JPH07204170A - Activation area extraction method - Google Patents

Abstract

(57) [Summary] [Object] The present invention provides a method for easily extracting an activation region for efficient brain function analysis, and a method capable of examining activation states from various angles. . [Structure] When extracting an activation region, a plurality of images among different types of anatomical images, difference images, and test images are used to observe the signal changes in multiple directions.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION The present invention relates to a nuclear magnetic resonance apparatus (MRI).
(Device) is used for imaging for the purpose of analyzing brain functions and the like, and an activation region is extracted from the acquired time-series image data.

[0002]

2. Description of the Related Art Techniques for analyzing brain function using nuclear magnetic resonance have been developed. When measuring the response of the brain to an external stimulus, several tens to several hundreds of time-series images are taken while applying a stimulus such as light and sound to the subject for a predetermined period. From a series of images, the area where the signal intensity increases in synchronization with the applied external stimulus (activation area) is extracted, designated as the area to be analyzed (region of interest), and the signal change in that area is observed. It is common.

As a publicly known example of performing brain function analysis, Magnetic Resonance in Medicine, Vol. 25, 39.
0-397, 1992 (Magnetic Resonance in Medi
cine, 25 , 390-397 (1992)). Here, a difference image is created from the image to which the stimulus is not applied and the image to which the stimulus is being applied, and the location where the signal intensity largely changes is set as the activation area.

However, the change of the signal intensity due to the external stimulus is as small as about several percent, and there is a case where the region where the signal change becomes large due to the influence of noise is erroneously designated. In addition, the signal intensity may change asynchronously with the stimulus due to the influence of the mental activity of the living body (hereinafter, baseline fluctuation) .To extract the activation area due to the stimulus, a large amount of captured time-series image data is taken. Had to be examined in detail. Therefore, there has been a demand for a technique for extracting an activation region in a short time and efficiently performing brain function analysis.

In addition, as a device capable of measuring the function of the brain, MR
I, X-ray CT, PET (positron tomography),
There is SPECT (single photon tomography) and the like, and there has been a demand for a technique of comparing images taken by these different imaging devices and examining brain functions from various angles.

[0006]

SUMMARY OF THE INVENTION An object of the present invention is to examine a method for easily extracting an activation region, which is essential for efficient brain function analysis, and the state of activation from various angles. To provide a possible method.

[0007]

A feature of the present invention is that a plurality of images of an anatomical image, a difference image and a test image are used at the same time when an activation region is extracted. Here, the anatomical image refers to an image taken in order to grasp the anatomical structure of the brain, and the image taken when determining the measurement cross section before the brain function measurement corresponds to this. . The verification image is an image in which the degree of danger and the value of t distribution are imaged by testing the degree to which the signal change is synchronized with the external stimulus for each pixel.

[0008]

By using a plurality of images of different types in this way, it becomes possible to observe changes in signals in multiple directions. As a result, the activation region can be easily extracted, and the brain function can be efficiently analyzed. In addition, it will be possible to study the state of activation from multiple angles.

[0009]

EXAMPLE First, a brain functional image used in the present invention,
A method of creating the difference image and the test image will be described.

The difference image is created by taking the difference between the image in the period in which the stimulus is applied (stimulus application period) and the corresponding pixel in the image in the stationary period. By using this image, a portion where the signal is increased by the application of the external stimulus is displayed as a high signal area. When the signal increase is large and the difference with noise is clear, the activation area can be extracted without error even if a difference image is created using each of the stimulus application period and the rest period. it can. When noise and fluctuations in the baseline cannot be ignored, it is desirable to create an arithmetic mean image for each period and perform the difference. It is also possible to replace the difference image with the signal change rate image. The signal change rate image is an image obtained by normalizing one image or the arithmetic mean image of the stimulus application period with reference to one image or the arithmetic mean image of the stationary period. When performing this processing, it is necessary to remove background noise in advance.

The imaging of the result of the t-test, which is an example of the test image, will be described below. The value of t for each pixel is calculated using Equation 1.

[0012]

[Equation 1]

N1, m (1, pn) and S (1, pn) in the equation 1 are
These are the number of images, the signal average value, and the sum of squared deviations of the signals during the stimulus application period. N2, m (2, pn), S (2, pn)
Is the number of images in the stationary period, the signal average value, and the sum of squared deviations of the signals. In the mean value of the signal and the sum of squared deviations, the first subscript represents the presence or absence of stimulation, and the second subscript represents the pixel number. The image of the obtained value of t of each pixel is the test image.

The test image is created in order to judge whether or not the change in the signal is synchronized with the application of the stimulus (null hypothesis), which cannot be sufficiently judged only by the difference image.
FIG. 2 shows an example of the processing procedure related to the verification image. First, the images of the stationary period and the stimulus application period are input.
At this time, it is known that the change in the signal when the brain function is measured is delayed from several seconds to several tens of seconds from the start of the stimulation.
Therefore, in consideration of the rise and fall times of the signal change, the image in the specific period immediately after the stimulation is applied or immediately after the stimulation is stopped may be deleted. Next, an appropriate threshold value is set for the signal intensity, pixels below the threshold value are excluded as a background noise area, and pixels in the remaining area (area A) are extracted. It is desirable to set the value of t to 0 in the area determined to be background noise. The removal of background noise is intended to reduce the number of pixels to be tested, and is not an essential process. Area A
The value of t of the pixel is calculated, the result is imaged, and the test image is output. If necessary, the stationary period and the stimulus application period are changed, and a series of processing is repeated.

In the present invention, an anatomical image, a difference image, and a test image are used. The features of each image are shown in Table 1.

[0016]

[Table 1]

By using these images having different properties, it is possible to catch the signal change in multiple directions and to easily extract the activation region.

Next, the layout on the display and the analysis procedure when the brain function is analyzed using the above image will be described.

FIG. 1 shows an example of the screen of the present invention. 10 is an anatomical image, 20 is a difference image, 21 is a high signal region of the difference image, 30 is a test image, 31 is a large region of t in the test image, and 40 is a graph of calculation results such as signal changes. Reference numeral 50 is a menu screen for selecting a process. It is desirable that these are displayed on the same display 100 at the same time, but it is not necessarily limited to this, and they may be displayed on different displays.

An example of a brain function analysis procedure using the present invention,
This is shown in the flowchart of FIG. First, the coordinates of the high signal area 21 on the difference image 20 are input. This input is performed using a keyboard or a mouse. In addition, a threshold value may be set in advance, and the program or the like may be configured such that the coordinates of pixels exceeding the threshold value are automatically input. Less than,
In the present invention, both manual input and automatic input are simply referred to as input.

After the input, the corresponding position on the anatomical image 10 is displayed, and the value of t of the coordinate on the test image 30 is output. The corresponding position is displayed, for example, by color-displaying the corresponding area on each image. As a result, the high signal area 2
It is possible to accurately grasp the anatomical position of No. 1 and also to confirm whether or not a signal change occurs in synchronization with the application of the stimulus. The corresponding position on each image is displayed, and at the same time, the signal change or rate of change of the pixel is displayed on the graph 40.
The display content of the graph 40 is selected on the menu screen 50.

In the analysis of the brain function, the region of interest and the output contents of the graph are changed, and a series of processes are repeated. At that time, it is necessary to observe various processes and phenomena. These processes are also selected on the menu screen 50, but the graph 40 may be used at the same time.

An example of this is shown in FIG. The activated region may spread with time from the start of stimulation. In order to observe such a phenomenon, the stimulus application period is divided into a plurality of periods on the graph 40 to be period 1 and period 2. The difference images in the divided periods are added and averaged, and the addition and average image of the period 1 is output as the difference image 22 and the addition and average image of the period 2 is output as the difference image 23. As a result, the activation region 24 in the period 1 immediately after the stimulation is applied and the activation region 25 in the period 2 immediately after the stimulation are applied.
You can see that it has spread to. Also, the difference images 22 and 23
At the same time, it is desirable to output the verification image for each period.

In the description of FIG. 2, the process of removing the background noise has been described in order to reduce the number of pixels for calculating t. An example of further extension of this processing is shown in FIG. First, the file names of the images in the stationary period and the stimulus application period are input, and the arithmetic mean images are created respectively. Create a difference average image from the stimulus application period average image and the stationary period average image,
The difference image is normalized by the stationary period average image. This gives a signal change rate image in which the pixel values represent the signal change rate. A threshold value is set for the signal change rate, and the region B showing the signal change above the threshold value is extracted. Next, the same processing as in FIG. 2 is performed to remove the background noise and extract the area A. Pixels for which t-test is performed are limited to pixels included in both area A and area B. In the test image obtained after this processing, pixels in which the signal change rate is equal to or higher than the set threshold value and the signal change is synchronized with the application of the stimulus are displayed, and the activation region can be efficiently extracted. it can.

In all the processes described above, the number of pixels designated by one coordinate input is arbitrary. In some cases, the area where the signal decreases is observed in synchronization with the application of the stimulus. In this case, at least the display 100
Observe the distribution of the signal increase area and the signal decrease area by displaying the area where the signal change is positive in red and the area where the signal change is negative in blue on one image displayed in You can

Since both the difference image and the test image are created from a series of time-series images, the correspondence between the region to be photographed and the coordinates on the image is the same. However, the anatomical image may be created by using an imaging method different from that of the brain functional image. In this case, due to non-uniformity of the static magnetic field of the imaging device, difference in signal acquisition time, non-linearity of the gradient magnetic field that gives position information to the signal, etc. Is different from the correspondence in the brain functional image, and needs to be corrected.

For this correction, for example, a grid-shaped phantom is used before imaging, imaging is performed under the same imaging conditions as the anatomical image and brain functional image, and the image taken under the same conditions as the brain functional image is captured. The correction coefficient is derived and tabulated so that the grid point matches the grid point on the image taken under the same condition as the anatomical image, and this correction coefficient is used when correcting the brain functional image. Alternatively, the correction coefficient may be derived by creating grid points on the image using a shooting method called tagging. Alternatively, the correspondence between the position on the anatomical image and the position on the brain functional image is made into a function.

It is also possible to determine the contour of the brain and the position of the groove from the contrasts of the anatomical image and the brain functional image, and derive the above-mentioned correction coefficient. This method is also useful when the anatomical image and the brain functional image are photographed by different photographing devices, for example, when the anatomical image is photographed by X-ray CT and the brain functional image is photographed by MRI. As an example of the combination of the methods of photographing with different photographing apparatuses or extracting the function information, the example of Table 2 can be considered.

[0029]

[Table 2]

The present invention is applicable to any combination thereof. It is necessary to superimpose the measurement position on the anatomical image of the electroencephalogram and magnetoencephalogram. In that case, it is preferable to superimpose it on an MRI or X-ray CT image suitable for an anatomical image.

The case where the brain functional image is photographed by a specific photographing device has been described above. However, the brain functional image is created using a plurality of photographing devices having different physical phenomena to be measured, and each brain function is measured. The present invention is also applied when comparing and examining images. That is, when displaying at least one type of the difference image and the test image on the display, the brain function images captured by different image capturing devices are simultaneously displayed on the display. For example, it is assumed that MRI and PET are used in a photographing device. In brain function measurement using MRI, signal changes due to changes in blood flow and blood volume, and changes in magnetic susceptibility of hemoglobin due to desorption of oxygen are measured. On the other hand, PET can image the metabolism of glucose and the like. By displaying both brain functional images at the same time, it becomes possible to study the phenomenon occurring in the activation region from various angles. In this case, the combination of the photographing device or the method of extracting the function information is also the same as in Table 2.

[0032]

According to the present invention, the activation region can be easily extracted, and the brain function can be efficiently analyzed.

[Brief description of drawings]

FIG. 1 is a front view of a screen on which an activation area can be easily extracted.

FIG. 2 is a flowchart showing an example of a procedure for creating a test image.

FIG. 3 is a flowchart showing an example of a brain function analysis procedure.

FIG. 4 is a flowchart showing an example of a procedure for creating a test image.

FIG. 5 is an explanatory diagram of a case where a stimulus application period is divided into a plurality of periods and an arithmetic mean image of difference images is created in each period.

[Explanation of symbols]

10 ... Anatomical image, 20 ... Difference image, 21 ... High signal area of difference image, 30 ... Test image, 31 ... Area where t value of test image is large, 50 ... Menu screen, 100 ... Display screen.

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Etsuji Yamamoto 1-280, Higashi Koigokubo, Kokubunji, Tokyo Inside the Central Research Laboratory, Hitachi, Ltd.

Claims (11)

[Claims] 1. A cerebral function measuring method in which a subject is stimulated for a predetermined period of time to capture time-series images, and the activation status of the brain is extracted from changes in signals of a series of time-series images. A single image or an averaged image of a plurality of images taken in a non-existing period is used as a reference image, and a difference image is created by taking a difference between corresponding pixels from a series of the time-series image and the reference image, and a change in signal is generated. Test the null hypothesis regarding the presence or absence of stimulation, create a test image that images the test result, the difference image and the test image created, and three types of anatomical image of the brain structure A method for extracting an active region, characterized in that a plurality of types of images are simultaneously displayed on a display. 2. A brain function measuring method for stimulating a subject for a predetermined period of time to capture time-series images, and extracting the activation status of the brain from changes in signals of a series of time-series images, wherein the time-series images are , A plurality of image capturing devices having different physical phenomena to be measured, and each of the time-series images captured by each of the image capturing devices were captured during a period when no stimulus was applied, Alternatively, a process of creating a difference image from a series of the time-series image and the reference image using an arithmetic mean image of a plurality of images as a reference image, and a null hypothesis regarding a change in a signal and the presence or absence of stimulation is tested, and a test result is obtained. Performing a process of creating a test image to image, the difference image and the test image, and of the anatomical image of the brain structure is imaged, having a process of simultaneously displaying a plurality of types of images on the display, And above In the display processing, an activation area extraction method, characterized in that at least one of a difference image and a test image captured by different image capturing devices is simultaneously displayed on a display. 3. The region of interest is input using at least one of the three types of images, and a graph of the time change of the signal in the region of interest is displayed on the display simultaneously with the image according to claim 1 or 2. A method for extracting an activated area. 4. A region of interest is input using at least one of the three types of images, and the remaining regions are subjected to position correction as necessary. A method for extracting an activated region, in which a corresponding position on the image is derived and a region of interest is displayed on each image at the corresponding position. 5. The method according to claim 1 or 2, wherein an interest period is provided in a part of the entire measurement period, and at least one of an addition image of time series difference images during the interest period or an addition average image of difference images is created, A method for extracting an activated area displayed on a display. 6. The activation area extraction method according to claim 4, wherein a graph of a time change of a signal is used for inputting the interest period, and the interest period is input on the graph. 7. The activation area extraction method according to claim 1, wherein a threshold value is set for a signal on the time-series image, and pixels having a signal equal to or higher than the threshold value are used for the test to create the test image. 8. The signal according to claim 1 or 2, wherein a threshold value is provided for the signal on the time-series image, and a condition that the signal is equal to or higher than the threshold value and a threshold value for the change or change rate of the signal with respect to the application of the stimulus A method for extracting an activated area, wherein pixels for which a change or a change rate is equal to or more than a threshold value are simultaneously satisfied are used for the test, and the test image is created. 9. The activation area extraction method according to claim 1, 2, 6 or 7, wherein the test is performed by excluding the time series image of a specific period immediately after the stimulation is applied or immediately after the stimulation is stopped, and the verification image is created. 10. The activation area extraction method according to claim 1, wherein the difference image and the test image are photographed by an MRI apparatus. 11. The method for extracting an activated region according to claim 1, wherein the difference image, the test image, and the anatomical image are photographed by an MRI apparatus.