CN116458906B - Side bitmap generation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application discloses a side bitmap generation method, a side bitmap generation device, electronic equipment and a storage medium. The side bitmap generation method of the application comprises the following steps: a detector movable to the other side; controlling the fast KVP switching source to rapidly expose twice by using a pulse signal sequence control signal; transmitting a twice-reading pulse signal to the detector based on the pulse signal sequence control signal while exposing; the detector reads the image to generate two X-ray images; the two X-ray images are decomposed into two energy spectrum images; reconstructing two energy spectrum images, and separating contributions of different tissue structures in the two energy spectrum images to obtain corresponding target images; and splicing the images to obtain a side bitmap of the measured object. Based on the rapid KVP switching source technology, X-ray shooting of two different energy intervals can be completed in extremely rapid speed, and more superior conditions are provided for a target tissue energy spectrum segmentation method.
Description
Technical Field
The application relates to a side bitmap generation method, a side bitmap generation device, electronic equipment and a storage medium.
Background
A multi-channel detector based energy spectrum segmentation method is a technique that uses a common source, but uses a detector with multiple channels to collect X-ray radiation in different energy intervals.
Typically, a multi-channel detector is a photon counting detector, consisting of a plurality of detection units, each of which is responsible for receiving and counting X-rays in a specific energy range. The output signal of each channel can be used to create an energy spectrum reflecting the absorption characteristics of the different tissue structures.
However, the implementation process of the multi-channel detector is more complex than that of the conventional single-channel detector, and it involves more electronics, signal processing and data processing technologies, requiring higher technical requirements and manufacturing costs.
The energy spectrum segmentation method based on the two imaging of the source is a common technology, and is used for performing two X-ray shooting at the same position by using high kilovolts and low kilovolts respectively.
However, this method may be affected by motion artifacts in practice, that is, image blurring or distortion is caused by motion introduced by a time interval between two shots, because between two shots, under the condition of applying a spectrum segmentation technique, two shots of a source need to be exposed for a certain time interval, which leads to a prolonged detection movement time, and during the process of shooting a patient, an object or a patient may move with a longer shooting time, which may lead to incomplete alignment of images, a conventional source continuous exposure is not suitable for the spectrum decomposition method, and a defect of a large detector in use is a high cost, so that the spectrum segmentation decomposition method is suitable for a moving detector in practical application.
Disclosure of Invention
The application aims to provide a rapid KVP switching source technology, which can complete X-ray shooting of two different energy intervals in extremely high speed, and the principle of side images and DR (digital radiography) of the X-ray shooting is similar, and the images are generated by accumulating target objects. In the X-ray image, X-rays are absorbed or scattered by tissues of different tissue structures when passing through a human body or an object, so that the superposition effect of the tissue structures is shown in an image.
Because of the penetrability of X-rays, X-ray images cannot provide clear depth information, so that different tissue structures are superimposed together in a certain direction in a side image. This means that in the side images we cannot directly discern the layers and positions of the different tissue structures, but only observe their relative position and density variations in the overall.
In order to better identify and explain the tissue structure in the side image, it is generally necessary to combine other imaging technologies or use further image processing methods to implement a more superior bone tissue energy spectrum segmentation method of the side image, so as to solve the problems set forth in the above-mentioned background art.
In order to achieve the above purpose, the present application provides the following technical solutions:
a side bitmap generation method, comprising:
s102, the detector can move to the other side;
s104, controlling the fast KVP switching source to rapidly expose twice by using a pulse signal sequence control signal;
s106, transmitting a double-image reading pulse signal to the detector based on the pulse signal sequence control signal while exposing, so that the detector reads and records an X-ray signal after each exposure;
s108, the detector reads the images to generate two X-ray images;
s110, decomposing the two X-ray images into two energy spectrum images, wherein,
the fast KVP switching source is used for shooting twice respectively at the same position when in fast exposure, the tube voltage of the source is controlled to be a first kilovolt peak value when shooting for the first time and a second kilovolt peak value when shooting for the second time, wherein the second kilovolt peak value is at least 20KV higher than the first kilovolt peak value, and the fast KVP switching source is capable of controlling the tube voltage of the source to be a first kilovolt peak value when shooting for the second time,
V 1 =k 1 A 1 +k 2 A 2 +k 3 A 1 A 2 +k 4 A 1 2 +k 5 A 2 2
V 2 =k 6 A 1 +k 7 A 2 +k 8 A 1 A 2 +k 9 A 1 2 +k 10 A 2 2
fitting and representing gray values of pixel points on two X-ray images before decomposition, wherein V 1 And V 2 Expressed as gray values of pixel points on the image before decomposition, A 1 And A 2 Expressed as gray values of decomposed pixel points, k in the system of equations 1 ，k 2 ，k 3 ，k 4 ，k 5 ，k 6 ，k 7 ，k 8 ，k 9 ，k 10 Is a known energy spectrum characteristic parameter;
s112, reconstructing the two energy spectrum images, and separating contributions of different tissue structures in the two energy spectrum images according to the absorption characteristics of the different tissue structures of the human body to the X-rays with different energies so as to obtain corresponding target images;
s114, repeating the operations of S104-S112 in the process of uniform movement of the detector;
s116, independently splicing the two X-ray images generated by the detector image reading, the two decomposed energy spectrum images and the reconstructed target image respectively to obtain a side bitmap of the measured object.
In some possible implementations of the first aspect of the present application, a side bitmap of a measured object includes:
in step S108, the detector reads the image to generate two side bitmaps formed by respectively splicing two X-ray images;
step S110, two side bitmaps are respectively spliced by the two decomposed energy spectrograms;
and (3) two side bitmaps are respectively spliced by the target images after the two energy spectrum images are reconstructed in the step (S112).
In some possible implementations of the first aspect of the present application, the detector receives X-ray radiation generated by two exposures and converts it into an electrical signal, and the detector generates two X-ray images by reading and recording the electrical signal, each image corresponding to the result of one exposure.
In some possible implementations of the first aspect of the present application, the system of equations is solved according to newton's iterative method, and the successive approximation of the unknown a is calculated according to iteration 1 And A 2 And (3) obtaining the gray value of the decomposed pixel point.
In some possible implementations of the first aspect of the present application, a is set up 1 And A 2 In each iteration, according to the current A 1 And A 2 The values are brought into the equation set, the difference value between the left side and the right side of the equation set is calculated, and the difference value approaches through continuous iterationAt 0, a solution to the system of equations is obtained.
In some possible implementations of the first aspect of the present application, the spectral feature parameter is expressed as a k coefficient, k 1 ，k 2 ，k 3 ，k 4 ，k 5 Is the energy spectrum characteristic parameter, k of the second kilovolt peak value 6 ，k 7 ，k 8 ，k 9 ，k 10 Is the energy spectrum characteristic parameter of the first kilovolt peak value.
In some possible implementations of the first aspect of the present application, the k coefficient verification method includes:
selecting two reference substances as calibration samples of energy spectrum characteristic parameters, and manufacturing a plurality of die bodies, wherein each die body is formed by mixing two reference substances with different ratio thicknesses;
exposing and shooting each die body by using a first kilovolt peak value and a second kilovolt peak value to obtain corresponding V 1 And V 2 And a is known as 1 And A 2 Is a measurement of (2);
solving parameters using least squares method, to measure V 1 And V 2 And a is known as 1 And A 2 Substituting the difference value into an energy spectrum decomposition equation set to obtain a difference value between the left side and the right side of the equation set;
using least square method to solve k by minimizing the sum of squares of the difference values 1 ，k 2 ，k 3 ，k 4 ，k 5 ，k 6 ，k 7 ，k 8 ，k 9 ，k 10 Is a numerical value of (2).
In some possible implementations of the first aspect of the present application, a substance image with a similar atomic number of a human tissue is taken and applied to reconstruction of the two energy spectrum images, the human tissue including bone tissue and soft tissue;
according to the first decomposition parameter obtained by energy spectrum decomposition by the side bitmap generation method, an absorption coefficient is obtained, and the absorption characteristic of the substance is represented;
shooting a target tissue image;
performing energy spectrum decomposition according to the side bitmap generation method to obtain target tissue decomposition parameters;
and weighting and calculating the target tissue decomposition parameters according to the orthogonal coefficients of the absorption coefficients to obtain a reconstructed image.
In some possible implementations of the first aspect of the present application, the method for generating a side bitmap is used for performing energy spectrum decomposition, an image of a substance having an atomic number close to that of bone tissue is selected to be captured, and the image is applied to a system of energy spectrum decomposition equations to obtain a first decomposition parameter C 1 And C 2 First decomposition parameter C 1 And C 2 Dividing by the thickness of the mould body to obtain the absorption coefficient c 1 And c 2 ；
Shooting a target tissue image, which is represented as an image A;
performing energy spectrum decomposition according to the side bitmap generation method to perform energy spectrum decomposition on the image A to obtain a target tissue decomposition parameter A 1 And A 2 ；
Use and c 1 And c 2 Orthogonal coefficient pair A 1 And A 2 Weighting and calculating;
a new image a' =a is calculated by the following formula 1 c 2 -A 2 c 1 The obtained image a' is an image not including bone tissue.
In some possible implementations of the first aspect of the present application, the side bitmap generating method is used to perform energy spectrum decomposition, an image of a substance close to an atomic number of soft tissue is selected to be captured, and the image is applied to a system of energy spectrum decomposition equations to obtain a first decomposition parameter C 1 And C 2 First decomposition parameter C 1 And C 2 Dividing by the thickness of the mould body to obtain the absorption coefficient c 1 And c 2 ；
Shooting a target tissue image, which is represented as an image A;
performing energy spectrum decomposition according to the side bitmap generation method to perform energy spectrum decomposition on the image A to obtain a target tissue decomposition parameter A 1 And A 2 ；
Use and c 1 And c 2 Orthogonal coefficient pair A 1 And A 2 Weighting and calculating;
the new image a "=a is calculated by the following formula 1 c 2 -A 2 c 1 The obtained image A '' is an image which does not contain soft tissues.
According to a second aspect of the present application, a side bitmap generation apparatus includes:
the fast KVP switching unit is connected with the source and is used for fast switching the output voltage of the high-voltage power supply when receiving the control signal so as to realize fast KVP switching; a measured image acquisition unit for acquiring an image from a measured object; the measured image processing unit is used for processing the obtained image from the measured object to obtain a decomposed energy spectrum image; an image reconstruction unit for reconstructing the spectrogram image to obtain a target image; and the side bitmap acquisition unit is used for utilizing the target image to splice and acquire a side bitmap of the measured object.
According to a third aspect of the application, an electronic device comprises: a memory storing execution instructions; and a processor that executes the execution instructions stored in the memory, so that the processor executes the above-described side bitmap generation method.
According to a fourth aspect of the present application, a readable storage medium having stored therein an execution instruction that is executed by a processor to perform the above-described side bitmap generation method.
Compared with the prior art, the application has the beneficial effects that:
the mode of fast KVP switching really solves the problem that the position deviation is overlarge when the small-area detector shoots the side images, the deviation possibly affects the accuracy of energy spectrum segmentation, and through the fast KVP switching source technology, X-ray shooting of different energy intervals can be fast switched in extremely short time, so that a plurality of images with different energy characteristics are obtained, and therefore, even if the area of the detector is small, enough data can be obtained to carry out energy spectrum segmentation, and the problem of overlarge deviation is avoided.
In addition, this technology solves the problem of expensive large detectors, which traditionally have been expensive due to their large size and complex manufacturing process, and after the fast KVP switching source technology is adopted, only the small area detector needs to be moved, and expensive large detector equipment is not needed, which reduces the cost and makes the technology more economical and practical.
Therefore, by means of fast KVP switching, the problem of deviation when the small-area detector shoots the side images is solved, the limit of high price of the large detector is overcome, a more practical and cost-effective solution is provided for the application of the energy spectrum segmentation technology, and the accuracy and the reliability of medical imaging are improved.
Drawings
Fig. 1 is a schematic flow chart of a side bitmap generation method in the present application.
FIG. 2 is a block diagram of a schematic of some embodiments of a side bitmap generation apparatus employing a hardware implementation of a processing system.
FIG. 3 is a graph showing the energy distribution of X-ray photons generated by a 100kV electron beam tungsten target in the application.
Detailed Description
The present application will be described in further detail with reference to the drawings and embodiments. It is to be understood that the specific embodiments described herein are merely illustrative of the substances, and not restrictive of the application. It should be further noted that, for convenience of description, only the portions related to the present application are shown in the drawings.
In addition, the embodiments of the present application and the features of the embodiments may be combined with each other without collision. The technical scheme of the present application will be described in detail below with reference to the accompanying drawings in combination with embodiments.
Unless otherwise indicated, the exemplary implementations/embodiments shown are to be understood as providing exemplary features of various details of some of the ways in which the technical concepts of the present application may be practiced. Thus, unless otherwise indicated, the features of the various implementations/embodiments may be additionally combined, separated, interchanged, and/or rearranged without departing from the technical concepts of the present application.
The use of cross-hatching and/or shading in the drawings is typically used to clarify the boundaries between adjacent components. As such, the presence or absence of cross-hatching or shading does not convey or represent any preference or requirement for a particular material, material property, dimension, proportion, commonality between illustrated components, and/or any other characteristic, attribute, property, etc. of a component, unless indicated. In addition, in the drawings, the size and relative sizes of elements may be exaggerated for clarity and/or descriptive purposes. While the exemplary embodiments may be variously implemented, the specific process sequences may be performed in a different order than that described. For example, two consecutively described processes may be performed substantially simultaneously or in reverse order from that described. Moreover, like reference numerals designate like parts.
When an element is referred to as being "on" or "over", "connected to" or "coupled to" another element, it can be directly on, connected or coupled to the other element or intervening elements may be present. However, when an element is referred to as being "directly on," "directly connected to," or "directly coupled to" another element, there are no intervening elements present. For this reason, the term "connected" may refer to physical connections, electrical connections, and the like, with or without intermediate components.
The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, when the terms "comprises" and/or "comprising," and variations thereof, are used in the present specification, the presence of stated features, integers, steps, operations, elements, components, and/or groups thereof is described, but the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof is not precluded. It is also noted that, as used herein, the terms "substantially," "about," and other similar terms are used as approximation terms and not as degree terms, and as such, are used to explain the inherent deviations of measured, calculated, and/or provided values that would be recognized by one of ordinary skill in the art.
The following describes embodiments of the present application in detail with reference to fig. 1 to 3.
Fig. 1 shows a flow diagram of a side bitmap generation method of some embodiments of the present application. The side bitmap generation method of the embodiment of the application comprises the following steps S102-S116.
Step S102, the detector is able to move to the other side.
After one side of the source is ready, the narrowband detector begins to move to the other side. A narrowband detector is a device for receiving a signal in a specific frequency range, which will continue to receive a signal when the narrowband detector is activated and starts moving to the other side.
S104, controlling the fast KVP switching source to rapidly expose twice by using the pulse signal sequence control signal.
The interval time of the fast KVP switching source is at least within 100ms, if the interval time exceeds 100ms, the influence on the movement of a patient in the shooting process can be caused, and the movement artifact is generated, the larger the area of the detector is, the more expensive the cost is, the more the small-area detector is moved for imaging, and the splicing is an economic and effective method.
The source is positioned at the same location of the object to be photographed and is ready to be photographed twice.
At the first shot, the tube voltage of the source is set to a first kilovolt peak, which is the high voltage level used by the source in this shot, by controlling it.
At the second shot, the tube voltage of the source is set to the second kilovolt peak by controlling it. The second KV peak is at least 20KV higher than the first KV peak, ensuring that the radiation energy generated by the source in the second shot is significantly higher than in the first shot.
The same position and exposure parameters (e.g., exposure time, number of photons, etc.) are used during the two shots to ensure consistency of contrast and image quality.
Through the tube voltage of the fast switching source, two shooting times are completed in a short time, so that the purpose of fast exposure of the fast KVP switching source is realized.
The method has the advantages that the target can be shot twice in succession at the same position, and the obvious increase of the radiation energy in the second shooting is realized by controlling the tube voltage of the source.
In a specific embodiment, a rapid KVP switching source technology is adopted, and the rapid KVP switching source technology is controlled through a pulse signal sequence, so that 80 kilovolts and 100 kilovolts of rapid exposure are realized in extremely short time, and when exposure is carried out, a target is firstly shot for the first time; by pulse signal sequence control, we set the tube voltage of the source to 80 kv; at this point, the first source unit is activated and generates radiation in a very short time, and then we take a second shot; by the same pulse signal sequence control, we set the tube voltage of the source to 100 kv; at this point, the second source unit is activated and produces radiation in the same very short time; by switching the tube voltage of the source rapidly, we ensure that the difference between the time interval of the second exposure and the first exposure is very small, further reducing the possibility of motion artefacts, by using two different tube voltages of 80 kv and 100kv we can obtain different radiation energy levels in the two exposures.
And S106, transmitting a double-image reading pulse signal to the detector based on the pulse signal sequence control signal while exposing, so that the detector can read and record the X-ray signal after each exposure.
In the exposure process, in order to ensure that the detector can accurately read and record the X-ray signals, the following steps are taken:
after exposure starts, a synchronization mechanism is used for ensuring that a double-time image reading pulse signal is sent to the detector after each exposure;
the first time the image reading pulse signal is sent to the detector at a specific time point after the exposure is started so that the detector is ready to receive and record the X-ray signal;
after the detector receives the first image reading pulse signal, data reading operation is executed according to the triggering of the signal, and the X-ray signal is converted into recordable data;
the exposure process is continued, and X-ray radiation irradiates the target area;
at a specific time point after each exposure is finished, the pulse signal sequence sends a second image reading pulse signal to the detector;
after the detector receives the second image reading pulse signal, the data reading operation is executed again, and the X-ray signal corresponding to the second exposure is recorded;
in this synchronized manner, the detector is able to accurately read and record the X-ray signal after each exposure, ensuring that high quality image data is obtained.
The implementation of the steps can ensure that the time of data reading and X-ray radiation in the exposure process is consistent, so that the X-ray signal of the target area is accurately recorded. The synchronous image reading pulse signal transmitting mechanism is helpful to eliminate time offset and data loss and improve image quality and data accuracy.
S108, the detector reads the images to generate two X-ray images.
In the exposure process, by synchronously sending two image reading pulse signals to the detector and generating corresponding X-ray images, the method is specifically described as follows:
after the exposure is started, the detector receives X-ray radiation generated by the exposure and converts the X-ray radiation into corresponding electric signals;
the detector processes the signal generated by the first exposure by reading and recording the electric signal;
the detector converts the processed signals into image information to generate a first X-ray image, wherein the image corresponds to a first exposure result;
the exposure process is continued, and X-ray radiation irradiates the target area;
after each exposure is finished, the pulse signal sequence sends a second image reading pulse signal to the detector;
the detector processes the signal generated by the second exposure by reading and recording the electric signal;
the detector converts the processed signal into image information, generating a second X-ray image corresponding to the result of the second exposure.
Through the steps, after each exposure, the detector can accurately read and record the X-ray signals and generate corresponding X-ray images, so that the result of each exposure can be captured and recorded, and two X-ray images corresponding to the result of each exposure are generated.
In step S110, the two X-ray images are decomposed into two energy spectrum images.
The method comprises the steps of applying an energy spectrum decomposition algorithm to the two X-ray images, decomposing the two X-ray images into two energy spectrum images based on aluminum and resin, applying the energy spectrum decomposition algorithm to separate and decompose different components in the images for each X-ray image, decomposing signals in the images into components with different energy characteristics by the energy spectrum decomposition algorithm based on the principle of interaction between different energies and substances of X-rays, and applying energy spectrum decomposition to the two X-ray images to obtain two energy spectrum images based on aluminum and resin respectively.
For the same object, the high kilovolts and the low kilovolts are respectively used for exposure shooting at the same angle and position to generate two images, so that energy spectrum decomposition can be performed, and the following equation set is solved:
V 1 =k 1 A 1 +k 2 A 2 +k 3 A 1 A 2 +k 4 A 1 2 +k 5 A 2 2
V 2 =k 6 A 1 +k 7 A 2 +k 8 A 1 A 2 +k 9 A 1 2 +k 10 A 2 2
wherein V is 1 And V 2 The gray value expressed as pixel points on the image before decomposition is a known term, A 1 And A 2 Expressed as gray values of decomposed pixel points, k in the system of equations 1 ，k 2 ，k 3 ，k 4 ，k 5 ，k 6 ，k 7 ，k 8 ，k 9 ，k 10 Is a known energy spectrum characteristic parameter, k 1 ，k 2 ，k 3 ，k 4 ，k 5 Is the energy spectrum characteristic parameter, k of the second kilovolt peak value 6 ，k 7 ，k 8 ，k 9 ，k 10 Is the energy spectrum characteristic parameter of the first kilovolt peak value, thus, the energy spectrum characteristic parameter is a binary quadratic nonlinear equation system, and the unknown A can be solved by Newton iteration method 1 And A 2 For a state stable X-ray imaging system, the spectral feature parameter is fixed, but requires pre-calibration measurements.
Given two X-ray exposure images with different energies, namely high kilovolts and low kilovolts, the gray value of any pixel point on each image is respectively expressed as V 1 And V 2 。
Solving the equation set by Newton iteration method, and gradually approximating the unknown number A by iterative calculation 1 And A 2 Is a solution to (a).
Initially, it can be assumed that A 1 And A 2 For example, set to 0.5, in each iteration, according to the current a 1 And A 2 And the values are brought into the equation set, and the difference value between the left side and the right side of the equation set is calculated. And (5) continuously iterating to enable the difference value to approach 0, and obtaining the solution of the equation set.
For k coefficient calibration, two substances can be generally selected as reference substances, wherein aluminum and resin are selected, and for aluminum with thickness of 1cm, we set the energy spectrum decomposition into A 1 =1，A 2 =0; for a resin thickness of 1cm, we set A 1 =0，A 2 =1; mixing x cm thick aluminum with (1-x) cm thick resin, then A 1 =x，A 2 =1-x, we by mixing aluminum and resin in any ratio thicknessCan construct any A 1 And A 2 Is a combination of (a) and (b).
After two reference substances are selected, a plurality of die bodies mixed in different thickness ratios can be manufactured, and each die body is respectively subjected to exposure shooting by using high kilovolts and low kilovolts to obtain corresponding V 1 And V 2 And a is known as 1 And A 2 At least 5 sets of sample measurements of different proportions are required.
Least squares solution parameters:
to be measured V 1 And V 2 And a is known as 1 And A 2 Substituting the difference value into the energy spectrum decomposition equation set to obtain the difference value between the left side and the right side of the equation set.
Using least square method to solve k by minimizing the sum of squares of the difference values 1 ，k 2 ，k 3 ，k 4 ，k 5 ，k 6 ，k 7 ，k 8 ，k 9 ，k 10 Is a numerical value of (2).
The least squares method can be implemented by a numerical optimization algorithm (e.g., gradient descent) to find k that minimizes the difference 1 ，k 2 ，k 3 ，k 4 ，k 5 ，k 6 ，k 7 ，k 8 ，k 9 ，k 10 Therefore, the calibration of energy spectrum decomposition is realized, and the calibrated energy spectrum characteristic parameters can be applied to an actual energy spectrum decomposition algorithm for carrying out energy spectrum decomposition and imaging analysis on an unknown object.
The above-mentioned energy spectrum decomposition by solving the nonlinear equation set has practical physical significance, the nonlinear polynomial model is derived from the continuous energy spectrum characteristic of the X-ray, and the following two points are used for discussing the reason of fitting the continuous energy spectrum imaging characteristic by using the polynomial:
first, fig. 3 shows the energy distribution, i.e. spectrum, of X-ray photons generated by a 100kV electron beam tungsten target, and it can be seen from fig. 3 that the X-ray emitted by the source is in a continuous energy spectrum and has a certain range.
Second, the detector receives the remaining X-ray energy attenuated by passing through the target object, assuming X-raysIs unipotent (corresponds to only a very narrow inter-cell range in the energy spectrum), the attenuation process can be described by the following formula: i=i 0 e -A Wherein a= ≡ L Mu (l) dl, which is the absorption coefficient of the object at a point in space where the radiation passes. L is the length of the ray passing through the target object, obviously, the detector directly receives I, the difference between different pixels is exponential, the observation and the comparison are inconvenient, and the X-ray image actually seen by the user is subjected to negative logarithm processing, namely: a= -ln (I/I 0 )。
After negative logarithmic processing, the gray value of the pixel is the line integral A of the absorption coefficient, and the difference of A values among different pixels is of a linear level, so that observation and analysis are facilitated, but here we assume that the X-ray is unipotent and inconsistent with the actual situation, and the actual attenuation process can be described by the following formula: i= ≡i 0 S(E)e -A(E) dE. In the formula, S (E) is the proportion of the number of photons with energy E to the total number of photons in the energy spectrum, A (E) = Special L Mu (l' E) dl, if processed according to our normal negative logarithm, the final image gray value represents the physical meaning as follows: ln (I/I) 0 )=-ln(∫S(E)e -A(E) dE)。
Obviously, the simple negative logarithm operation at this time does not fully resolve a (E). The difficulty here is that A (E) is a function of E, not simply a number, if we can decompose A (E) into Σ 1 n A i f i (E) And f is of the form i (E) Is a fixed and imaging target independent basis function, we solve for this function not being A (E) anymore, but the combined coefficients A i The problem is simplified:。
except for a series A in the formula i The parameters, the other terms, are system-inherent and do not change from shot to shot, so we can approximate the function with a higher order polynomial.
Let us take n=2, then-ln (I/I 0 )=k 1 A 1 +k 2 A 2 +k 3 A 1 A 2 +k 4 A 1 2 +k 5 A 2 2 。
Since in the above formula we take n=2, i.e.: a (E) =a 1 f 1 (E)+A 2 f 2 (E)。
In theory, the larger the n value is, the more the decomposed spectral components are, and the influence of energy on the absorption coefficient can be fitted, but according to the actual physical principle, on the premise of medical diagnosis X-ray, the absorption coefficient of a substance mainly has two physical factors of photoelectric absorption and Compton scattering, so that the two spectral components are enough.
The absorption capacity of a substance with atomic number Z in the medical X-ray range is mainly determined by compton scattering and photoelectric absorption, namely: mu (Z' E) =mu Compton (Z'E)+μ PhotoelectrLc (Z'E)。
In particular, compton scattering and photoelectric absorption can each be independently decomposed and the product of an atomic number factor and an X-ray energy factor, so the formula is decomposed into: mu (Z' E) =a 1 (Z)f 1 (E)+a 2 (Z)f 2 (E) A. The application relates to a method for producing a fibre-reinforced plastic composite Here, f 1 (E) And f 2 (E) Are fundamental functions of Compton scattering and photoelectric absorption, which are functions of the X-ray energy E only. The X-ray absorption capacity of the substance with the atomic number Z is the linear superposition of the two, and the superposition coefficient is a 1 (Z) and a 2 (Z) is related only to atomic number. The absorption response of different substances to X-ray energy can be completely used as a 1 And a 2 And (3) representing. Whereas a (E) = ≡in the foregoing L Mu (l ' E) dl, where mu (l ' E) is in fact the absorption coefficient of a substance at that point in space, and mu (Z ' E) here is equivalent, namely: a (E) = ≡ L a 1 (l)f 1 (E)+a 2 (l)f 2 (E)dl。
Let A 1 =∫ L a 1 (l)dl，A 2 =∫ L a 2 (l) dl, from a physical cause point of view, proves that a (E) =a 1 f 1 (E)+A 2 f 2 (E) Is reasonable.
Selection of a basis function:
according to f 1 (E) And f 2 (E) Are the basis functions of Compton scattering and photoelectric absorption, which are the only a priori parameters associated with the imaging system, f for either material 1 (E) And f 2 (E) Is a linear combination of some kind of (c).
If we know the combined result f of substance x and substance y x (E) And f y (E) Then, according to the theory of linear transformation, the substance z is also f x (E) And f y (E) From this it can be seen that the absorption coefficient of any two substances can be used as a basis function.
Step S112, reconstructing the two energy spectrum images, and separating contributions of different tissue structures in the two energy spectrum images according to absorption characteristics of different tissue structures of a human body to X-rays with different energies so as to obtain corresponding target images.
First, a material image is taken of the atomic number of human tissue, including bone tissue and soft tissue, which will be used as input to the spectral decomposition algorithm.
And decomposing the two material images by using an energy spectrum decomposition algorithm to obtain a first decomposition parameter.
According to the energy spectrum decomposition algorithm, the absorption coefficient is obtained by utilizing a first decomposition parameter, the absorption coefficient represents the absorption characteristic of the substance to X-rays, then, a target tissue image is shot, the side bitmap generation method is applied to the target tissue image, and the decomposition parameters of the target tissue are obtained, wherein the parameters describe the distribution condition of each component in the target tissue.
And weighting and calculating the decomposition parameters of the target tissue by utilizing the absorption coefficient acquired before and the decomposition parameters of the target tissue, and weighting the decomposition parameters of the target tissue by utilizing the orthogonal coefficient. This allows reconstruction of the target tissue from the absorption properties.
Finally, by weighting the decomposition parameters of the target tissue to obtain a reconstructed image, we use the prior bone tissue spectral parameters to eliminate bone tissue from the two spectral images to segment out soft tissue or to eliminate soft tissue to segment out bone tissue, as shown in the examples below.
Performing energy spectrum decomposition by using the side bitmap generation method, selecting an image of a substance close to the atomic number of bone tissue, and applying the image to an energy spectrum decomposition equation set to obtain a first decomposition parameter C 1 And C 2 First decomposition parameter C 1 And C 2 Dividing by the thickness of the mould body to obtain the absorption coefficient c 1 And c 2 ；
Shooting a target tissue image, which is represented as an image A;
performing energy spectrum decomposition according to the side bitmap generation method to perform energy spectrum decomposition on the image A to obtain a target tissue decomposition parameter A 1 And A 2 ；
Use and c 1 And c 2 Orthogonal coefficient pair A 1 And A 2 Weighting and calculating;
a new image a' =a is calculated by the following formula 1 c 2 -A 2 c 1 =∫ L1 c 2 a 1 (l)-c 1 a 2 (l)dl+∫ L2 c 1 c 2 -c 2 c 1 dl, where L 2 Is the thickness of bone tissue, L 1 Is to remove other tissue thickness of bone tissue, the second result is zero, because in the ray integral path of bone tissue, c 1 c 2 And c 2 c 1 The images a' obtained in this way are, by way of mutual cancellation, images which do not contain bone tissue.
Performing energy spectrum decomposition by using the side bitmap generation method, selecting an image of a substance close to the atomic number of the soft tissue, and applying the image to an energy spectrum decomposition equation set to obtain a first decomposition parameter C 1 And C 2 First decomposition parameter C 1 And C 2 Dividing by the thickness of the mould body to obtain the absorption coefficient c 1 And c 2 ；
Shooting a target tissue image, which is represented as an image A;
performing energy spectrum decomposition according to the side bitmap generation method to perform energy spectrum decomposition on the image A to obtain a target tissue decomposition parameter A 1 And A 2 ；
Use and c 1 And c 2 Orthogonal coefficient pair A 1 And A 2 Weighting and calculating;
the new image a "=a is calculated by the following formula 1 c 2 -A 2 c 1 =∫ L1 c 2 a 1 (l)-c 1 a 2 (l)dl+∫ L2 c 1 c 2 -c 2 c 1 dl, where L 2 Is the thickness of soft tissue, L 1 The second term results in zero, except for other tissue thicknesses of soft tissue, because c in the ray integral path of soft tissue 1 c 2 And c 2 c 1 The images A '' obtained by the mutual cancellation are images which do not contain soft tissues.
By combining the energy spectrum decomposition algorithm and the absorption coefficient, the human tissue image can be shot, and the image with more accurate tissue structure and composition information can be reconstructed.
And step S114, repeating the operations of S104-S112 in the process of uniform movement of the detector.
And S116, independently splicing the two X-ray images generated by the image reading of the detector, the two decomposed energy spectrum images and the reconstructed target image respectively to obtain a side image of the measured object.
A side bitmap of a measured object, comprising:
in step S108, the detector reads the image to generate two side bitmaps formed by respectively splicing two X-ray images;
step S110, two side bitmaps are respectively spliced by the two decomposed energy spectrograms;
and (3) two side bitmaps are respectively spliced by the target images after the two energy spectrum images are reconstructed in the step (S112).
The detector image reading is conducted to generate two X-ray images, the two decomposed energy spectrum images and the reconstructed target image are spliced independently to obtain a side image of the measured object, and the reconstructed images are combined according to specific positions and sizes in the splicing process to present the overall view of the measured object on the side; by aligning and superposing reconstructed images of different angles or layers, the structure and the characteristics of the measured object can be accurately displayed by the side image; the obtained lateral images can be used for further analysis and diagnosis, and provide lateral information about the tested object, such as bone structure, organ position, abnormal situation and the like; by stitching the reconstructed images into side image, we can obtain a more comprehensive view of the object under test.
Fig. 2 is a schematic diagram of a configuration of a side bitmap generation apparatus 300 according to an embodiment of the present application. As shown in fig. 2, the side bitmap generation apparatus 300 according to the present application may include the following.
In some embodiments, the fast KVP switching unit 302 is connected to the source and is configured to rapidly switch the output voltage of the high-voltage power supply when receiving the control signal, so as to achieve fast KVP switching; a measured image acquisition unit 304 for acquiring an image from a measured object; a measured image processing unit 306, configured to process the obtained image from the measured object to obtain a decomposed energy spectrum image; an image reconstruction unit 308 for reconstructing the spectrogram image to obtain a target image; and a side bitmap acquiring unit 310, configured to obtain a side bitmap of the measured object by stitching using the target image.
In a specific application, the side bitmap generation apparatus 300 may be disposed in the CBCT, or may be disposed independently of the CBCT, and the side bitmap generation apparatus may be implemented by software, hardware, or a combination of both.
The present application also provides an electronic device 400 comprising: a memory 500, the memory 500 storing execution instructions; and a processor 600 that executes the execution instructions stored in the memory, so that the processor executes the above-described side bitmap generation method.
According to an embodiment of the present application, a readable storage medium has stored therein an execution instruction that is executed by the processor 600 to perform the above-described side bitmap generation method.
In the description of the present specification, reference to the terms "one embodiment/mode," "some embodiments/modes," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment/mode or example is included in at least one embodiment/mode or example of the present application. In this specification, the schematic representations of the above terms are not necessarily the same embodiments/modes or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments/modes or examples. Furthermore, the various embodiments/implementations or examples described in this specification and the features of the various embodiments/implementations or examples may be combined and combined by persons skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
While the preferred embodiments of the present patent have been described in detail, the present patent is not limited to the above embodiments, and various changes may be made without departing from the spirit of the present patent within the knowledge of those skilled in the art.
Claims (12)
1. A method for generating a side map, comprising:
s102, the detector can move to the other side;
s104, controlling the fast KVP switching source to rapidly expose twice by using a pulse signal sequence control signal;
s106, transmitting a double-image reading pulse signal to the detector based on the pulse signal sequence control signal while exposing, so that the detector reads and records an X-ray signal after each exposure;
s108, the detector reads the images to generate two X-ray images;
s110, decomposing the two X-ray images into two energy spectrum images, wherein:
according to given X-ray exposure images with two different energies, the rapid KVP switching source is used for shooting two times at the same position respectively, the tube voltage of the source is controlled to be a first kilovolt peak value in the first shooting and a second kilovolt peak value in the second shooting, wherein the second kilovolt peak value is at least 20KV higher than the first kilovolt peak value, and the rapid KVP switching source is used for shooting the X-ray exposure images with the same position,
V 1 =k 1 A 1 +k 2 A 2 +k 3 A 1 A 2 +k 4 A 1 2 +k 5 A 2 2
V 2 =k 6 A 1 +k 7 A 2 +k 8 A 1 A 2 +k 9 A 1 2 +k 10 A 2 2
fitting and representing gray values of pixel points on two X-ray images before decomposition, wherein V 1 And V 2 Expressed as gray values of pixel points on the image before decomposition, A 1 And A 2 Expressed as gray values of decomposed pixel points, k in the system of equations 1 ，k 2 ，k 3 ，k 4 ，k 5 ，k 6 ，k 7 ，k 8 ，k 9 ，k 10 Is a known energy spectrum characteristic parameter;
s112, reconstructing the two energy spectrum images, and separating contributions of different tissue structures in the two energy spectrum images according to the absorption characteristics of the different tissue structures of the human body to the X-rays with different energies so as to obtain corresponding target images;
s114, repeating the operations of S104-S112 in the process of uniform movement of the detector;
s116, independently splicing the two X-ray images generated by the detector image reading, the two decomposed energy spectrum images and the reconstructed target image respectively to obtain a side bitmap of the measured object.
2. The side bitmap generation method according to claim 1, wherein the side bitmap of the object under test comprises:
in step S108, the detector reads the image to generate two side bitmaps formed by respectively splicing two X-ray images;
step S110, two side bitmaps are respectively spliced by the two decomposed energy spectrograms;
and (3) two side bitmaps are respectively spliced by the target images after the two energy spectrum images are reconstructed in the step (S112).
3. The method of generating a side map according to claim 1, wherein the detector receives X-ray radiation generated by two exposures and converts it into an electrical signal, and the detector generates two X-ray images by reading and recording the electrical signal, each image corresponding to the result of one exposure.
4. The method of generating a bitmap according to claim 1, wherein the system of equations is solved according to newton's iterative method, and the successive approximation unknowns a are calculated according to iteration 1 And A 2 And (3) obtaining the gray value of the decomposed pixel point.
5. The side bitmap generation method according to claim 4, wherein setting a 1 And A 2 In each iteration, according to the current A 1 And A 2 And (3) taking the value into the equation set, calculating the difference value between the left side and the right side of the equation set, and continuously iterating to enable the difference value to approach 0, so as to obtain the solution of the equation set.
6. The method of generating a side map according to claim 1, wherein the spectral feature parameter is expressed as a k coefficient, k 1 ，k 2 ，k 3 ，k 4 ，k 5 Is the energy spectrum characteristic parameter, k of the second kilovolt peak value 6 ，k 7 ，k 8 ，k 9 ，k 10 Is the energy spectrum characteristic parameter of the first kilovolt peak value.
7. The side bitmap generation method according to claim 6, wherein the k coefficient verification method comprises:
selecting two reference substances as calibration samples of energy spectrum characteristic parameters, and manufacturing a plurality of die bodies, wherein each die body is formed by mixing two reference substances with different ratio thicknesses;
exposing and shooting each die body by using a first kilovolt peak value and a second kilovolt peak value to obtain corresponding V 1 And V 2 And a is known as 1 And A 2 Is a measurement of (2);
solving parameters using least squares method, to measure V 1 And V 2 And a is known as 1 And A 2 Substituting the difference value into an energy spectrum decomposition equation set to obtain a difference value between the left side and the right side of the equation set;
using least square method to solve k by minimizing the sum of squares of the difference values 1 ，k 2 ，k 3 ，k 4 ，k 5 ，k 6 ，k 7 ，k 8 ，k 9 ，k 10 Is a numerical value of (2).
8. The side bitmap generation method according to claim 1, comprising:
shooting a substance image with a near atomic number of human tissue, and applying the image to reconstruction of the two energy spectrum images, wherein the human tissue comprises bone tissue and soft tissue;
according to the first decomposition parameter obtained by energy spectrum decomposition of the equation set, obtaining an absorption coefficient, and representing the absorption characteristic of the substance;
shooting a target tissue image;
performing energy spectrum decomposition according to the equation set to obtain target tissue decomposition parameters;
and weighting and calculating the target tissue decomposition parameters according to the orthogonal coefficients of the absorption coefficients to obtain a reconstructed image.
9. The side bitmap generation method according to claim 8, comprising:
performing energy spectrum decomposition by using the equation set, selecting an image of a substance close to the atomic number of the bone tissue, and applying the image to the energy spectrum decomposition equation set to obtain a first decomposition parameter C 1 And C 2 First decomposition parameter C 1 And C 2 Dividing by the thickness of the mould body to obtain the absorption coefficient c 1 And c 2 ；
Shooting a target tissue image, which is represented as an image A;
performing energy spectrum decomposition on the image A according to the equation set to obtain a target tissue decomposition parameter A 1 And A 2 ；
Use and c 1 And c 2 Orthogonal coefficient pair A 1 And A 2 Weighting and calculating;
a new image a' =a is calculated by the following formula 1 c 2 -A 2 c 1 The obtained image a' is an image not including bone tissue.
10. The side bitmap generation method according to claim 8, comprising:
performing energy spectrum decomposition by using the equation set, selecting an image of a substance with atomic number close to that of the soft tissue, and applying the image to the energy spectrum decomposition equation set to obtain a first decomposition parameter C 1 And C 2 First decomposition parameter C 1 And C 2 Dividing by the thickness of the mould body to obtain the absorption coefficient c 1 And c 2 ；
Shooting a target tissue image, which is represented as an image A;
performing energy spectrum decomposition on the image A according to the equation set to obtain a target tissue decomposition parameter A 1 And A 2 ；
Use and c 1 And c 2 Orthogonal coefficient pair A 1 And A 2 Weighting and calculating;
the new image a "=a is calculated by the following formula 1 c 2 -A 2 c 1 The obtained image A '' is an image which does not contain soft tissues.
11. An electronic device, comprising: a memory storing execution instructions; and a processor executing the execution instructions stored in the memory, causing the processor to perform the side bitmap generation method of any one of claims 1 to 10.
12. A readable storage medium, wherein execution instructions are stored in the readable storage medium, which when executed by a processor are for implementing the side bitmap generation method of any one of claims 1 to 10.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4686695A (en) * | 1979-02-05 | 1987-08-11 | Board Of Trustees Of The Leland Stanford Junior University | Scanned x-ray selective imaging system |
| CN104422704A (en) * | 2013-08-21 | 2015-03-18 | 同方威视技术股份有限公司 | Method of decomposing energy spectrum information of X-ray energy spectrum CT and corresponding reconstruction method |
| KR101860145B1 (en) * | 2016-12-26 | 2018-06-27 | 연세대학교 원주산학협력단 | Dual energy imaging method for digital tomosynthesis apparatus, system using photon counting detector and digital tomosynthesis system thereof |
| CN110742635A (en) * | 2019-10-08 | 2020-02-04 | 南京安科医疗科技有限公司 | Composite energy spectrum CT imaging method |
| CN112581556A (en) * | 2020-12-25 | 2021-03-30 | 上海联影医疗科技股份有限公司 | Multi-energy CT image hardening correction method and device, computer equipment and storage medium |
| CN113281358A (en) * | 2021-06-22 | 2021-08-20 | 清华大学 | Multi-energy X-ray cone-beam CT imaging system and method |
| CN115067981A (en) * | 2022-05-19 | 2022-09-20 | 清华大学 | Dual-energy CT material decomposition method, device, system, electronic device and storage medium |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8165264B2 (en) * | 2009-01-28 | 2012-04-24 | Kabushiki Kaisha Toshiba | Method of pre-reconstruction decomposition for fast kV-switching acquisition in dual energy computed tomography (CT) |
| US9269168B2 (en) * | 2013-03-15 | 2016-02-23 | Carestream Health, Inc. | Volume image reconstruction using data from multiple energy spectra |
| US10451568B2 (en) * | 2014-08-22 | 2019-10-22 | Canon Medical Systems Corporation | Photon counting X-ray CT apparatus |
| TWI661812B (en) * | 2017-10-24 | 2019-06-11 | 行政院原子能委員會核能硏究所 | Tomography system and method thereof |
-
2023
- 2023-06-19 CN CN202310724684.9A patent/CN116458906B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4686695A (en) * | 1979-02-05 | 1987-08-11 | Board Of Trustees Of The Leland Stanford Junior University | Scanned x-ray selective imaging system |
| CN104422704A (en) * | 2013-08-21 | 2015-03-18 | 同方威视技术股份有限公司 | Method of decomposing energy spectrum information of X-ray energy spectrum CT and corresponding reconstruction method |
| KR101860145B1 (en) * | 2016-12-26 | 2018-06-27 | 연세대학교 원주산학협력단 | Dual energy imaging method for digital tomosynthesis apparatus, system using photon counting detector and digital tomosynthesis system thereof |
| CN110742635A (en) * | 2019-10-08 | 2020-02-04 | 南京安科医疗科技有限公司 | Composite energy spectrum CT imaging method |
| CN112581556A (en) * | 2020-12-25 | 2021-03-30 | 上海联影医疗科技股份有限公司 | Multi-energy CT image hardening correction method and device, computer equipment and storage medium |
| CN113281358A (en) * | 2021-06-22 | 2021-08-20 | 清华大学 | Multi-energy X-ray cone-beam CT imaging system and method |
| CN115067981A (en) * | 2022-05-19 | 2022-09-20 | 清华大学 | Dual-energy CT material decomposition method, device, system, electronic device and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 面向双能CT成像的医用X射线能谱重构解析方法;史再峰 等;南开大学学报;第53卷(第3期);第5-11页 * |
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