radiation detection element (x, y) becomes an abnormal pixel with a certain probability, whether or not to register the defective pixel (xs, ys) from the occurrence probability and the degree of abnormality is determined. It comes to judge.

As described above, the dark reading value d _m (x, y) output from the radiation detection element (x, y) itself in the dark reading performed a plurality of times (M times) during the past calibration (M, M). Data) is accumulated for each radiation detection element (x, y). And their dark read values _d m (x, y) expressed together in a histogram, as shown in FIG. 12, each radiation detection element (x, y) dark read value for each _d m (x, y ) Temporal statistical values such as the temporal average value δ (x, y) and standard deviation σd (x, y) of the temporal fluctuation distribution.

Therefore, in this way, the dark read value d _m (x, y) itself output from one radiation detection element (x, y) obtained in dark reading performed a plurality of times during past calibrations is itself. Or based on temporal statistical values such as temporal average value δ (x, y) and standard deviation σd (x, y) in the distribution of temporal fluctuations of dark reading value d _m (x, y) According to each determination method, it is determined whether the one radiation detection element (x, y) is a defective pixel.

[Determination method 1]
First, attention is paid to the standard deviation σd (x, y) in the temporal fluctuation distribution of the dark read value d _m (x, y) output from one radiation detection element (x, y) as a temporal statistical value. When the standard deviation σd (x, y) is larger than a preset threshold σdth, the one radiation detection element (x, y) is determined as a defective pixel (xs, ys) and registered. Is possible.

Dark read value d _{m (x,} y) of the temporal fluctuation standard deviation .sigma.d (x, y) in the distribution of that large, dark read value d _{m (x,} y) output an abnormal value with some probability Therefore, if the pixel is larger than a preset threshold value σdth, it is determined as a defective pixel (xs, ys) and is registered in the defective pixel map. Can solve the problem.

That is, the standard deviation in the fluctuation distribution of the dark read value d _m (x, y) output from one radiation detection element (x, y) obtained in the dark reading performed a plurality of times during the past calibration. σd (x, y) is equal to or less than the threshold σdth, that is,
σd (x, y) ≦ σdth (23)
If so, the fluctuation (variation) in the dark read value d _m (x, y) of the one radiation detection element (x, y) is within an allowable range, and is determined to be a normal pixel. In this case, the one radiation detection element (x, y) is not registered as a defective pixel.

However, as shown in the normal distribution on the right side of FIG. 20, the standard deviation σd (x) in the temporal fluctuation distribution of the dark read value d _m (x, y) output from one radiation detection element (x, y). , Y) is an average standard deviation in the temporal fluctuation distribution of the dark read value d _m (x, y) output from the normal radiation detection element (x, y) shown in the normal distribution on the left side of FIG. When larger than σd (x, y) and exceeding the threshold σdth, that is,
σd (x, y)> σdth (24)
Is satisfied, the temporal fluctuation (variation) of the dark read value d _m (x, y) of the one radiation detection element (x, y) exceeds the allowable range and is determined to be a defective pixel. Is done. In this case, the one radiation detection element (x, y) is registered in the defective pixel map as a defective pixel (xs, ys).

The threshold value σdth is, for example, 3 of the average standard deviation σd (x, y) in the distribution of temporal fluctuations of the dark reading value d _m (x, y) output from the radiation detection element (x, y). The value is preferably set to a value of about 10 to 10 times, but is not limited to this value.

Note that the variance σd ² (x, y) is used instead of the standard deviation σd (x, y), a threshold is set for the variance σd ² (x, y), and processing is performed in the same manner as described above. Is also possible.

[Determination method 2]
In addition, as a temporal statistical value, a temporal average value δ (x, y) in a temporal fluctuation distribution of the dark read value d _m (x, y) output from one radiation detection element (x, y) is used. Paying attention, another threshold value in which the temporal average value δ (x, y) is larger than a preset threshold value δth1 (hereinafter referred to as the first threshold value δth1) or smaller than the threshold value δth1. If it is smaller than δth2 (hereinafter referred to as the second threshold δth2), it can be considered that the one radiation detection element (x, y) has a defect, so this is regarded as a defective pixel (xs , Ys) can be determined and registered.

If dark read value d _{m (x,} y) the temporal average value in the distribution of the temporal fluctuations of [delta] (x, y) is too large or too small, the dark read value d _{m (x,} y) in the future This also indicates that there is a high possibility that an abnormal value is output with a certain probability. Therefore, if the value is larger than the preset first threshold value δth1 or smaller than the second threshold value δth, the defective pixel (xs, ys) ) And registering it in the defective pixel map can solve the problem recognized by the present invention as a problem.

That is, the time of the dark read value d _m (x, y) output from one radiation detection element (x, y) obtained in dark reading performed a plurality of times (M times) at the time of past calibration. Similar to the other radiation detection elements (x ^* , y ^* ), the temporal average value δ (x, y) in the fluctuation distribution is equal to or higher than the second threshold δth2 and lower than the first threshold δth1, that is,
δth2 ≦ δ (x, y) ≦ δth1 (25)
If so, the magnitude of the dark read value d _m (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The magnitude of the dark read value d _m (x ^* , y ^* ) does not change so much and is within the allowable range and is determined to be a normal pixel. In this case, the one radiation detection element (x, y) is not registered as a defective pixel.

However, as shown in FIG. 21, the temporal average value δ (x, y) in the temporal fluctuation distribution of the dark read value d _m (x, y) output from one radiation detection element (x, y) is obtained. Is greater than the threshold δth1, that is,
δ (x, y)> δth1 (26)
Or the temporal average value δ (x, y) in the temporal fluctuation distribution of the dark read value d _m (x, y) output from one radiation detection element (x, y) is small, If it is smaller than the threshold δth2, that is,
δ (x, y) <δth2 (27)
Is satisfied, the magnitude of the dark read value d _m (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The difference between the dark read value d _m (x ^* , y ^* ) and the read value is large and exceeds the allowable range, and is determined to be a defective pixel. In this case, the one radiation detection element (x, y) is registered in the defective pixel map as a defective pixel (xs, ys).

[Determination method 3]
Further, as the temporal statistics, one radiation detecting element (x, y) consideration of the magnitude itself of the value of the dark read values output from the d _{m (x,} y), dark read value d _{m (x,} when the value of y) is greater than the threshold value d _m th set in advance, since regarded as the the one of the radiation detecting element (x, y) has a defect from what defective pixels it It can be configured to determine and register as (xs, ys).

The value of the dark reading value d _m (x, y) itself being too large indicates that there is a high possibility that the dark reading value d _m (x, y) will output an abnormal value with a certain probability in the future. because there, defective pixel (xs, ys) is larger than the threshold value d _m th set in advance is determined as the, is possible to solve the problem of the present invention by registering the defective pixel map is recognized as problems it can.

That is, the value of the dark read value d _m (x, y) output from one radiation detection element (x, y) obtained in dark reading performed a plurality of times (M times) at the time of past calibration is obtained. , other radiation detecting elements ^(x *, ^{y *)} as well as the threshold _{d m} th or less, i.e.,
d _m (x, y) ≦ d _m th (28)
If so, the magnitude of the dark read value d _m (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The magnitude of the dark read value d _m (x ^* , y ^* ) does not change so much and is within the allowable range and is determined to be a normal pixel. In this case, the one radiation detection element (x, y) is not registered as a defective pixel.

However, when the value of the dark read value d _m (x, y) output from one radiation detection element (x, y) is larger than the threshold value d _m th, that is,
d _m (x, y)> d _m th (29)
Is satisfied, the magnitude of the dark read value d _m (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The difference between the dark read value d _m (x ^* , y ^* ) and the read value is large and exceeds the allowable range, and is determined to be a defective pixel. In this case, the one radiation detection element (x, y) is registered in the defective pixel map as a defective pixel (xs, ys).

In the above [determination method 1] to [determination method 3], the dark read value d output from the radiation detection element (x, y) itself in the dark reading performed a plurality of times (M times) at the time of past calibration. A case has been described in which only _m (x, y) is used to determine whether or not the one radiation detection element (x, y) is a defective pixel from the temporal statistical value. That is, during the dark reading period that is performed a plurality of times (M times), the signal value output from the radiation detection element (x, y) is not affected by the temperature change, or the signal value is not affected by the temperature change. It was considered small enough to be ignored.

  However, if the signal value output from the radiation detection element (x, y) is affected by a temperature change during a plurality of (M times) dark reading periods, it is more accurate to compensate for this temperature change. A good judgment can be made.

Therefore, by using the concept of temperature compensation at the time of calibration in the offset correction value method for each radiation detection element of the radiation image detector described above, the dark read value d output from one radiation detection element (x, y) itself. _m (x, y) and a plurality of radiation image detection elements that are associated with the one radiation detection element (x, y) in advance and change in temperature similarly to the one radiation detection element (x, y). Using the spatial average value w _m (x, y) of each dark read value d _m (x ′, y ′) output from (x ′, y ′), the one radiation detection element (x, A method of determining whether or not y) is a defective pixel and registering it will be described in [Determination Method 4] to [Determination Method 6].

  By adopting this temperature compensation concept, errors due to temperature can be removed when determining defective pixels, so that defective pixels can be determined accurately without being affected by temperature. It becomes.

[Determination Method 4]
The determination method described here is a method in which the concept of temperature compensation is incorporated in the above [determination method 1]. First, in a past calibration during several times (M times) carried out a dark read, in each time of the dark read, one radiation detecting element (x, y) dark output from its own readings d _{m (x,} y) and a plurality of radiation detection elements (x ′, y ′) that are associated with the one radiation detection element (x, y) in advance in the same manner as the one radiation detection element (x, y). ) And the difference e _m (x, y) represented by the following equation (30) with the spatial average value w _m (x, y) of each dark read value d _m (x ′, y ′) output from Is newly defined. That is, the spatial average value w _m (x, y) is used as a temperature compensation variable for the dark read value d _m (x, y).
_{e m (x, y) =} d m (x, y) -w m (x, y) ... (30)

The space of each dark read value d _m (x ′, y ′) output from a plurality of radiation detection elements (x ′, y ′) previously associated with the one radiation detection element (x, y). The average value w _m (x, y) is output from the one radiation detection element (x, y) itself in order to determine whether or not the one radiation detection element (x, y) is a defective pixel. Since it is used in contrast with the dark read value d _m (x, y), a plurality of radiation detection elements (x ′, y ′) that are targets for calculating the spatial average value w _m (x, y). It is preferable not to include the dark read value d _m (x, y) output from the one radiation detection element (x, y) in each dark read value d _m (x ′, y ′) from And a plurality of radiation detection elements (x ′, y ′) that are targets for calculating the spatial average value w _m (x, y) Each dark read values d _{m (x',} y') of et al in, the one of the radiation detecting element (x, y) dark read values output from the d _{m (x,} y) that may be included There is a way of thinking.

  Both of these are permissible and are not limited to either one. The same applies to the offset correction value acquisition method described above.

  In addition, a plurality of other radiation detection elements (x ′, y ′) that are associated with the one radiation detection element (x, y) in advance and change in temperature in the same manner as the one radiation detection element (x, y). ) Is selected as described above.

Now, in this way, past calibration at several times (M times) is calculated for each performed a dark read each time the dark reading difference e _{m (x,} y) expressed together the value of the histogram , the one of the radiation detecting element (x, y) if the normal pixel, for example, as shown in FIG. 22, the distribution of the difference e _{m (x,} y) of the temporal fluctuation (variation), the average standard The distribution is a normal distribution having a deviation σe (x, y).

However, the one of the radiation detecting element (x, y) is the defective pixel (xs, ys) If, dark read value output from the one radiation detection device _{(xs, ys) d m (} xs, ys) Since the fluctuation itself is much larger than that in the case of a normal pixel, the distribution of temporal fluctuation (variation) of the difference e _m (xs, ys) has a large standard deviation σe (xs, ys) as shown in FIG. It becomes a distribution of normal distribution having

Therefore, focusing on the standard deviation σe (x, y) in the temporal fluctuation distribution of the difference e _m (x, y), the standard deviation σe (x, y) is larger than a preset threshold σeth. In addition, the one radiation detection element (x, y) can be determined as a defective pixel (xs, ys) and registered.

That is, in the past upon calibration several times (M times) carried out a dark read, in each time of the dark read, one radiation detecting element (x, y) dark output from its own readings d _{m (x,} y) and each dark read value d _m (x ′, y ′) output from a plurality of radiation detection elements (x ′, y ′) previously associated with the one radiation detection element (x, y). spatial average _w m of (x, y) the difference _e m with (x, y) to calculate the standard deviation in the distribution of the temporal fluctuations of the difference _e m (x, y) Sigma] e (x, y) Is calculated as a temporal statistical value, and the standard deviation σe (x, y) is larger than a preset threshold σeth, that is,
σe (x, y)> σeth (31)
Is satisfied, it is determined that the one radiation detection element (x, y) is a defective pixel. In this case, the one radiation detection element (x, y) is registered in the defective pixel map as a defective pixel (xs, ys).

The above threshold σeth, as in the case of the threshold σdth described above, for example, 3 times to 10 times the average standard deviation σe in the distribution of the temporal fluctuations of the difference _{e m (x, y) (} x, y) Although it is preferable to set to a value of about, it is not limited to this value. Further, the variance σe ² (x, y) is used instead of the standard deviation σe (x, y), a threshold is set for the variance σe ² (x, y), and processing is performed in the same manner as described above. Is also possible.

The difference e _m (x, y) is a variable obtained by performing temperature compensation with w _m (x, y) on the dark read value d _m (x, y) as shown in the equation (30). Therefore, the error due to the temperature change of the dark reading value d _m (x, y) is canceled out. Accordingly, the standard deviation σe (x, y) of the temporal fluctuation of the difference e _m (x, y) is equal to the standard deviation σd (x, y) of the temporal fluctuation of the dark read value d _m (x, y). And
σe (x, y) ≦ σd (x, y) (32)
The relationship is established. That is, the spread of the histogram distribution of the difference e _m (x, y) is equal to or less than the spread of the histogram distribution of the dark read value d _m (x, y). Thus, it can be said that [Determination Method 4] has a smaller error with respect to temperature change than [Determination Method 1].

[Determination method 5]
The determination method described here is a method in which the concept of temperature compensation is incorporated into the above-mentioned [determination method 2].

As a temporal statistical value, attention is paid to a temporal average value in the distribution of temporal fluctuations of the difference ε _m (x, y). The time mean value of the distribution of the temporal fluctuations of even a difference cases shown above in FIGS. 22 and 23 _e m (x, y) is the aforementioned (12) epsilon (x, y) = δ (x, y) −ω (x, y) (12)
The calculation is equal to the temporal average value ε (x, y) of the temperature-corrected dark reading calculated in (1).

  Therefore, in this case, the temporal average value ε (x, y) of the temperature-corrected dark reading is larger than a preset threshold value εth1 (hereinafter, referred to as a first threshold value εth1), or is larger than the threshold value εth1. When the threshold value is smaller than another threshold value εth2 (hereinafter referred to as the second threshold value εth2) set to a small value, the one radiation detection element (x, y) is determined as a defective pixel (xs, ys), and the defect is detected. It is configured to be registered in the pixel map.

That is, the difference ε (x, y) obtained in the dark reading performed a plurality of times (M times) at the time of the past calibration is not less than the second threshold εth2 and not more than the first threshold εth1, that is,
εth2 ≦ ε (x, y) ≦ εth1 (33)
If so, the magnitude of the dark read value d _m (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The dark read value d _m (x ^* , y ^* ) does not vary greatly and is determined to be within the allowable range and to be a normal pixel. In this case, the one radiation detection element (x, y) is not registered as a defective pixel.

However, if the temporal average value ε (x, y) of the temperature-corrected dark reading is larger than the threshold value εth1, that is,
ε (x, y)> εth1 (34)
Or, when the temporal average value ε (x, y) of the temperature-corrected dark reading is smaller than the threshold value εth2, that is,
ε (x, y) <εth2 (35)
Is satisfied, the magnitude of the dark read value d _m (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The difference between the dark read value d _m (x ^* , y ^* ) and the read value is large and exceeds the allowable range, and is determined to be a defective pixel. In this case, the one radiation detection element (x, y) is registered in the defective pixel map as a defective pixel (xs, ys).

Note that the temporal average value ε (x, y) of the dark corrected temperature reading is the temporal average value δ (x, y) of the dark reading value d _m (x, y) as shown in the equation (12). Therefore, the error due to the temperature change of the dark read value d _m (x, y) is canceled out. Thus, it can be said that [Determination Method 5] is a method with less error with respect to temperature change than [Determination Method 2].

[Determination method 6]
The determination method described here is a method in which the concept of temperature compensation is incorporated into the above-mentioned [determination method 3]. That is, as a temporal statistical value used for determination, instead of each dark reading value d _m (x, y), it is the absolute value of the difference e _m (x, y) defined by the equation (30) | e _{Use m} (x, y) |.

What is the one radiation detection element (x, y) when the absolute value | e _m (x, y) | of the difference e _m (x, y) is larger than a preset threshold value e _m th Therefore, it is possible to determine that this is a defective pixel (xs, ys) and register it as a defective pixel (xs, ys).

That is, the dark read value d _m (x, y) output from one radiation detection element (x, y) obtained in the dark reading performed a plurality of times (M times) at the time of past calibration and the spatial Similar to the other radiation detection elements (x ^* , y ^* ), the absolute value of the difference e _m (x, y) of the average value w _m (x, y) is equal to or less than the threshold value e _m th, that is,
| E _m (x, y) | ≦ e _m th (36)
If so, the magnitude of the dark read value d _m (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The magnitude of the dark read value d _m (x ^* , y ^* ) does not change so much and is within the allowable range and is determined to be a normal pixel. In this case, the one radiation detection element (x, y) is not registered as a defective pixel.

However, if the absolute value of one radiation detecting element (x, y) the difference _e m calculated for (x, y) is larger than the threshold value _{e m} th, i.e.,
| E _m (x, y) |> e _m th (37)
Is satisfied, the magnitude of the dark read value d _m (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The difference between the dark read value d _m (x ^* , y ^* ) and the read value is large and exceeds the allowable range, and is determined to be a defective pixel. In this case, the one radiation detection element (x, y) is registered in the defective pixel map as a defective pixel (xs, ys).

The difference e _m (x, y) is a variable obtained by performing temperature compensation with w _m (x, y) on the dark read value d _m (x, y) as shown in the equation (30). Therefore, the error due to the temperature change of the dark reading value d _m (x, y) is canceled out. Thus, it can be said that [Determination Method 6] is a method with less error with respect to temperature change than [Determination Method 1].

  Further, in the above [determination method 1] to [determination method 6], a pixel exceeding a predetermined threshold is not registered as a defective pixel immediately, but is registered as a defective pixel, for example, based on the number of times (frequency). You may make it determine whether to do. Further, a plurality of threshold values are set at a predetermined interval, a histogram (the number of abnormal pixels entering a predetermined interval) for each interval is calculated, and the interval position and the occurrence frequency of abnormal pixels in the interval are calculated. Accordingly, it may be determined whether or not to register a defective pixel.

As described above, according to the defective pixel determination method according to the present embodiment, for example, the standard deviation σd (x, y) is significantly large in the fluctuation distribution of the dark read value d _m (x, y). A radiation detection element (x, y) in which the temporal average value δ (x, y) in the fluctuation distribution is an abnormal value or the dark read value d _m (x, y) itself is an abnormal value. It is possible to accurately find the radiation detection element (x, y) as a defective pixel and register it in the defective pixel map.

Therefore, by registering such defective pixels in advance, the offset correction value O (x, y) is calculated, or the actual image data F (x, y) is corrected to obtain the final image data F _O. When generating (x, y), it is possible to accurately eliminate the adverse effect of such defective pixels, and to improve the SN ratio of the final image data F _O (x, y). Is possible.

  In addition, by registering defective pixels in advance, it is possible to register and manage them collectively in the form of, for example, a defective pixel map in the same way as a defective pixel group registered as a defective pixel due to other factors. It becomes.

Furthermore, as described above, the dark read value d _m (x, y) output from the radiation detection element (x, y) increases or decreases due to temperature fluctuation. However, according to the above [Determination Method 4], [Determination Method 5], and [Determination Method 6], from each radiation detection element (x, y) itself for each dark reading at the time of past calibration. The dark read value d _m (x, y) that is output and each dark that is output from a plurality of radiation detection elements (x ′, y ′) associated in advance with the one radiation detection element (x, y). A difference ε _m (x, y) from the spatial average value w _m (x, y) of the read value d _m (x ′, y ′) is calculated, and based on the difference, the one radiation detection element (x, y) is calculated. ) Is a defective pixel.

Therefore, by paying attention to the difference ε _m (x, y), the radiation detection element (x, y) is removed in the state where the influence of the value variation due to the temperature variation of the dark read value d _m (x, y) is removed. It is possible to determine whether or not the pixel is a defective pixel, and the defective pixel can be found more stably without being affected by the temperature.

  [Decision method 1] to [determination method 3] or [determination method 4] to [determination method 6] can be used independently to register defective pixels, but [determination method 1] to [Determination Method 3] or a combination of [Determination Method 4] to [Determination Method 6], for example, [Determination Method 1] and [Determination Method 3] or [Determination Method 4] and [Determination Method 6] , [Determination Method 1], [Determination Method 2], [Determination Method 3] or [Determination Method 4], [Determination Method 5], and [Determination Method 6] are used to register defective pixels with higher accuracy. It can be performed.

Further, for each radiographic image capture, the dark read value D (x, y) immediately before and after the radiographing (or the average value of a plurality of dark read values D _m (x, y) when there are a plurality of dark read values) is offset. When used as the correction value O (x, y), the dark read value D (x, y), the dark read value D _m (x, y), or the dark read value D immediately before and after radiographic imaging. _Using the above [Determination Method 3] or [Determination Method 6] for the average value of _m (x, y), the dark reading value D (x, y) or the dark reading value D _m (x, y It is possible to determine and register defective pixels by determining whether or not the average value of y) or the dark read value D _m (x, y) is an abnormal value.

[Abnormal pixel determination method]
In the above [determination method 1] to [determination method 6], dark reading values of dark reading performed a plurality of times (M times) at the time of calibration and dark reading performed immediately before or immediately after radiographic imaging are used. Therefore, statistical determination including the occurrence frequency can be performed by sufficiently increasing the value of M. For this reason, it was possible to determine whether or not to determine as a defective pixel or whether or not to register.

  However, when using dark read values D (x, y) immediately before and after radiographic imaging, a sufficient number of dark read values D (x, y) cannot always be used as in calibration. In some cases (especially when dealing with one or two dark scans), the recognized abnormal pixel value is an unusual phenomenon that occurs very rarely, or an abnormal value that can be registered as a defective pixel. In some cases, it is difficult to determine whether or not is frequently occurring.

  Therefore, in this description, a case where such an abnormal pixel is temporarily registered as an abnormal pixel without immediately registering it as a defective pixel will be described. Whether or not to register these abnormal pixels as defective pixels will be described later.

  Hereinafter, an abnormal pixel determination method in the case where [Determination Method 6] is applied to the dark read value D (x, y) immediately before and after radiographic imaging will be described.

[Judgment method 7]
First, the difference E (x, y) between the dark read value D (x, y) and the spatial average value W (x, y) is defined as follows.
E (x, y) = D (x, y) -W (x, y) (38)

  When the absolute value of the difference E (x, y) is expressed as | E (x, y) |, the absolute value | E (x, y) | of the difference E (x, y) is greater than a preset threshold value Eth. Is larger, the one radiation detection element (x, y) can be regarded as having any abnormality, so that it is determined as an abnormal pixel and temporarily stored.

That is, the difference E (x, y) between the dark read value D (x, y) output from one radiation detection element (x, y) immediately before and after radiographic imaging and the spatial average value W (x, y). ) Is equal to or smaller than the threshold Eth, similarly to the other radiation detection elements (x ^* , y ^* ), that is,
| E (x, y) | ≦ Eth (39)
If so, the magnitude of the dark read value D (x, y) output from the one radiation detection element (x, y) is the dark output from the other radiation detection element (x ^* , y ^* ). The read value D (x ^* , y ^* ) is not much different from the size of the read value D (x ^* , y ^* ) and is within the allowable range, and is determined to be a normal pixel.

However, when the absolute value of the difference E (x, y) calculated for one radiation detection element (x, y) is larger than the threshold value Eth, that is,
| E (x, y) |> Eth (40)
Is satisfied, the magnitude of the dark read value D (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The dark read value D (x ^* , y ^* ) is greatly different from the allowable range and is determined to be an abnormal pixel.

  The difference E (x, y) is a variable obtained by performing temperature compensation with W (x, y) on the dark read value D (x, y) as shown in the equation (38). The error due to the temperature change of the dark reading value D (x, y) is cancelled.

If it is determined as an abnormal pixel, even if the pixel position is not registered in the defective pixel map, it is temporarily regarded as equivalent to the defective pixel, and, as with the defective pixel, abnormalities are detected by interpolation using surrounding pixel values. By performing a correction process for correcting an abnormal value of the pixel itself, it is possible to prevent an abnormal pixel from being generated in the final image data F _O (x, y).

  The method shown in [Determination method 7] can be further developed into [Determination method 8] shown below.

[Judgment method 8]
First, as in [Determination method 7], the difference E (x, y) between the dark read value D (x, y) and the spatial average value W (x, y) is calculated according to the equation (38).

Next, in the dark reading performed a plurality of times (M times) at the time of past calibration, the temporal average value δ (x) of the distribution of the dark reading value d _m (x, y) calculated according to the equation (12) , Y) and the difference ε (x, y) between the temporal average value ω (x, y) of the distribution of the spatial average value w _m (x, y) of the dark reading value d _m (x, y), The difference Λ (x, y) with the difference E (x, y) calculated by the equation (38) is obtained according to the equation (41).
Λ (x, y) = ε (x, y) −E (x, y) (41)

  Here, when the absolute value of the difference Λ (x, y) is expressed as | Λ (x, y) |, when the absolute value is larger than a preset threshold Λth, the one radiation detection element (x , Y) can be regarded as having an abnormality, so that it is determined as an abnormal pixel and temporarily stored.

That is, the absolute value of the difference Λ (x, y) is equal to or less than the threshold value Λth, like the other radiation detection elements (x ^* , y ^* ), that is,
| Λ (x, y) | ≦ Λth (42)
If so, the magnitude of the dark read value D (x, y) output from the one radiation detection element (x, y) is the dark output from the other radiation detection element (x ^* , y ^* ). The read value D (x ^* , y ^* ) is not much different from the size of the read value D (x ^* , y ^* ) and is within the allowable range, and is determined to be a normal pixel.

However, when the absolute value of the difference Λ (x, y) calculated for one radiation detection element (x, y) is larger than the threshold Λth, that is,
| Λ (x, y) |> Λth (43)
Is satisfied, the magnitude of the dark read value D (x, y) output from the one radiation detection element (x, y) is output from the other radiation detection element (x ^* , y ^* ). The dark read value D (x ^* , y ^* ) is greatly different from the allowable range and is determined to be an abnormal pixel.

  Note that the difference Λ (x, y) is an arithmetic operation between the difference ε (x, y) and the difference E (x, y), both of which are temperature compensated, as shown in the equation (41). Therefore, the error due to the temperature change of the dark read value D (x, y) is cancelled.

If it is determined as an abnormal pixel, even if the pixel position is not registered in the defective pixel map, it is temporarily regarded as equivalent to the defective pixel, and, as with the defective pixel, abnormalities are detected by interpolation using surrounding pixel values. By performing a correction process for correcting an abnormal value of the pixel itself, it is possible to prevent an abnormal pixel from being generated in the final image data F _O (x, y).

  In addition, regarding the handling of abnormal pixels shown in [Determination method 7] and [Determination method 8], any of the following options 1) to 5) can be employed.

Option 1) It is regarded as an abnormal pixel that occurs accidentally and is not registered as a defective pixel.
Option 2) Immediately register in the defective pixel map as defective pixel (xs, ys).
Option 3) Decide whether or not to register as a defective pixel according to the value of the abnormal pixel value. That is, when the value of an abnormal pixel is very large (when a threshold value for determining registration to a defective pixel determined separately is exceeded), it is registered in the defective pixel map as a defective pixel (xs, ys).
Option 4) As an abnormal pixel, a pixel position is stored separately from the defective pixel. After that, if the signal value at the same pixel position becomes an abnormal pixel with a certain frequency, the occurrence probability is determined at that time and determined in advance. When the generated occurrence probability threshold value is exceeded, it is registered in the defective pixel map as a defective pixel (xs, ys).
Option 5) The above options 3) and 4) are combined.

Regarding the above [Determination Method 4] to [Determination Method 8], the spatial average value w _m (x, y) and the spatial average value W (x, y), which are temperature compensation variables, and these temperature compensation variables are determined. Differences ε (x, y), differences e _m (x, y), differences E (x, y), absolute values | Λ (x, y) | ing. Here, if there is a sudden abnormal pixel that is not registered as a defective pixel in the spatial average value w _m (x, y) or the spatial average value W (x, y), the temperature compensation coefficient There is a concern that the accuracy of the value of the value decreases.

However, in the case of temperature compensation coefficient, the dark reading values (D (x, y) and _D m (x, y) and _d m (x, y)) surrounding the target pixel position (x, y) of Is the spatial average value of N pixel values, and even if there is a sudden abnormal pixel that is not registered as a defective pixel among the N peripheral pixels, the effect is reduced to 1 / N. However, it does not cause a big problem, but a separate means may be provided to detect sudden abnormal pixels and exclude them from the pixels used for calculating the temperature compensation variable.

Up to this point, the method for discriminating defective pixels and abnormal pixels using dark read values has been described. However, as described above, in order to obtain good final image data F _O (x, y), not only the offset correction value O (x, y) and the gain correction value G (x, y) but also the actual image. The image data F (x, y) is also required to be good.

That is, even if the defective pixel and the abnormal pixel are appropriately dealt with with respect to the offset correction value O (x, y) and the gain correction value G (x, y), the pixel of the actual image data F (x, y) If a sudden abnormal pixel is included in the value, the abnormal pixel is also recognized in the final image data F _O (x, y), which is not preferable. Therefore, it is preferable to take appropriate measures not only for defective pixel correction but also for abnormal pixels that occur suddenly for the real image data F (x, y).

  However, since the photographed image data F (x, y) has the following characteristics, it is not as easy to handle as the dark read value described so far.

1) In most cases, the photographed image data F (x, y) needs to be handled as the photographed image data F (x, y) that has been radiographed only once. In some cases, the same subject is photographed multiple times. In this case, since the subject is moved or the direction of the subject is changed during multiple radiographic image capturing, each of the independent photographed image data F (x , Y).

2) Radiation image capturing for acquiring actual image data F (x, y) is solid image capturing for acquiring gain correction data (solid image capturing is a uniform radiation without placing a subject. Except for shooting that is irradiated), the subject is always placed and the subject image is reflected in the real image data F (x, y).

  In addition, as described above, since the actual image data F (x, y) is independent data that is only radiographed once, the value of the actual image data F (x, y) accurately reflects subject information. It is difficult to judge objectively whether or not there is. For example, if radiation image capturing under the same conditions is performed a plurality of times on the same subject (assuming that the subject does not move during the plurality of capturing operations), a plurality of times are performed for a predetermined pixel position (x, y). By comparing the variations in image data, it can be determined whether or not subject information is reflected almost accurately from a statistical point of view.

  For example, when the average value of the signal values of the pixel position (x, y) in multiple radiographic imaging is calculated and the variation of each signal value from the average value is measured, if there is little variation, those signal values Can be determined to reflect the subject information almost accurately. On the other hand, if the value of a certain signal value deviates significantly from the average value with respect to the average value of the signal value at the pixel position (x, y) in multiple radiographic imaging, the signal value is The subject information is not accurately reflected, and it can be determined that the pixel is an abnormal pixel affected by noise or the like.

  In this way, if radiographic image capturing under the same conditions is performed for the same subject a plurality of times, it can be determined whether or not subject information is reflected almost accurately from a statistical viewpoint, but the actual image data F ( Since x, y) is independent data that is radiographed only once, such a statistical judgment cannot be made.

  Therefore, it is not known what value should be originally for each pixel value (value that each pixel value should be, that is, the true value of each pixel value). For example, if it is a dark reading value, it can be determined by statistical processing as described above whether the current data is normal or abnormal with respect to a plurality of data acquired at the time of calibration. There is no way to make the same determination for the real image data F (x, y) that is taken only once.

  A technique for discriminating suddenly abnormal pixels generated in the actual image data F (x, y) and taking appropriate measures in such a problem will be described below.

[Determination Method 9]
First, each pixel value of the live-action image data F (x, y) varies depending on the radiation absorption rate of the subject, but this is a signal value that changes very gently from a microscopic viewpoint of the pixel size level. There are many cases (the normal pixel size is often selected in the range of 100 to 200 microns, and the pixel size exceeding 200 microns is often not selected even though the selection is 100 microns or less). In particular, it can be said that there is no pixel in which only a specific pixel changes greatly. In addition, as a lesion having a size closest to the pixel level, there is microcalcification in mammography, which acts in the direction of absorbing radiation, and thus the signal value changes in the direction in which the signal value attenuates.

  Most of the abnormal pixels to be affected here act so that the signal value becomes large (abnormalities that act so that the signal value becomes small are already registered as defective pixels), so they act in the direction of absorbing radiation. A lesion that does not get confused with an abnormal pixel.

  On the other hand, since there are no lesions that act to increase the signal value and have a pixel-level size, an independent pixel that has a large value relative to surrounding pixels is regarded as a sudden abnormal pixel. No problem. In the present invention, this characteristic is used to suddenly determine abnormal pixels in the photographed image data F (x, y).

  Furthermore, a pixel that occurs suddenly is always an isolated pixel. In the first place, abnormal pixels that occur suddenly have a low frequency of occurrence (those with a high frequency of occurrence are already registered as defective pixels), and one flat panel detector usually has a pixel count of around 5 megapixels. Therefore, the probability that the sudden abnormal pixels in question are generated side by side or as a clustered cluster is astronomically small.

  Therefore, as described above, it may be considered that the sudden abnormal pixel taken up as a problem this time is always generated as an isolated pixel. Of course, it goes without saying that the case where they occur next to each other or the case where they occur as a cluster-like lump may be taken into consideration. However, in the following description, it is assumed that they occur as isolated pixels.

  In summary, the suddenly abnormal pixels in the actual photographed image data F (x, y) that are the subject of this time are considered to have the following properties.

1) An abnormal pixel always has a large signal value (behaves like a pixel irradiated with a lot of radiation)
2) An abnormal pixel is an isolated point. The pixels around the abnormal pixel are always normal pixels other than those registered as defective pixels.
3) A normal pixel changes smoothly in the direction in which the signal value increases, and does not show a large pixel change in units of one pixel.

  One embodiment of the method for discriminating the suddenly abnormal pixels will be described below with reference to FIG.

For example, the one radiation detection element (x, y), that is, the pixel position (x, y) as the plurality of radiation detection elements (x, y) is set as the target pixel position of the actual image data. Then, 25 pixel positions (x−2, y−2) to (x + 2, y + 2) existing in a 5 × 5 square area centered on the pixel position (x, y) are defined as comparison areas, and this When the average value of 24 signal values excluding the signal value at the pixel position (x, y) that is the target pixel from the signal value in the comparison area is expressed as A (x, y),

  Here, the value of L is 24 (= 5 × 5-1) in this case. In this example, L = 24 and a 5 × 5 square area centered at the pixel position (x, y) is described as the comparison area. However, the comparison area selection method is not limited to this. As L = 8 (= 3 × 3-1), a 3 × 3 square region centered at the pixel position (x, y) may be used as the comparison region, and for example, a square region having a size of 7 × 7 or larger may be used. Even if it adopts as a comparison field, the effect of the present invention is not spoiled. Further, if the region surrounding the pixel position (x, y) is selected as the comparison region, the comparison region is not necessarily a square region. In order to reduce the number of calculations, the comparison area may be four pixels above and below the pixel position (x, y), or the comparison area may be two pixels above and below the pixel position (x, y) or left and right.

Next, the difference V (x, y) is calculated according to the equation (45).
V (x, y) = F (x, y) −A (x, y) (45)

If this difference V (x, y) is less than or equal to a preset threshold value Vth, that is,
V (x, y) ≦ Vth (46)
If so, the value of the actual image data F (x, y) output from the one radiation detection element is used as it is without being changed.

On the other hand, when the difference V (x, y) is larger than a preset threshold value Vth, that is,
V (x, y)> Vth (47)
If so, the photographed image data F (x, y) output from the one radiation detection element is determined as an abnormal pixel, and the photographed image is obtained with the average value B (x, y) defined in the equation (49). The value of data F (x, y) is replaced (see equation (48)).
F (x, y) ← B (x, y) (48)

Here, nine pixel positions (x−1, y−1) to (x + 1, y + 1) existing in a 3 × 3 square area centered on the pixel position (x, y) are defined as calculation areas, The average value of the eight signal values excluding the signal value at the pixel position (x, y), which is the target pixel, from the signal value in this calculation area is defined as an average value B (x, y).

  In the equation (49), the value of P is 8 (= 3 × 3-1) in this case. In this example, P = 8 and a 3 × 3 square area centered at the pixel position (x, y) is described as the calculation area. However, the calculation comparison area selection method is not limited to this. As P = 24 (= 5 × 5-1), a 5 × 5 square area centered at the pixel position (x, y) may be used as the comparison area, and for example, a square area having a size of 7 × 7 or larger may be used. You may employ | adopt as a comparison area | region. Further, if a region surrounding the pixel position (x, y) is selected as the calculation region, the calculation region is not necessarily a square region. In order to reduce the number of calculations, the calculation area may be four pixels above and below the pixel position (x, y), or the calculation area may be two pixels above and below the pixel position (x, y).

  Here, the comparison area A (x, y) and the calculation area B (x, y) are individually defined (the comparison area and the calculation area do not necessarily match), but the comparison area A (x , Y) and the calculation area B (x, y) may be treated as the same. If a defective pixel exists in the comparison area or calculation area, the average value A (x, y) or average value B (x, y) can be calculated using normal pixels adjacent to the defective pixel. good.

As described above, if an abnormal pixel is suddenly dealt with in the real image data F (x, y), no abnormal pixel is generated in the final image data F _O (x, y). It is possible to stably supply a good diagnostic image. In addition, regarding the handling of the abnormal pixel detected here (whether or not to register as a defective pixel), any of the methods 1) to 5) described after [Determination Method 8] described above should be adopted. Is possible.

[Determination Method 10]
In the above description, the abnormal pixel in the actual image data F (x, y) is described as having a large signal value (behaves like a pixel irradiated with a lot of radiation). Also, the case where the signal value changes in a decreasing direction may be considered. That is,

1) An abnormal pixel always has an abnormal value in a direction of increasing or decreasing with respect to surrounding pixel values.
2) An abnormal pixel is an isolated point. The pixels around the abnormal pixel are always normal pixels other than those registered as defective pixels.
3) Normal pixels change smoothly and do not show large pixel changes in units of one pixel.
Judgment may be made.

That is, an absolute value | V (x, y) | for V (x, y) in the equation (45) is defined, and this absolute value | V (x, y) | is equal to or less than a preset threshold value V′th. If so, ie
| V (x, y) | ≦ V′th (50)
If so, the value of the actual image data F (x, y) output from the one radiation detection element is used as it is without being changed.

On the other hand, when the absolute value | V (x, y) | of the difference V (x, y) is larger than a preset threshold value V′th, that is,
| V (x, y) |> V′th (51)
If so, the photographed image data F (x, y) output from the one radiation detection element is determined as an abnormal pixel, and the photographed image is obtained with the average value B (x, y) defined in the equation (49). The value of the data F (x, y) may be replaced (see formula (48)). Hereinafter, it is the same as that described in [Determination Method 9].

[Determination method 11]
Further, as described above, since the lesion size of the microcalcification lesion in mammography is close to the pixel size level, the photographed image data F (x , Y), even if there is a radiation detection element that outputs, it is difficult to determine whether it is an image of actual microcalcifications present in the lesion or just an abnormal value is output. It is difficult to determine whether or not the radiation detection element can be regarded as an abnormal pixel based on the actual image data F (x, y) obtained by performing mammography.

  However, on the other hand, especially for the radiation image detector 1 used for mammography, it is necessary to know in advance which pixel (radiation detection element) outputs an abnormal signal value when radiation is irradiated. Otherwise, there is a problem that microcalcification is present but erroneously determined as an abnormal value, or the abnormal value is misdiagnosed as microcalcification.

  Therefore, the radiation image detector 1 is uniformly irradiated with radiation in a state where no subject is present, and the actual image data F (x, y) is transmitted from each radiation detection element (x, y). y) is output, and the abnormal pixel is determined in the same manner as in the above [determination method 10] based on each photographed image data F (x, y) acquired in a state where the subject does not exist. be able to.

  That is, in the state where no subject exists, the radiation incident surface X (see FIG. 1) of the radiation image detector 1 is irradiated with radiation so as to have a substantially constant dose over the entire surface, and each radiation detection element (x, It is assumed that the actual image data F (x, y) having substantially the same signal value is to be output from y).

In this state, V (x, y) is calculated according to the above equations (44) and (45) for the actual image data F (x, y) actually output from each radiation detection element (x, y). Then, an absolute value | V (x, y) | for V (x, y) is calculated, and if this absolute value | V (x, y) | is equal to or smaller than a preset threshold value V′th, that is, ,
| V (x, y) | ≦ V′th (50)
If so, it is determined that the one radiation detection element is not an abnormal pixel. In actual mammography, the value of the actual image data F (x, y) output from the one radiation detection element is used as it is without being changed. Further, it is more preferable to determine whether or not the pixel is an abnormal pixel based on the dark reading value, and to use the actual image data as it is only when it is determined that both are not abnormal pixels.

However, the absolute value of the difference V (x, y) is satisfied in spite of the situation where the actual image data F (x, y) having substantially the same signal value is to be output from each radiation detection element (x, y). When V (x, y) | is larger than a preset threshold value V′th, that is,
| V (x, y) |> V′th (51)
If so, the one radiation detection element is determined as an abnormal pixel. In such a case, since the peripheral pixel has an output value obtained by detecting normal tissue, the value obtained by interpolation using the value of the peripheral pixel cannot be used for the abnormal pixel. ) Announce the presence of abnormal pixels and encourage other radiological image detectors to be used. (2) Display the address of the abnormal pixel and display the area where the abnormal pixel exists outside the irradiation field area (outside the breast area) The operator, such as an engineer, is notified via the console that the radiographic image detector is to be changed in position with respect to the subject to be photographed.

So far, the description has been given of performing the abnormal pixel determination method and correction method individually for the offset correction value O (x, y) and the actual image data F (x, y). The pixel determination method and the correction method are not individually applied to the offset correction value O (x, y) and the actual image data F (x, y), but the final image data F _O which is the calculation result thereof. There is also a method implemented for (x, y).

The final image data F _O (x, y) is expressed by the following formula (1): F _O (x, y) = (F (x, y) −O (x, y)) × G (x, y) (1) )
Therefore, if there is an abnormal pixel in the offset correction value O (x, y) or the photographed image data F (x, y), the final image data F _O (x, y) also becomes an abnormal pixel. .

In most cases, the abnormal pixel changes in the direction in which the pixel value of the offset correction value O (x, y) or the photographed image data F (x, y) increases, so that the offset correction is performed in the calculation result of the above formula (1). If there is an abnormal pixel in the value O (x, y), the signal value of the final image data F _O (x, y) changes in a decreasing direction, and the actual image data F (x, y) has an abnormal pixel. For example, the signal value changes in the direction in which the signal value of the final image data F _O (x, y) increases.

For this reason, as a determination method, if the real image data F (x, y) of the above [determination method 10] is replaced with the final image data F _O (x, y), it will be described in [determination method 10]. It is possible to determine abnormal pixels by the same method as described above.

[Calculation method of spatial average when there are defective pixels]
Next, in the case where a radiation detection element having a defect (hereinafter referred to as a defective pixel) is included in another radiation detection element associated in advance with one radiation detection element (x, y), the one radiation detection element. A method of calculating the spatial average value W (x, y) as the temperature compensation variable of (x, y) will be described.

  In order to make the following explanation easy to understand, here, as shown in FIG. 24, the one radiation detection element (target pixel) for calculating the spatial average value W (x, y) as a temperature compensation variable is radiation. 7 × 7 radiation detection elements (1, 1) to (7, 7) centered on the radiation detection element (4, 4) are associated with the detection element (4, 4), A case where the radiation detection element (6, 6) is a defective pixel will be described.

[Calculation method 1]
The simplest calculation method includes a plurality of radiation detection elements (1, 1) to (7, 7) associated with the one radiation detection element (4, 4) in advance including the defective pixel (6, 6). 7) Using the dark reading values D (1, 1) to D (7, 7) output from 7),
The spatial average value W (4, 4) of the radiation detection element (4, 4) can be calculated by the above. However, with this calculation method, there is a possibility that W (4, 4) is affected by the dark read value D (6, 6) of the defective pixel (6, 6).

[Calculation method 2]
Output from the radiation detection elements excluding the defective pixel (6, 6) among the plurality of radiation detection elements (1, 1) to (7, 7) previously associated with the one radiation detection element (4, 4). Using only the dark read values D (1,1) to D (7,7) (excluding D (6,6)),
Thus, the spatial average value W (4, 4) of the radiation detection element (4, 4) can be calculated.

[Calculation method 3]
The value of the dark read value D (6, 6) output from the defective pixel (6, 6) is replaced with the dark read value output from the radiation detection element in the vicinity of the defective pixel (6, 6) to obtain a spatial average. It is also possible to configure to calculate the value W (4, 4).

For example, the dark reading value D (6, 6) output from the defective pixel (6, 6) is used as the dark reading value output from the radiation detection element (5, 6) in the vicinity of the defective pixel (6, 6). Using the value D (5,6)
D (6,6) ← D (5,6) (54)
Replace with Then, the spatial average value W (4, 4) of the radiation detection element (4, 4) is calculated according to the above equation (52).

  In this case, the dark reading value D (6, 6) output from the defective pixel (6, 6) is converted into the radiation detection element (5, 6) adjacent to the defective pixel (6, 6) inside the region R. For example, a radiation detection element that exists at a position outside the region R, such as the radiation detection element (8, 6) shown in FIG. , 6) can be configured to replace the dark read value D (6, 6) output from the defective pixel (6, 6) with the dark read value D output from the radiation detection element adjacent to the pixel. .

[Calculation method 4]
The dark read value D (6, 6) output from the defective pixel (6, 6) is interpolated with each dark read value D output from a plurality of radiation detection elements in the vicinity of the defective pixel (6, 6). The spatial average value W (4, 4) may be calculated.

  For example, the dark read value D (6, 6) output from the defective pixel (6, 6) is used as the radiation detection element (5, 5), (6, 5) in the vicinity of the defective pixel (6, 6). , (7,5), (5,6), (7,6), (5,7), (6,7), (7,7) , D (6,5), D (7,5), D (5,6), D (7,6), D (5,7), D (6,7), D (7,7) For example, the average value of these values is calculated, and the value of D (6,6) is interpolated with the average value. Then, the spatial average value W (4, 4) of the radiation detection element (4, 4) is calculated according to the above equation (52).

  In this case, for example, when the defective pixel is a radiation detection element (7, 6) present at the end of the region R as shown in FIG. 26, the defective pixel (7, 6) is output. The dark read value D (7,6) is calculated from the radiation detection elements (5,5), (6,5), (7,5), (5,6) in the vicinity of the defective pixel (7,6). , (6,6), (5,7), (6,7), (7,7), the dark read values D (5,5), D (6,5), D (7,7) 5), D (5,6), D (6,6), D (5,7), D (6,7), D (7,7) can be used for interpolation. is there.

  In addition, as shown in FIG. 26, radiation detection elements (8, 5), (8, 6), (8) that are radiation detection elements that are located outside the region R and are close to the defective pixel (7, 6). , 7) using the dark read values D (8, 5), D (8, 6), D (8, 7) output from the defective pixels (7, 6). The values of (7, 6) are set to the radiation detection elements (6, 5), (7, 5), (8, 5), (6, 6), (8, 6), (6, 7), (7 , 7), (8, 7), the dark read values D (6, 5), D (7, 5), D (8, 5), D (6, 6), D (8, 6) ), D (6, 7), D (7, 7), and D (8, 7) may be used for interpolation.

  In each of the calculation methods described above, the case where there is one defective pixel, that is, one point defect in the region R has been described. However, the same calculation method can be used when there are a plurality of point defects. . A similar calculation method can also be used when there is a line defect in which defective pixels exist in a line.

[Create thinned data]
In the present invention, the thinning data is created based on the actual image data F (x, y) by the control means 6 of the radiation image detector 1 or the console 31 of the radiation image generation system 30 described later.

  In creating the thinned data, the control means 6 and the console 31 of the radiographic image detector 1 use the actual image data F (x, y) output from each radiation detection element (x, y) of the radiographic imaging device 1. The thinned data is created by thinning out the real image data F (x, y) from the inside at a predetermined thinning rate. Here, an example of the thinned image data created in the present embodiment will be described.

  For example, when actual image data (number of pixels: 2010 × 2400) of half-cut size (14 × 17 inches) read with a pixel size of 175 μm is compressed to 1/15 both vertically and horizontally, the number of pixels of image data to be transmitted Is 134 × 160. In this case, for example, the photographed image data F (x, y) once stored in the storage unit 7 of the radiation image detector 1 or the photographed image transmitted from the radiation image detector 1 and stored in the storage unit of the console 31 or the like. When the data F (x, y) is read, the thinned data is created by reading the real image data F (x, y) every 15 pixels in the vertical and horizontal directions.

  When the thinning data is created by the control means 6 of the radiological image detector 1, in the above example, the control means 6 is, for example, real image data F (2010 × 2400) pixels F ( x, y) is generated by reading from the radiation detection element (x, y), and the thinned-out data f (x, y) as illustrated in FIG. 27B is generated based on the actual image data F (x, y). y) is created, and both are stored in the storage means 7 in association with each other.

  Note that the thinned data f (x, y) may be configured to be transmitted to the console 31 at the same time as the data is created. Further, if the vertical and horizontal thinning rates are the same as described above, the image aspect ratio can be kept the same as that of the original image (original image). Note that the reduction rate (compression rate) of the thinned data f (x, y) is not limited to the example illustrated here.

[Radiation image generation system]
Below, an example of embodiment of the radiographic image generation system which concerns on this invention is shown. In the present embodiment, the radiographic image generation system 30 includes the radiographic image detector 1 (see FIG. 1 and the like), a console 31, and server means 39, as shown in FIG.

  In the following description, the console 31 functions as an offset correction value generation unit that generates an offset correction value in radiographic image capturing in the radiographic image detector 1 based on the dark reading value transmitted from the radiographic image detector 1. The offset correction value generation processing is performed by the control means 6 of the radiological image detector 1, that is, the control means 6 of the radiographic image detector 1 can be configured as an offset correction value generation means. It is.

  The radiation image detector 1 is used by being loaded into a holding portion 33a of a bucky device 33 provided in the photographing room R1. The bucky device 33 is provided with a small operation unit 33b similar to a portable information terminal.

  In the present embodiment, one radiation source 34a of the radiation generator 34 is shared and used by the respective bucky devices 33, and the radiation image detector 1 is loaded into the bucky device 33 and used. In this case, when radiation is emitted from the corresponding radiation source 34a, the radiation generation timing control of the radiation generator 34 is linked with the control means 6 of the radiation image detector 1, and the radiation generator 34 Various controls of the radiation image detector 1 are performed based on the timing of radiation generation. In addition, it is also possible to constitute so that each radiation source 34a of the radiation generator 34 is provided in association with each Buckie device 33.

  The radiation image detector 1 can be used alone in a free state without being loaded into the bucky device 33. In this case, for example, the radiographic image detector 1 can be used on the bed-type bucky device 33, or the patient can use the radiographic image detector 1 with his / her hand.

  The radiation image detector 1 is provided with an antenna device 3 (see FIG. 1) which is a communication means for transmitting the dark read value D (x, y) or the like in a wireless manner. Further, the radiation image detector 1 is connected to an electrode (not shown) provided on the holding unit 33a when the radiation image detector 1 is loaded on the holding unit 33a of the bucky device 33, and the dark read value D (x, The terminal 13 (see FIG. 2) which is a communication means for transmitting y) etc. in a wired manner and a power supply means to the radiation image detector 1 is present in the antenna device 3 and the power switch 11 of the radiation image detector 1. It is provided in the side part opposite (facing) to the side part of the housing 2 to be operated. Further, a terminal 22 which is a power supply means for charging the battery 21 is provided on the same side surface portion as the terminal 13.

  As described above, when the radiation image detector 1 is loaded in the bucky device 33, the terminal 13 and the electrode of the holding unit 33 a are connected, and the dark read value D (x, y) and the like are transmitted via the cable 32. It is sent to the relay terminal 35 in a wired manner and is sent to the console 31 via the relay terminal 35. The radiographic image detector 1 is configured to supply power from the relay terminal 35 to the radiographic image detector 1 via the cable 32 and the terminal 13 when the radiographic image detector 1 is loaded in the bucky device 33.

  Further, when the radiation image detector 1 is used alone without being loaded into the bucky device 33, the dark read value D (x, y) or the like is transmitted via the antenna device 3 in a wireless manner. Yes. The radiographing room R1 is provided with a relay terminal 35 including a radio antenna 36 that relays when the radiological image detector 1 communicates the dark read value D (x, y) or the like to the console 31 in a wireless manner. Information such as the dark reading value D (x, y) transmitted from the antenna device 3 of the radiation image detector 1 by the wireless method is received by the wireless antenna 36 and transmitted to the console 31 via the relay terminal 35. It has become so.

  The radiographic image detector 1 is supplied with power from the relay terminal 35 via the cable 32 and the terminal 13 when loaded in the bucky device 33, but when used alone, the built-in battery 21 is used. It is designed to operate with the power of Note that the relay terminal 35 is provided with a terminal which is a power supply means (not shown) for charging the battery. When the terminal 22 of the radiation image detector 1 is brought into contact with the terminal on the relay terminal 35, the relay terminal 35 is not shown. Electric power is supplied to the battery 21 of the radiation image detector 1 via the terminal 22 and the battery 21 is charged. However, it is not limited to this form.

  The radiographic image detector 1 includes a tag (not shown). In this case, a so-called RFID (Radio Frequency IDentification) tag is used as the tag, and the tag includes a control circuit that controls each part of the tag and a storage unit that stores unique information such as the ID of the radiation image detector 1. Built in compact.

  A tag reader 37 that reads the RFID tag of the radiation image detector 1 is installed in the vicinity of the entrance of the front chamber R2. The tag reader 37 transmits predetermined instruction information on radio waves or the like via a built-in antenna (not shown), detects the radiation image detector 1 entering or leaving the front chamber R2, and detects the radiation image detector 1 An ID or the like is transmitted to the console 31.

  In addition, although the example in the case of incorporating an RFID tag in the radiation image detector 1 is shown, instead of incorporating the RFID tag in the radiation image detector 1, a radiation image is formed on the outer surface of the housing of the radiation image detector 1. A bar code in which the ID of the detector 1 and the like are written may be attached and read with a bar code reader. In this case, the tag reader 37 becomes a barcode reader, reads the barcode of the radiation image detector 1 entering or leaving the front chamber R2, and transmits the ID of the radiation image detector 1 to the console 31.

  The tag reader 37 and the barcode reader are installed in the vicinity of the entrance of the imaging room R1 instead of in the vicinity of the entrance of the front room R2, and the entrance / exit of the radiation image detector 1 to the imaging room R1 is managed. good.

  In this way, by using the RFID or the barcode, the radiation image detector 1 is informed of which radiation generating device (by which the radiation image detector 1 enters or leaves the anterior chamber R2 or the radiographing room R1 is notified to the console 31. In the case of this example, it is possible to automatically notify the console 31 and the radiation generator 34 of whether or not it is necessary to link with the radiation generator 34). Such management of entering or leaving the radiographic image detector 1 using the RFID or barcode functions effectively in a facility where there are a plurality of radiographing devices and radiation generators. When RFID or barcode is not used, the user may directly input information on entering or leaving the radiographic image detector 1 into the imaging room or the like to the console 31.

  The front chamber R2 is provided with a console 31 that controls the defective pixel determination system 30 and the entire radiation image generation system. The console 31 includes main units of the relay terminal 35, the tag reader 37, and the radiation generator 34 described above. 34 b and the like are connected, and a bucky device 33 and the like are connected via the relay terminal 35.

The console 31 includes a computer (not shown), a CPU (Central Processing Unit), a storage means such as a ROM, a RAM, and a hard disk, an input / output interface and the like connected to a bus, and includes real image data F (x, y) and thinned data. An image processing unit (not shown) that performs processing on f (x, y) is provided. Further, the console 31 is provided with a display unit 31a composed of a CRT (Cathode Ray Tube), an LCD (Liquid Crystal Display), or the like, and the thinned data f (x, y) described above is displayed on the display screen of the display unit 31a. ), Actual image data F (x, y), gain and offset correction processing, correction processing for defects and abnormal pixels, gradation processing according to the imaging region, etc. are performed and finally generated. The diagnostic image data F _O (x, y) and the like are displayed.

  The console 31 is connected to server means 39 comprising a computer via a network NW. The server means 39 is connected to a storage means 38 composed of a hard disk or the like.

  In the storage means 38 and the storage means (not shown) of the console 31 itself, in order to calculate the spatial average value described above for each radiation image detector 1 usable in the radiation image generation system, each radiation detection element (x, Information on which radiation detection element (x ′, y ′) is associated with y) is stored in advance in association with the ID of the radiation image detector 1.

Further, the console 31 from the radiographic image detector 1, the radiation detection elements in the read dark made during calibration (x, y) dark read values output from the d _{m (x,} y) and radiographic imaging When the dark reading values D (x, y) and D _m (x, y) obtained in the dark reading performed one or more times immediately before or after are transmitted by the wired method or the wireless method, In association with the ID of the radiation image detector 1, it is stored in its own storage means or the storage means 38 of the server means 39.

Further, the console 31 is configured to calculate the temporal average value δ (x, y) of the dark read value d _m (x, y) output from each radiation detection element (x, y) of the radiation detector 1 and each radiation. Spatial average as a temperature compensation variable of each dark read value d _m (x ′, y ′) output from a plurality of radiation detection elements (x ′, y ′) associated with the detection element (x, y) A temporal statistical value (temporal average value) ω (x, y) of the value w _m (x ′, y ′) is calculated and stored in the storage means 38 of the server means 39.

  The dark read value d (x, y) can be stored and the temporal average value δ (x, y) and the like can be calculated and stored by the console 31 or the storage means of the console 31. is there.

  The console 31 reads a program necessary for executing various processes stored in a storage means such as a ROM or a hard disk, expands it in a work area of the RAM, and executes the process according to the program. In the present embodiment, the storage means of the console 31 and the storage means 38 of the server means 39 (hereinafter simply referred to as storage means) include pixel positions (x, y) of defective pixels for each radiation image detector 1. The defective pixel map in which the information is registered is stored.

The storage means such as a ROM or a hard disk contains a defective pixel determination program for executing the above-described defective pixel determination, an abnormal pixel determination program for executing abnormal pixel determination, and thinned data f (x, y). A thinned data display program for displaying, a radiographic image generating program for generating final diagnostic image data F _O (x, y) from actual captured image data F (x, y) obtained by radiographic imaging, etc. Stored.

  The console 31 reads the defective pixel determination program and executes the above defective pixel determination method at the time of calibration. In the defective pixel determination program, which of the above-described defective pixel determination methods [determination method 1] to [determination method 6] is executed, or a combination of these determination methods is executed. Is appropriately determined.

When the console 31 performs the defective pixel determination described in [Determination Method 3] among the above-described defective pixel determination methods according to the defective pixel determination program, for example, the dark read value d _m ( x, y) is compared with a predetermined threshold value d _m th, and when at least one dark reading value d _m (x, y) is larger than the threshold value d _m th (see the above formula (29)), The radiation detection element (x, y) is determined as a defective pixel and registered in a defective pixel map stored in the storage unit.

For example, when the console 31 performs the defective pixel determination described in [Determination Method 6] among the above-described defective pixel determination methods according to the defective pixel determination program, the dark read value d transmitted from the radiation image detector 1 is used. _m (x, y) based on the advance to one of the radiation detecting element (x, y) dark read values output from the _d m (x, y) and the like and, the one of the radiation detecting element (x, y) Absolute value | e _m (x, y) of difference e _m (x, y) from spatial average value w _m (x, y) of each dark reading value output from a plurality of associated radiation detection elements | Is calculated and compared with a predetermined threshold value e _m th, and when the absolute value | e _m (x, y) | of the difference is larger than the threshold value e _m th (see the above formula (37)). The radiation detection element (x, y) is determined as a defective pixel, and the memory Registered in the defective pixel map stored in.

  In the above example, the case where [determination method 3] or [determination method 6] is performed has been described. However, other [determination method 1], [determination method 2], and [determination method 4] in addition to the defective pixel determination method. The same applies to the case where the [determination method 5] is performed, and the same applies to the case where the determination method combining them is performed.

  Further, as described above, in the abnormal pixel determination method of [Determination method 7] to [Determination method 11], the dark read value D (x) output from the radiation detection element (x, y) of the radiation image detector 1 is also used. , Y) and the real image data F (x, y) are extremely abnormal values or frequently output abnormal values, the defective pixel map is regarded as a defective pixel and stored in the storage means. Registered in

  Accordingly, the defective pixel map includes 1 before or after the radiographic image capturing for each time, as well as the steady defective pixels detected at the time of the manufacturing inspection of the radiation image detector 1 and the periodic calibration. The dark reading value D (x, y) obtained by the dark reading performed more than once, the actual image data F (x, y) obtained by actual radiographic imaging, or the state where there is no subject. Pixels that are regarded as defective pixels based on real image data F (x, y) acquired by radiographic imaging are included, and are constantly updated.

  In addition, the console 31 reads a thinning data display program, an abnormal pixel determination program, and the like from the storage unit, and performs processing in parallel at the time of normal radiographic image capturing.

The radiation image generation program is a program for generating final image data F _O (x, y) and the like, and as shown in FIG. 28, a defective pixel determination step (step S1) and a real image data acquisition step (Step S2), dark reading step (step S3), thinning data creation step (step S4), temperature compensation variable calculation step (steps S5 and S9), temporal average value calculation step (steps S6 and S10), offset It comprises a correction value calculation step (steps S7 and S11), a thinned image display step (step S8), an image correction step (step S12), and the like. The console 31 reads out the radiological image generation program, develops it in the work area of the RAM, executes necessary processes according to the radiological image generation program, and controls each part of the apparatus.

  In the defective pixel determination step (step S1), as described above, defective pixel determination is performed based on the defective pixel determination program, and the radiation detection element (x, y) determined as the defective pixel corresponds to the radiation image detector 1. Attached and stored in the defective pixel map. Therefore, it can be said that the defective pixel determination step (step S1) is a step performed as preparation work for the current radiographic image capturing, rather than being performed during the current radiographic image capturing.

  When the console 31 receives a radiographic image capturing instruction from a radiographer, doctor, or the like, the actual image data acquisition step is performed by driving the radiation generating device 34 that controls the imaging conditions (tube current, tube voltage, etc.) and the start of irradiation. (Step S <b> 2) is executed to acquire the actual image data F (x, y) from each radiation detection element (x, y). In addition, before or after radiographic imaging, an instruction signal is transmitted to the radiographic image detector 1 so as to perform at least one dark reading, and a dark reading step (step S3) is executed to execute each radiation detecting element (x , Y) to obtain the dark reading value D (x, y). In addition, a thinning data creation step (step S4) is executed to create thinning data f (x, y) from the actual image data F (x, y) as described above.

  Note that the dark reading may be performed only once before or after the radiographic image capturing, or may be configured to be performed twice or more. When dark reading is performed before radiographic image capturing, the order of the captured image data acquisition step (step S2) and the dark reading step (step S3) is reversed.

  The thinning data creation step (step S4) is performed at an appropriate timing after the captured image data acquisition step (step S2). Further, the actual image data F (x, y) is transmitted from the radiation image detector 1 to the console 31, and the thinned data f (x, y) is created by executing the thinned data creating step (step S4) on the console 31. It is also possible to configure as described above.

  In the present embodiment, when the radiation image detector 1 finishes the thinning data creation step (step S4), the radiographic image detector 1 obtains its own ID, the dark reading value D (x, y), and the thinning data f (x, y). It transmits to the console 31 by a wired system or a wireless system. When the dark read value D (x, y) and the thinned data f (x, y) are transmitted from the radiation image detector 1, the console 31 stores them in the storage means.

  At this stage, a thumbnail image (an image having a size of 1/15 with respect to the original image size) based on the transmitted thinned data f (x, y) may be displayed. In this case, offset / gain correction and abnormal / defective pixel correction have not yet been performed, but since the image is sufficient for confirmation of positioning, it is possible to determine the necessity of re-shooting earliest.

  Subsequently, the console 31 executes a temperature compensation variable calculation step (step S5). The console 31 refers to the ID of the radiation image detector 1, reads out information of a plurality of radiation detection elements (x ′, y ′) associated with each radiation detection element (x, y ′) from the storage means, and outputs from the information Using each of the dark read values D (x ′, y ′) thus obtained, a temperature compensation variable W (x, y) is calculated for each radiation detection element (x, y) according to the above equation (3).

  At this time, the console 31 calculates the temperature compensation variable W (x, y) only for the radiation detection element (x, y) that has output the thinned data f (x, y) at this stage. Further, in calculating the temperature compensation variable W (x, y) for one radiation detection element (x, y), there is a defect among other radiation detection elements that are associated in advance with the one radiation detection element (x, y). When a pixel is included, the dark reading value D (xs, ys) output from the defective pixel using any one of [Calculation method 1] to [Calculation method 4] described above is detected in the vicinity of the radiation. The temperature compensation variable W (x, y) of the one radiation detection element (x, y) is calculated by replacing or interpolating with the dark reading value output from the element.

In addition, the console 31 executes a temporal average value calculation step (step S6) based on data obtained in advance at the time of previous calibration or the like. In this embodiment, the console 31 performs the calculation for the radiation image detector 1. The temporal average value δ (x, y) and the temporal average value ω (x, y) of the spatial average value w _m (x, y) as the temperature compensation variable are previously stored in the server means 39 as described above. It is calculated in advance and stored in the storage means 38. The console 31 may be configured to calculate these values by itself at this stage.

Subsequently, the console 31 executes an offset correction value calculation step (step S7). At that time, the console 31 sends information about the ID of the radiation image detector 1 and the pixel number (x, y) of the radiation detection element (x, y) that has output the thinned data f (x, y) via the network NW. To the server means 39. The server means 39 outputs a temporal average value δ (x, y) of the radiation detection element (x, y) that outputs the thinned data f (x, y) and a spatial average value w _m (x, y) as a temperature compensation variable. The temporal average value ω (x, y) of y) is read from the storage means 38 and transmitted to the console 31.

The console 31 calculates the temporal average value δ (x, y) of the dark read value d _m (x, y) obtained from the server means 39 for the radiation detection element (x, y) that has output the thinned data f (x, y). y) and the temporal average value ω (x, y) of the spatial average value w _m (x ′, y ′) as the temperature compensation variable, and their difference ε (x, y) (= δ (x , Y) −ω (x, y)). The calculated ε (x, y) and each temperature compensation variable W (x, y) for each radiation detection element (x, y) of the radiation image detector 1 calculated in the temperature compensation variable calculation step (step S5). y) is added to calculate an offset correction value O (x, y) for the radiation detection element (x, y) that has output the thinned data f (x, y).

In addition, the console 31 reads the gain correction value G (x, y) of the radiation detection element (x, y) from the storage unit, performs the gain correction process and the offset correction process according to the above equation (1), and performs the thinning data f. The processing for (x, y) is performed, and the processed image data f _O (x, y) is calculated. In this process, F _O (x, y) and F (x, y) in the above equation (1) are read as f _O (x, y) and f (x, y), respectively.

Subsequently, the console 31 executes a thinned image display step (step S8), and, as described above, the corrected image data f _O (x, y) calculated from the thinned data f (x, y). The thinned image based is displayed on the display screen of the display unit 31a. At this time, a thumbnail image (a thinned image reduced to 1/15 of the original image) is displayed on the display screen of the display unit 31a. If necessary, the thumbnail image (thinned-out image) may be displayed after being subjected to image processing such as gradation processing or frequency enhancement processing according to the captured part.

In the image displayed at this stage, correction processing for abnormal / defective pixels has not been executed yet, but offset / gain correction (including gradation processing in some cases) is performed. Whether or not the value is within the appropriate output range can be visually confirmed. Even at this stage, it is possible to determine the necessity of re-shooting in terms of image quality (in the output range of each pixel).

  Note that the image data displayed at this stage is thinned data, but in order to improve the visibility of the output range of each pixel, the thinned data is enlarged and interpolated to the same size as the original image data. Although it may be displayed, in this case, since the interpolation is based on the thinned data, it is inevitable that the resolution is lowered (see FIG. 13B).

  At this stage, a radiologist, a doctor, or the like checks the thinned image displayed on the display screen of the display unit 31a of the console 31, and determines whether or not the photographing position of the subject in the radiation image is an appropriate position. Judgment is made to determine whether or not re-shooting is necessary. If it is determined that re-photographing is necessary, the processing after the actual image data acquisition step (step S2) is repeated again.

In addition, when a radiographer, a doctor, or the like checks the thinned image displayed on the display screen of the display unit 31a of the console 31 and determines that re-imaging is not necessary, the final diagnostic image is displayed on the console 31. An instruction is issued to continue the process in order to obtain the data F _O (x, y).

  When the console 31 receives an instruction to continue from a radiographer or the like, the console 31 does not subsequently obtain the actual image data F (x, y) of all the radiation detection elements (x, y) from the radiation image detector 1. A transmission request signal is transmitted to the radiation image detector 1 to transmit the actual image data F (x, y).

  Then, the console 31 executes a temperature compensation variable calculation step (step S9), and sets a plurality of radiation detection elements (x ′, y ′) corresponding to the radiation detection elements (x, y) already read from the storage means. Based on the information, using each dark reading value D (x ′, y ′) output from them, the temperature compensation variable W (x, y) for each radiation detection element (x, y) according to the above equation (3). y) is calculated. Also in this case, processing such as replacement and interpolation is appropriately performed using the methods of [Calculation Method 1] to [Calculation Method 4] described above.

  The processes from the temperature compensation variable calculation step (step S9) to the offset correction value calculation step (step S11) have already been performed for the radiation detection element (x, y) corresponding to the thinned data f (x, y). Therefore, there is no need to do it again.

  Subsequently, the console 31 executes a temporal average value calculation step (step S10), and performs temporal processing on each radiation detection element (x, y) of the radiation image detector 1 from the storage unit 38 of the server unit 39. The average value δ (x, y) and the temperature compensation variable ω (x, y) are obtained, the offset correction value calculation step (step S11) is executed, and each radiation detection element (x, y) is performed in the same procedure as described above. ) Is calculated for offset correction value O (x, y).

Then, the console 31 reads the gain correction value G (x, y) of each radiation detection element (x, y) from the storage means, performs gain correction processing and offset correction processing according to the above equation (1), and performs each actual image. Processing is performed on the data F (x, y), and the processed image data F _O (x, y) is calculated.

  In the present embodiment, the console 31 subsequently executes an image correction step (step S12).

In the image correction step (step S12), the above-described defective pixel determination and abnormal pixel determination are performed, and the actual image data F (x, y) output from the radiation detection element (x, y) determined to be a defective pixel or an abnormal pixel. Image correction such as replacement or interpolation is performed on the image data F _O (x, y) based on y).

Specifically, the console 31 has, for example, a defect in the radiation detection element (x, y) of the radiation image detector 1 according to the stationary defect pixel or the above-described [determination method 1] to [determination method 6]. When there is a pixel determined to be a pixel, image data based on the actual image data F (x, y) output from the radiation detection element (xs, ys) corresponding to the defective pixel registered in the defective pixel map Image correction such as replacement and interpolation is performed on F _O (x, y).

  Moreover, the console 31 is based on the dark reading value D (x, y) output from the radiation detection element (x, y) of the radiation image detector 1, for example, and the above-mentioned [determination method 7] and [determination method 8]. ], The pixel determined to be an abnormal pixel exists, or based on the actual image data F (x, y) output from the radiation detection element (x, y) of the radiation image detector 1 described above [ If there is a pixel determined to be an abnormal pixel according to the determination method 9] or [determination method 10], information on these radiation detection elements (x, y) is temporarily stored in the storage means. At the same time, it is assumed that the defective pixel is equivalent, and image correction is performed by performing replacement processing or interpolation processing using surrounding pixel values as in the case of the defective pixel.

  At this time, the dark read value D (x, y) and the actual image data F (x, y) output from the radiation detection element (x, y) are extremely abnormal values or frequently abnormal values are present. When output, the radiation detection element (x, y) is regarded as a defective pixel and is registered in a defective pixel map stored in the storage means.

  After performing the above offset correction processing, gain correction processing, defective pixel correction processing, and abnormal pixel correction processing, image processing such as gradation processing, frequency enhancement processing, and grain suppression processing according to the imaging region is performed, and the final processing is performed. Generate a diagnostic image.

  As described above, according to the radiation image generation system 30 according to the present invention, the console 31 displays the thinned data or the thinned data that has been subjected to the offset / gain processing without performing the correction processing for the defective or abnormal pixels. Therefore, a thinned image for confirming the necessity of re-photographing can be displayed quickly, and the engineer can quickly determine the necessity of re-photographing.

  Therefore, it is possible to immediately determine whether or not re-imaging is necessary by confirming the thinning data displayed by the radiologist, etc., and the patient does not have to wait for a long time to judge whether or not re-imaging is necessary. , The burden on the patient is reduced.

In addition, an offset correction value O (x, y) for correcting the actual image data F (x, y) of the radiation detection element (x, y) is output from the radiation detection element (x, y). The read value D (x, y) and the dark read value D (x ′, y) output from a plurality of radiation detection elements (x ′, y ′) previously associated with the radiation detection element (x, y). ′), The dark correction value D (x, y) is sufficiently accurate even when dark reading is performed about once before or after radiographic imaging. O (x, y) can be obtained, the characteristic variation for each pixel (radiation detection element) is corrected, and final diagnostic image data F _O (x, y) having a good SN ratio is generated. Is possible.

Furthermore, by using the above-described abnormal pixel determination method and defective pixel determination method, the final image data F _O (x, y) can be accurately excluded from the influence of abnormal pixels and defective pixels, and a good final result can be obtained. Image data F _O (x, y) can be generated.

When the final image data F _O (x, y) is calculated after the offset correction process and the gain correction process are completed, generally logarithmic conversion to the final image data F _O (x, y) is performed. Processing is applied and converted to linear data with respect to the logarithm of the radiation intensity. When the representative of the final image data after the logarithmic conversion _{LOG (F O (x, y} )) _{and, LOG (F O (x,} y)) various image processing is applied to.

Therefore, final image data F _{O (x,} y) as part value is smaller signal value of the signal value is greatly amplified by the logarithmic conversion, the final image data F _{O (x,} y) of the signal values of As the value is larger, the signal value is compressed by logarithmic transformation. Accordingly, the various threshold values determined in [Determination Method 1] to [Determination Method 11] can be determined in consideration of how the signal value is finally amplified or compressed by the logarithmic conversion process. preferable. Further, various threshold values can be changed according to the dark read value, the actual image data, the value of the final image data F _O (x, y), and the like, and are set as appropriate.

  In this embodiment, the method is described as being particularly effective when the dark reading is performed once before or after the radiographic image capturing. However, the same effect can be obtained even when the dark reading is performed twice or more. be able to. In other words, if the number of dark readings performed at the time of calibration is M times and the number of dark readings performed before or after radiographic imaging is K times, if the relationship of M> K is established, the present invention has been described. Needless to say, similar effects can be obtained.

That is, when K> 2, the dark reading value is set as Dk (x, y) (k = 1 to K, K> 2),
May be applied to D (x, y) in the embodiment of the present invention. That is,
D (x, y) = Dk _ave (x, y) (56)
Think of it as

Further, even when there is a defective pixel in the radiation detection element (x, y) of the radiation image detector 1, output from the defective pixel by using the above-described spatial statistical value (spatial average value) calculation method. The obtained dark reading value D is appropriately replaced or interpolated to obtain temperature compensation variables W (x, y) and w _m (x ′, y ′) which are effective spatial statistics (spatial average values). It is possible to calculate. Thereby, the offset correction value O (x, y) can be accurately calculated.

  Needless to say, the present invention is not limited to the above-described embodiment, and can be changed as appropriate. The concept of the present invention is to select in advance a radiation detection element (x ′, y ′) that varies in temperature in the same manner as one radiation detection element and associate it with the one radiation detection element (x, y) in advance. . Therefore, the radiation detection element itself does not need to be a radiation detection element type as in the above-described embodiment, and is also applied to a radiation image detector including a sensor panel unit in which elements having other structures are two-dimensionally arranged. It goes without saying that it is possible.

  Further, in the present invention, the temperature variation in the pixel unit of the radiation detection element has been described, but even if it is a factor other than the temperature variation, a certain pixel value causes a similar change to a neighboring pixel value. Needless to say, the same effect can be obtained by applying the same method if the fluctuation is small.

Further, in the present embodiment, the case where the data processing is performed by the console 31 has been described. However, the offset image O (x, y) is subtracted for each pixel from the actual image data F (x, y), and the actual image is obtained. The radiation image detector 1 may be configured to perform all data processing from the correction of the data F (x, y) to the generation of the final image data F _O (x, y).

  Further, for example, in the above embodiment, the dark reading is performed at the time of calibration performed separately from the radiographic image capturing. However, the dark reading value to be performed before or after the radiographic image capturing is stored and stored. You may comprise so that it may be used. In this case, for example, the dark reading values for a plurality of consecutive radiographic image captures are stored by normalization and the like, and the plurality of dark reading values are used as in the above embodiment. Alternatively, a temporal statistical value (temporal average value) δ (x, y) or ω (x, y) may be calculated.

  Further, in this embodiment, the offset correction is taken as an example, and the description has been made. However, even when the gain correction value G (x, y) is obtained, the radiation image detector is subjected to uniform radiation under predetermined conditions. The offset correction is also applied to this read value (corresponding to the actual image data F (x, y) in this embodiment). For this reason, in the present embodiment, the case where offset correction is performed on the real image data F (x, y) has been described as an example. However, when the gain correction value O (x, y) is obtained for the above-described reason. Needless to say, the same treatment can be performed and the same effect can be obtained.

It is a figure which shows the external appearance structure of the radiographic image detector which concerns on this embodiment. It is an equivalent circuit diagram shown in the structure of the sensor panel part and reading part of a radiographic image detector. It is a figure explaining the number allocated to the radiation detection element. It is a figure explaining the dark reading value output from a radiation detection element for every multiple times of dark reading. It is a graph explaining distribution of temporal fluctuation of a plurality of dark reading values outputted from a radiation detection element by a plurality of dark readings. It is a figure which shows an example of how to take the some radiation detection element matched with a radiation detection element. It is a graph explaining that the average value and the standard deviation differ in the distribution of temporal fluctuation of the dark reading value when the radiation detection elements are different. It is a graph explaining that it becomes distribution with a small standard deviation of distribution of spatial average value W (x, y). It is a graph which shows the distribution of the temperature compensation variable which becomes broad when the shift degree by the temperature change of the temporal fluctuation distribution of D (x, y) and the temporal fluctuation distribution of D (x ', y') is different. It is a graph explaining that it is difficult to estimate the true value of the offset correction value from the radiation detection element in one dark reading. It is a figure explaining the dark reading value and spatial average value which are output from a radiation detection element for every multiple times of dark reading. It is a graph explaining that the dark reading value and spatial average value output for every multiple times of dark reading are distributed in a normal distribution. It is a graph explaining that the temperature of a radiation detection element fluctuates temporally. It is a graph explaining the distribution of the temporal fluctuation estimated about the dark reading value output from a radiation detection element and the spatial average value by one dark reading performed before or after radiographic imaging. If temperature fluctuation occurs during a plurality of times of dark reading, the distribution of dark reading values and the like becomes broad, but the distribution of temperature-corrected dark reading values does not become broad. (A)-(C) are figures which show the example of the area | region set so that one radiation detection element may be located in the position which is not the center of a square area | region. It is a figure explaining the read-out IC connected one for every predetermined number of radiation detection elements. It is a figure explaining the case where the electrical signal from each radiation detection element which belongs to a field is read by two adjacent read-out ICs separately. (A) and (B), when a plurality of radiation detection elements are selected in a normal manner, (C) and (D) treat the vicinity of the boundary of adjacent readout ICs in the same manner as the peripheral part of the sensor panel unit. It is a figure explaining a case. It is a graph showing the average distribution and the distribution which is much larger than the standard distribution of the fluctuation distribution of the dark reading value from the radiation detection element. It is a graph showing the case where the average value of the fluctuation distribution of the dark reading value from a radiation detection element is larger than a threshold value. It is a graph in which the standard deviation of the difference fluctuation distribution represents an average distribution. 23 is a graph showing a distribution in which the standard deviation of the fluctuation distribution of the difference is larger than that shown in FIG. It is a figure explaining an example in case a pixel of interest is a radiation detection element (4, 4) and a radiation detection element (6, 6) is a defective pixel among 7 × 7 radiation detection elements associated therewith. . It is a figure which shows the example which substitutes a defective pixel with the radiation detection element which exists in the position outside an area | region in the example of FIG. FIG. 25 is a diagram illustrating an example in which defective pixels are interpolated by radiation detecting elements existing at positions outside the region when the radiation detecting elements (7, 6) are defective pixels in the example of FIG. (A) It is a photograph which shows the example of real image data, (B) It is a photograph which shows the example of the thinning-out data produced based on the implementation image data of (A). It is a flowchart which shows the process sequence of the image generation using a radiographic image detector. It is a figure which shows the structure of the radiographic image generation system containing the defect image determination system which concerns on this embodiment.

Explanation of symbols

1 Radiation image detector 3 Antenna device (communication means)
4, 5, 6 Sensor panel section, reading section and control means (image data acquisition means)
6 Control means (offset correction value generation means)
13 terminals (communication means)
14, (x, y) radiation detection element 21 battery 30 radiation image generation system 31 console (offset correction value generation means)
31a Display unit 34 Radiation generator 38 Storage means A (x, y) Spatial average value D (x, y) of actual image data Dark read value E (x, y) difference, first difference Eth threshold value F (x, y) y) Actual image data f (x, y) Thinned-out data O (x, y) Offset correction value V (x, y) Difference Vth threshold value V'th threshold value W (x, y) Spatial average value (xs, ys) Defective pixel δ (x, y) Temporal average value of dark read value ε (x, y) Second difference | Λ (x, y) | Absolute value Λth threshold ω () of the difference between the first difference and the second difference x, y) Temporal average of the spatial average of the dark readings

Claims (14)

A plurality of radiation detection elements arranged two-dimensionally;
In radiographic imaging, real image data is acquired from the plurality of radiation detection elements, and in dark reading performed in a state where radiation is not irradiated, signal value acquisition means for acquiring dark reading values from the plurality of radiation detection elements;
Control means capable of creating thinned-out data based on the photographed image data;
Communication means capable of transmitting the actual image data, the dark reading value, and the thinned data;
A radiation image detector comprising:
An image processing unit that performs image processing on the actual image data and the thinned data transmitted from the radiation image detector;
A display unit that displays the actual image data, the image based on the thinned-out data, or an image after performing image processing on them;
A console having
Based on the dark reading value, an offset correction value in the radiographic image capturing in the radiographic image detector is generated based on the dark reading value output from the radiation detecting element of the radiographic image detector. Offset correction value generation means;
A radiation generator for irradiating the radiation image detector with radiation;
With
The radiation image detector includes the dark reading value in the dark reading performed at least once before or after the radiographic image capturing, the actual image data based on the radiographic image capturing, and the thinned data based on the actual image data. And at least one of the above to the console,
The console includes a gain correction process and the offset for an image based on the thinned data or the thinned data created based on the photographed image data, or on the thinned data or the thinned data created based on the photographed image data. An offset correction process based on a correction value is performed, an image after image processing is applied to the thinned data or the thinned data created based on the actual photographed image data, or a gain correction process and the offset correction value for the actual photographed image data A radiographic image generation system, wherein at least one of images after image processing that has been subjected to offset correction processing based on is displayed on the display unit.   The offset correction value generation means is associated in advance with the one radiation detection element and the dark reading value output from one radiation detection element of the radiation image detector based on the dark reading value. The offset correction value in the said radiographic imaging in the said radiographic image detector is produced | generated based on the spatial average value of the said dark reading value output from the several radiation detection element. The radiation image generation system described.   The radiographic image generation system according to claim 1, wherein the offset correction value generation unit is provided in the console. The console is
Storage means for storing a defective pixel map in which defective pixels in the radiation image detector are registered;
When the actual image data is not transmitted from the radiation image detector, the actual image data is transmitted,
When there is data output from a radiation detection element corresponding to the defective pixel registered in the defective pixel map in the actual captured image data, the gain correction processing and the The processing for correcting the data after the image processing at the position of the data output from the radiation detection element in the image after the offset correction processing based on the offset correction value is performed. The radiation image generation system according to any one of claims 3 to 4. The console is
When the actual image data is not transmitted from the radiation image detector, the actual image data is transmitted,
The actual image data includes data output from a radiation detection element that is determined to be an abnormal pixel that outputs an abnormal dark reading value based on the dark reading value transmitted from the radiation image detector. When performing the image processing of the position of the data output from the radiation detection element in the image after performing the gain correction processing and the offset correction processing based on the offset correction value for the photographed image data The radiographic image generation system according to claim 1, wherein a process for correcting data is performed.   Based on the dark reading value transmitted from the radiation image detector, the console outputs the dark reading value output from the radiation detection element of the radiation image detector and the one radiation detection element. Whether or not the one radiation detection element is an abnormal pixel that outputs an abnormal signal value based on the spatial average value of the dark reading values output from a plurality of radiation detection elements associated in advance. 6. The radiological image generation system according to claim 5, wherein the determination is performed.   Based on the dark reading value transmitted from the radiation image detector, the console outputs the dark reading value output from the radiation detection element of the radiation image detector and the one radiation detection element. If the absolute value of the difference from the spatial average value of the dark reading values output from a plurality of radiation detection elements associated in advance exceeds a preset threshold, the one radiation detection element is abnormal. The radiological image generation system according to claim 6, wherein the radiation image generation system is determined to be an abnormal pixel that outputs a simple signal value. The console is
Based on the dark reading value transmitted from the radiation image detector, the dark reading value output from the radiation detection element of one of the radiation image detectors is associated in advance with the one radiation detection element. Calculating a first difference with a spatial average value of the dark reading values output from the plurality of radiation detecting elements;
A temporal average value of the dark reading values output from the one radiation detection element in the dark reading performed a plurality of times during past calibrations, and a plurality of radiations previously associated with the one radiation detection element Calculating a second difference between a spatial average value of the dark reading value output from the detection element and a temporal average value;
When the absolute value of the difference between the first difference and the second difference exceeds a preset threshold, it is determined that the one radiation detection element is an abnormal pixel that outputs an abnormal signal value. The radiation image generation system according to claim 6.   When the photographed image data is transmitted from the radiation image detector, the console outputs the photographed image data output from the radiation detection element of the radiation image detector based on the photographed image data. And the one radiation detection element outputs an abnormal signal value based on the spatial average value of the actual image data output from the plurality of radiation detection elements previously associated with the one radiation detection element. The radiographic image generation system according to claim 5, wherein it is determined whether or not the pixel is an abnormal pixel.   The console, based on the actual image data, the actual image data output from one of the radiation detection elements of the radiation image detector and a plurality of radiation detections previously associated with the one radiation detection element When the difference from the spatial average value of the actual image data output from the element exceeds a preset threshold value, it is determined that the one radiation detection element is an abnormal pixel that outputs an abnormal signal value. The radiographic image generation system according to claim 9, wherein:   The console, based on the actual image data, the actual image data output from one of the radiation detection elements of the radiation image detector and a plurality of radiation detections previously associated with the one radiation detection element When the absolute value of the difference from the spatial average value of the photographed image data output from the element exceeds a preset threshold, the one radiation detection element is an abnormal pixel that outputs an abnormal signal value. The radiation image generation system according to claim 9, wherein the radiation image generation system is determined to be present.   In the radiographic image capturing performed in a state where no subject exists in advance in the defective pixel registered in the defective pixel map, the actual image data output from the radiation detection element of the radiographic image detector; If the absolute value of the difference from the spatial average value of the photographed image data output from a plurality of radiation detection elements previously associated with the one radiation detection element exceeds a preset threshold, The radiation detection element determined to be an abnormal pixel that outputs actual image data, and includes the radiation detection element determined to be a defective pixel according to the size of the output actual image data. The radiation image generating system according to claim 4.   In the radiographic image capturing performed in a state where no subject exists in advance in the defective pixel registered in the defective pixel map, the actual image data output from the radiation detection element of the radiographic image detector; If the absolute value of the difference from the spatial average value of the photographed image data output from a plurality of radiation detection elements previously associated with the one radiation detection element exceeds a preset threshold, The radiation detection element that has been determined to be an abnormal pixel that outputs real image data, and that the probability of outputting the abnormal real image data exceeds a preset occurrence probability threshold value and is determined to be a defective pixel The radiation image generation system according to claim 4, wherein the radiation detection element is included.   The console includes a gain correction process and the offset for an image based on the thinned data or the thinned data created based on the photographed image data, or on the thinned data or the thinned data created based on the photographed image data. Performing an offset correction process based on a correction value, an image after image processing on the thinned data or the thinned data created based on the actual image data, or an image after image processing of the thinned data is defective or abnormal An image subjected to pixel correction processing, or an image-processed image obtained by performing gain correction processing and offset correction processing based on the offset correction value for the photographed image data, or image processing for the photographed image data The subsequent image is corrected for defects or abnormal pixels. Image, at least one radiation image generating system according to any one of claims 13 claim 4, characterized in that to be displayed on the display unit of the.