JP6882136B2 - Image processing equipment, image processing methods and programs - Google Patents

Description

The present invention relates to an image processing apparatus, an image processing method and a program.

Head function images such as cerebral blood flow SPECT images and glucose metabolism PET images are widely used clinically as a method for locally evaluating brain function. For example, information useful for diagnosing various degenerative diseases can be obtained by identifying a site in the brain in which the function is specifically reduced in a disease-specific manner and quantitatively evaluating the site as a region of interest (ROI).

WO2007 / 063656 WO2010 / 013300

However, in the methods disclosed so far, since the area for calculating the evaluation value is fixed, it is not possible to flexibly respond to the analysis of different degenerative diseases. In addition, since the judgment was made simply based on the evaluation value calculated in the region of interest, it is possible to distinguish whether the change in the value is due to a degenerative disease or another factor (for example, a decrease in blood flow due to a thrombus or the like). There was a problem that it could not be done.

In view of the above background, an object of the present invention is to provide an image processing apparatus having an increased degree of freedom in setting an area of interest.

The image processing apparatus of the present invention includes an input unit for inputting a functional image of the subject's brain, an anatomical standardization unit for anatomically standardizing the functional image of the subject, and an anatomical region allocated on the standard brain. The ROI candidate presentation unit that reads the data of the anatomical region from the storage unit that stores the data of the above and presents the data of the anatomical region as a candidate for ROI, and the selection of the anatomical region are accepted and selected. An evaluation value that calculates an evaluation value based on an ROI setting unit that sets an ROI on an anatomically standardized brain image of a subject based on one or more anatomical regions and a pixel value in the ROI. It includes a calculation unit and a display unit that displays information about the calculated evaluation value.

The image processing device of another aspect of the present invention includes an input unit for inputting a functional image of the subject's brain, and a conversion coefficient calculation unit for calculating a conversion coefficient for converting the functional image of the subject into a standard brain image. , The ROI candidate presentation unit that reads the data of the anatomical region from the storage unit that stores the data of the anatomical region allocated on the standard brain and presents the data of the anatomical region as a candidate for ROI, and the above. The selection of the anatomical region is accepted, the selected one or more anatomical regions are converted to match the subject's brain image using the inverse conversion coefficient of the conversion coefficient, and the ROI is generated on the subject's brain image. It includes an ROI setting unit to be set, an evaluation value calculation unit that calculates an evaluation value based on the set pixel value in the ROI, and a display unit that displays information on the calculated evaluation value.

According to the present invention, the operator can set the ROI by selecting a desired region from the anatomical regions presented by the ROI candidate presentation unit.

It is a figure which shows the structure of the image processing apparatus of 1st Embodiment. It is a figure which shows the example of the ROI candidate presentation screen. It is a figure which shows the example of the display screen of the evaluation result. It is a figure which shows the operation of the image processing apparatus of 1st Embodiment. It is a figure which shows the example of the ROI candidate presentation screen in 2nd Embodiment. It is a figure which shows the structure of the image processing apparatus of 3rd Embodiment. It is a figure which shows the operation of the image processing apparatus of 3rd Embodiment.

Hereinafter, the image processing apparatus according to the embodiment of the present invention will be described with reference to the drawings. In the embodiment described below, an example of performing image processing of a SPECT image obtained by photographing the brain of a subject using ^{123 I-IMP will be given. The} SPECT image taken using 123 I-IMP is an image showing the blood flow in the brain of the subject. The image processed by the image processing apparatus of the present invention ^{is not limited to the SPECT image taken by using 123} I-IMP, such as a SPECT image obtained by administering another drug, a PET image, an fMRI image, and the like. Functional images obtained by other modalities are also included.

(First Embodiment)
FIG. 1 is a diagram showing a configuration of an image processing device 1 according to the first embodiment. The image processing device 1 of the first embodiment has an input unit 10 for inputting data of a functional image of a subject's brain, and a control for setting an ROI for the input functional image and obtaining an evaluation value in the ROI. It has a unit 11, a display unit 12 for displaying the evaluation result, and a standard brain data storage unit 13 for storing standard brain data.

The input unit 10 is, for example, a communication interface. The functional image data is received from the SPECT device that has captured the functional image of the subject's brain through the communication interface. The display unit 12 is, for example, a display.

In a preferred embodiment, the image processing device 1 is composed of a computer including a CPU, a RAM, a ROM, a display, a keyboard, a mouse, a communication interface, and the like. A program for image processing is stored in a ROM, and the CPU reads the program from the ROM and executes the program, so that the computer performs image processing of the functional image of the subject's brain to obtain an evaluation value. Such programs are also included in the scope of the present invention.

The control unit 11 has an anatomical standardization unit 20, an ROI candidate presentation unit 21, an ROI setting unit 22, an evaluation value calculation unit 23, and a result output unit 24. The anatomical standardization unit 20 performs anatomical standardization on the functional image of the subject's brain, and converts the image of the subject's brain into an image of the standard brain. This anatomical standardization process is performed by known methods, such as the literature (Minoshima S et.al., J. Nucl. Med., 1994, 35, p.1528-37, or Friston KJ et.al., Human. Brain Mapping, 1995, 2, p.189-210) can be performed by the method described.

The anatomical standardization unit 20 converts a functional image of the subject's brain into a standard brain image in the form of a series of brain surface images. The brain surface image is obtained by extracting the maximum value or the average value of the pixels in a certain section (for example, 6 pixels from the brain surface) on the perpendicular line drawn from each point on the brain surface toward the inside of the brain (for example). Minoshima S, Frey KA, Koeppe RA, Foster NL, Kuhl DE: A diagnostic approach in Alzheimer's disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med. 1995; 36: 1238-48.).

The ROI candidate presentation unit 21 has a function of reading data of an anatomical region allocated on the standard brain from the standard brain data storage unit 13 and presenting the data of the anatomical region as a candidate for ROI. The anatomical region used in this embodiment is a region allocated according to Talairach's brain chart. The anatomical region data does not have to be limited to Talairach's brain pictorial book, and any available data can be used depending on the purpose of analysis and evaluation. For example, Penfield's brain map or Brodmann's brain map can be used.

FIG. 2 is a diagram showing a presentation screen of the ROI candidate presented by the ROI candidate presentation unit 21. In a preferred embodiment, the ROI candidate presentation screen includes a name of the anatomical region and a check box indicating whether or not the anatomical region is selected as the ROI. On the ROI candidate presentation screen, a plurality of anatomical regions can be selected by the check boxes.

In a preferred embodiment, the ROI candidate presentation screen includes an OK button and a Cancel button. In this case, when the OK button is selected, the anatomical region checked at that time is confirmed as a ROI candidate. If you select the Candle button, the check in the check box will be cleared and you will return to the previous screen.

The ROI candidate presentation unit 21 has tabs of "Group1", "Group2", "Group3", "Group4", and "Group5" at the upper part. As a result, the operator can switch tabs and set five ROIs of Group1 to Group5.

The ROI setting unit 22 sets the combination of anatomical regions selected by the ROI candidate presentation unit 21 as the ROI. The ROI setting unit 22 may transmit the set ROI data to the display unit 12 and display the ROI set on the display unit 12. The display unit 12 colors and displays the anatomical region in which the ROI is set, for example, on the template of the standard brain.

The evaluation value calculation unit 23 calculates the evaluation value using the pixel value in the set ROI. In the present embodiment, the evaluation value calculation unit 23 obtains a value obtained by normalizing the sum of the positive Z scores in the ROI with the ROI size (number of pixels or area) as the evaluation value. Here, the Z score is a value obtained for each pixel, and is obtained by the following equation (1) based on the pixel value of the image of the subject and the pixel value of the average image of the healthy person.
(Equation 1)
Z score = (added average pixel value of healthy person-pixel value of subject) / standard deviation pixel value of healthy person

The evaluation value calculation unit 23 calculates a value obtained by normalizing the sum of the positive Z scores of the pixels in the ROI to be evaluated by the ROI size (number of pixels or area), and uses it as the evaluation value of the ROI. In the present embodiment, the evaluation value calculation unit 23 divides the ROI into the left side and the right side of the brain, obtains the sum of the positive Z scores on the left side of the ROI and the sum of the positive Z scores on the right side, and corresponds to each. The evaluation value is obtained by dividing by the number of pixels of the ROI to be calculated.

The result output unit 24 sends the evaluation value of the ROI calculated by the evaluation value calculation unit 23 to the display unit 12, and causes the display unit 12 to display the evaluation result. Here, the result output unit 24 not only outputs the evaluation value, but also edits the image data generated from the Z score of each pixel, the data based on the evaluation value of a healthy person, and the like so that the evaluation result can be easily grasped. The data of the graph is sent to the display unit 12.

FIG. 3 is an example of a screen showing the evaluation result displayed on the display unit 12. Data for displaying this screen is sent from the result output unit 24 to the display unit 12. What is displayed in the area A1 at the upper part of the screen is the examination date, the examination method, and the subject information. On the left side of the screen, there is an area A2 for displaying a cerebral blood flow image and an area A3 for displaying a cerebral blood flow decrease image. The cerebral blood flow image shows the cerebral blood flow by color. Although the color is not expressed in the drawings of the patent gazette, the color gradually changes according to the cerebral blood flow, such as red when the cerebral blood flow is high, green when the cerebral blood flow is medium, and blue when the cerebral blood flow is low. It is displayed with. Further, in this example, the cerebral blood flow image is displayed by coloring a series of brain surface images such as the right lateral surface and the left lateral surface.

The cerebral blood flow decrease image shows the degree of decrease in cerebral blood flow (positive Z score value) as compared with a healthy subject by color. It is displayed in a color that gradually changes according to the cerebral blood flow, such as red when the degree of decrease in cerebral blood flow is large, green when it is moderate, and blue when it is small. The cerebral blood flow reduction image is also displayed by coloring a series of brain surface images to reflect the degree of cerebral blood flow reduction.

On the right side of the screen, the evaluation results for each region of interest (ROI) are displayed. In the upper right, there is an area A4 showing information of the area of interest set by the operator. In this example, five regions of interest are set from Group 1 to Group 5, and each region of interest is colored and shown on the brain surface image of the standard brain. Although the colors are not expressed in the drawings of the patent gazette, the labels of Groups 1 to Group 5 are colored orange, red, purple, blue, and green, respectively, and the brain surface image also has a region of interest corresponding to each group. It is colored in the same color as the label. As a result, the operator can easily grasp the set ROI.

In the area of "degree of decrease in cerebral blood flow in the area of interest" on the right side of the screen, the evaluation value for each ROI obtained by the evaluation value calculation unit 23 is shown in graph A5. The horizontal axis of the graph shows the Group number representing the set ROI and the left and right sides of each ROI. The vertical axis of the graph is a value obtained by normalizing the total value of positive Z scores by ROI size, and this value represents the degree of decrease in cerebral blood flow. In the graph, the evaluation values calculated for each ROI are plotted in circles. In addition, for comparison, the graph shows the average value of the evaluation values in healthy subjects as a rectangle, and the threshold value of the evaluation value as a horizontal line. Here, the threshold value is a guideline for determining that the evaluation value is abnormal (that is, there is a deviation from normal). In the example shown in FIG. 3, it can be seen that the evaluation values are higher than the threshold value on the left and right sides of Group1 and on the left side of Group2. In the area A6 at the bottom of the screen, a comment automatically generated based on the evaluation result is displayed.

FIG. 4 is a diagram showing the operation of the image processing device 1 according to the first embodiment. First, the image processing device 1 receives the input of the head medical image data of the subject at the input unit 10 (S10). In the present embodiment, the SPECT image taken by using ¹²³ I-IMP is input to the image processing device 1 as the image data for the head doctor. Next, the image processing device 1 performs anatomical standardization on the input head medical image data by the anatomical standardization unit 20 (S11).

Subsequently, the image processing device 1 operates the ROI candidate presentation unit 21 and uses the data of the anatomical region defined on the standard brain to select the ROI candidate using the screen as shown in FIG. Present to the operator (S12). When the operator selects an anatomical region that is a candidate for ROI on this screen, the image processing device 1 operates the ROI setting unit 22 and sets the ROI by the combination of the selected anatomical regions (S13). .. The image processing device 1 operates the evaluation value calculation unit 23, calculates the evaluation value in the ROI in the anatomically standardized image of the subject (S14), and then calculates the result by the function of the result output unit 24. Is output to the display unit 12 (S15), and the evaluation result is displayed on the display unit 12.
The image processing device 1 and the image processing method of the first embodiment have been described above.

The image processing apparatus 1 of the first embodiment presents an anatomical region as an ROI candidate to the operator, accepts the selection of the anatomical region, and sets the ROI based on the selected anatomical region. Therefore, the degree of freedom in setting the ROI can be increased.

As a result, the ROI for which the evaluation value is calculated can be arbitrarily set, so that it can be applied to the analysis of all degenerative diseases. For example, when the evaluation is performed only within the fixed disease-specific area of interest, only the disease to be diagnosed in advance can be evaluated. However, according to the image processing device 1 of the present embodiment, since the operator can select an anatomical region and set an arbitrary ROI while checking the image, it is estimated from the visual evaluation of the image. It is possible to evaluate any disease. For example, when a decrease in the accumulation of the frontal lobe is observed, the possibility of developing frontotemporal dementia (FTD) can be evaluated by the value of the evaluation value calculated by setting the region of interest in the frontal lobe. It becomes.

Further, since the image processing device 1 of the present embodiment calculates and outputs the evaluation value by dividing the ROI into the left side surface and the right side surface, the decrease in accumulation may be due to a degenerative disease, or the decrease in blood flow due to thrombus or the like. It becomes easier to distinguish whether the cause is.

(Second Embodiment)
Next, the image processing apparatus of the second embodiment will be described. The basic configuration of the image processing device of the second embodiment is the same as that of the image processing device 1 of the first embodiment, but the method of presenting the ROI candidate by the ROI candidate presenting unit 21 is different.

FIG. 5 is a diagram showing an example of a screen in which the ROI candidate presentation unit 21 presents an anatomical region as an ROI candidate. The ROI candidate presentation unit 21 does not display the name of the anatomical region and presents it to the operator, but presents the ROI candidate to the operator by displaying the anatomical region on a 3D image of the brain. On this screen, when the operator instructs the desired anatomical area to be included in the ROI, the instructed area is colored, and when the OK button is selected in that state, the anatomy is colored at that time. The anatomical domain is confirmed as a ROI candidate.

Since the image processing device of the second embodiment superimposes and displays the anatomical region on the 3D image of the brain, the operator can easily grasp the position where the ROI is to be set.

(Third Embodiment)
FIG. 6 is a diagram showing the configuration of the image processing device 3 according to the third embodiment. In the first embodiment, the brain image of the subject was converted into the standard brain by anatomical standardization, whereas in the third embodiment, the ROI set on the standard brain is the brain image of the subject. Reverse conversion to match.

The basic configuration of the image processing device 3 of the third embodiment is the same as that of the image processing device 1 of the first embodiment, but the image processing device 3 of the third embodiment further has a conversion coefficient. The calculation unit 25 is provided.

The conversion coefficient calculation unit 25 acquires the conversion coefficient used when the anatomical standardization unit 20 anatomically standardizes the functional image of the subject's brain and converts it into a standard brain. The ROI setting unit 22 sets the ROI based on the combination of anatomical regions selected by the ROI candidate presentation unit 21. At this time, using the inverse conversion coefficient of the conversion coefficient obtained by the conversion coefficient calculation unit 25, the inverse conversion is performed so that the ROI in the standard brain is matched with the brain image of the subject. Then, the evaluation value calculation unit 23 calculates the evaluation value. The result output unit 24 transmits the calculated evaluation value to the display unit 12. The result output unit 24 may also display the inversely transformed ROI superimposed on the brain image of the subject.

FIG. 7 is a diagram showing the operation of the image processing device 3 according to the third embodiment. First, the image processing device 3 receives the input of the head medical image data of the subject at the input unit 10 (S20). In the present embodiment, the SPECT image taken by using ¹²³ I-IMP is input to the image processing device 3 as the image data for the head doctor. Next, the image processing device 3 performs anatomical standardization on the input head medical image data by the anatomical standardization unit 20, and then operates the conversion counting calculation unit 25 to perform anatomical standardization. The conversion coefficient used at the time of this is acquired (S21).

Subsequently, the image processing device 3 operates the ROI candidate presentation unit 21 and uses the data of the anatomical region defined on the standard brain to select the ROI candidate using the screen as shown in FIG. Present to the operator (S22). When the operator selects an anatomical region that is a candidate for ROI on this screen, the image processing device 3 operates the ROI setting unit 22 and sets the ROI by the combination of the selected anatomical regions (S23). .. At this time, the ROI setting unit 22 performs an inverse transformation so as to match the ROI in the standard brain with the brain image of the subject by using the inverse conversion coefficient of the conversion coefficient obtained by the conversion coefficient calculation unit 25, and the brain of the subject. Set the ROI on the image. The image processing device 3 operates the evaluation value calculation unit 23 to calculate the evaluation value in the ROI (S24), and then outputs the calculated result to the display unit 12 by the function of the result output unit 24 (S25). ), The evaluation result is displayed on the display unit 12.
The image processing apparatus 3 and the image processing method of the third embodiment have been described above.

The image processing device 3 of the third embodiment reversely transforms the ROI so as to match the image of the subject's brain and superimposes it on the subject's brain image, so that the change in cerebral blood flow is examined in the subject's brain image. be able to.

In the present embodiment, an example is given in which the basic configuration is the same as that of the image processing device 1 of the first embodiment, but the basic configuration is the image processing device 2 of the second embodiment. May be the same as. That is, as shown in FIG. 5, the ROI is displayed in the image processing device 2 provided with the ROI candidate presentation unit 21 that presents the ROI candidate to the operator by displaying the anatomical region on the 3D image of the brain. At that time, it is also possible to adopt a configuration in which the ROI on the standard brain is inversely converted so as to match the image of the subject's brain.

Although the configuration and operation of the image processing device according to the embodiment of the present invention have been described above, the image processing device of the present invention is not limited to the above-described embodiment. In the above-described embodiment, an example of obtaining a value obtained by normalizing the sum of the positive Z scores with the ROI size as the evaluation value has been described, but the image processing apparatus may obtain other evaluation values. For example, the image processing apparatus may obtain the sum of the positive Z scores in the ROI as an evaluation value, or the Severity indicating the size of the region where the Z score is equal to or more than a predetermined threshold value, or the ratio occupied by the Severity in the ROI. The extent may be obtained as an evaluation value (Mizumura et al., Annals of Nuclear Medicine, Vol. 17, No. 4, 289-295, 2003).

In the above-described embodiment, the evaluation result is displayed on the brain surface image, but a tomographic image may be used instead of the brain surface image. For example, the anatomical standardization unit 20 may convert a functional image of the subject's brain into a standard brain image in the form of a series of tomographic images. In this case, the ROI setting unit 22 sets the ROI on a series of tomographic images, and the evaluation value calculation unit 23 calculates the evaluation value in the ROI set on the tomographic image. Further, in the embodiment in which the ROI set by using the conversion count used for standardization is inversely transformed (third embodiment), the ROI set on the tomographic image is inversely transformed and the shape of the ROI is obtained from the brain image of the subject. It is also possible to display the inversely transformed ROI on the tomographic image of the subject.

The present invention is useful as an image processing device or the like for functional images of subjects.

1,3 Image processing device 10 Input unit 11 Control unit 12 Display unit 13 Standard brain data storage unit 20 Anatomical standardization unit 21 ROI candidate presentation unit 22 ROI setting unit 23 Evaluation value calculation unit 24 Result output unit 25 Conversion coefficient acquisition unit

Claims (9)

An input unit for inputting a functional image of the subject's brain,
An anatomical standardization unit that anatomically standardizes the functional image of the subject,
ROI candidate presentation that reads the data of the anatomical region from the storage unit that stores the data of the anatomical region allocated on the standard brain and presents the data of the anatomical region as a candidate of the region constituting the ROI. Department and
Accepting a selection of the anatomical region to generate a region constituting the ROI by a combination of anatomical regions of multiple selected, ROI setting for setting the ROI on the anatomical standardized subject's brain image Department and
An evaluation value calculation unit that calculates an evaluation value based on the pixel value in the ROI,
A display unit that displays information about the calculated evaluation value,
An image processing device comprising. An input unit for inputting a functional image of the subject's brain,
A conversion coefficient calculation unit that calculates a conversion coefficient for converting the functional image of the subject into a standard brain image, and a conversion coefficient calculation unit.
ROI candidate presentation that reads the data of the anatomical region from the storage unit that stores the data of the anatomical region allocated on the standard brain and presents the data of the anatomical region as a candidate of the region constituting the ROI. Department and
Accepting a selection of the anatomical region to generate a region constituting the ROI by a combination of anatomical regions of multiple selected, the conversion to match the subject's brain image using the inverse transform coefficients of the transform coefficients ROI setting unit that sets the ROI on the subject's brain image
An evaluation value calculation unit that calculates an evaluation value based on the set pixel value in the ROI,
A display unit that displays information about the calculated evaluation value,
An image processing device comprising. As the evaluation value, the evaluation value calculation unit uses the sum of the positive Z scores in the ROI, the sum of the positive Z scores in the ROI normalized by the size of the ROI, and the Z score of a predetermined threshold value or more. The image processing apparatus according to claim 1 or 2 , which calculates at least one of an evaluation indicating the size of a region and an extent indicating the ratio of the evaluation to the ROI. The image processing apparatus according to any one of claims 1 to 3 , wherein the display unit displays data based on the evaluation value of a healthy person together with the evaluation value of a subject. The evaluation value calculation unit divides the ROI into a right side and a left side, calculates an evaluation value on each side, and calculates the evaluation value on each side.
The image processing apparatus according to any one of claims 1 to 4 , wherein the display unit displays evaluation values on the right side and the left side. It is a method of performing image processing of a functional image of a subject's brain by an image processing device.
A step of inputting a functional image of the subject's brain into the image processing device,
A step in which the image processing device anatomically standardizes the functional image of the subject.
The image processing device reads out the data of the anatomical region from the storage unit that stores the data of the anatomical region allocated on the standard brain, and uses the data of the anatomical region as a candidate for the region constituting the ROI. And the steps presented as
The image processing apparatus accepts the selection of the anatomical region to generate a region constituting the ROI by a combination of anatomical regions of the number of multiple selected, on the anatomical standardized subject's brain image Steps to set the ROI and
A step in which the image processing device calculates an evaluation value based on the pixel value in the ROI.
A step in which the image processing device displays information about the calculated evaluation value, and
An image processing method comprising. It is a method of performing image processing of a functional image of a subject's brain by an image processing device.
A step of inputting a functional image of the subject's brain into the image processing device,
A step in which the image processing device calculates a conversion coefficient for converting the functional image of the subject into a standard brain image.
The image processing device reads out the data of the anatomical region from the storage unit that stores the data of the anatomical region allocated on the standard brain, and uses the data of the anatomical region as a candidate for the region constituting the ROI. And the steps presented as
The image processing apparatus accepts the selection of the anatomical region, by a combination of anatomical regions of the number of multiple selected to generate a region constituting the ROI, the subject using an inverse transform coefficients of the transform coefficients The step of performing conversion to match the brain image and setting the ROI on the subject's brain image,
A step in which the image processing device calculates an evaluation value based on a set pixel value in the ROI.
A step in which the image processing device displays information about the calculated evaluation value, and
An image processing method comprising. A program that processes functional images of the subject's brain on a computer.
Steps to anatomically standardize the functional image of the subject,
A step of reading the data of the anatomical region from the storage unit that stores the data of the anatomical region allocated on the standard brain and presenting the data of the anatomical region as a candidate for the region constituting the ROI.
Accepting a selection of the anatomical region, comprising the steps of generating a region constituting the ROI by a combination of anatomical regions of multiple selected sets an ROI on an anatomical standardized subject's brain image ,
The step of calculating the evaluation value based on the pixel value in the ROI, and
A step to output information about the calculated evaluation value to the display unit,
A program that executes. A program that processes functional images of the subject's brain on a computer.
A step of calculating a conversion coefficient for converting the functional image of the subject into a standard brain image, and
A step of reading the data of the anatomical region from the storage unit that stores the data of the anatomical region allocated on the standard brain and presenting the data of the anatomical region as a candidate for the region constituting the ROI.
Accepting a selection of the anatomical region to generate a region constituting the ROI by a combination of anatomical regions of multiple selected, the conversion to match the subject's brain image using the inverse transform coefficients of the transform coefficients And the steps to set the ROI on the subject's brain image,
A step of calculating an evaluation value based on the set pixel value in the ROI, and
A step to output information about the calculated evaluation value to the display unit,
A program that executes.

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