JP2013040829A - Volume data processor and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To extract information that quatitatively shows motion features of a heart from an image of the heart synchronized with an electrocardiogram.SOLUTION: A volume data processor comprises: an electrocardiogram synchronous SPECT (Single Photon Emission Computed Tomography) data storage unit 11 for storing an electrocardiogram synchronous SPECT image composed of a plurality of phase images where one cycle of heartbeat has been divided into a plurality of segments and photographed by using an electrocardiogram synchronous SPECT; a motion vector calculation unit 13 for employing two phase images of phases adjacent to each other regarding a plurality of phase images stored in the electrocardiogram synchronous SPECT data storage unit 11 to calculate motion vector groups showing motion of a heart between the two phases, for motion between all phases; and a motion parameter calculation unit 17 for calculating a motion parameter showing motion features of a heart by analyzing motion for each predetermined area based on the motion vector groups.

Description

  The present invention relates to a technique for obtaining a motion parameter for evaluating a feature of heart motion from an electrocardiogram synchronization SPECT image and performing comparison between subjects using the motion parameter.

  A technique called myocardial SPECT (Single Photon Emission Computed Tomography) is known in which RI is administered to a subject and a tomographic image of the heart showing the state of blood flow of the myocardium is taken. Further, as an imaging method of myocardial SPECT, there are an ECG synchronous SPECT (Gateped SPECT) which is imaged in synchronization with an electrocardiogram and an ECG asynchronous SPECT which is asynchronous with the electrocardiogram. As a technique for processing an image taken by electrocardiogram synchronization SPECT, for example, there is a technique described in Patent Document 1.

JP 2006-153867 A

  Here, the electrocardiogram asynchronous SPECT is an image with a large blur that ignores the motion of the heart, and there is a limit to the information obtained therefrom.

  The ECG-synchronized SEPCT extracts a change due to the motion of the heart by analyzing each of a plurality of phase images so that more information can be obtained.

  Here, in order to evaluate whether or not the motion of the heart is appropriate, it is necessary to use information that quantitatively indicates the characteristics of the motion of the heart. However, no method has been established for extracting information that quantitatively indicates the feature of heart motion from an electrocardiogram-synchronized SEPCT image.

  This applies not only to the ECG-synchronized SEPCT image but also to images related to other modalities synchronized with the ECG.

  Accordingly, an object of the present invention is to extract information that quantitatively indicates the feature of the heart motion from an image synchronized with an electrocardiogram.

  Furthermore, another object of the present invention is to compare heart motion among subjects using information quantitatively indicating the feature of heart motion extracted from an image synchronized with an electrocardiogram.

  The volume data processing device according to one embodiment of the present invention comprises storage means for storing electrocardiogram-synchronized volume data comprising volume data of a plurality of phases, which is taken by dividing one cycle of a heartbeat into a plurality in synchronization with the electrocardiogram. Using a plurality of phase volume data stored in the storage means, a motion vector calculating means for calculating a plurality of motion vector groups indicating heart motion between phases, and a motion vector calculated by the motion vector calculating means Motion parameter calculating means for analyzing a motion for each predetermined region based on the group and calculating a motion parameter indicating the feature of the heart motion.

  In a preferred embodiment, one of the volume data of the plurality of phases is set as reference phase volume data, each voxel on the reference phase volume data is set as the predetermined area, and each voxel on the reference phase volume data is set as the predetermined area. When each reference voxel is used as the reference voxel, the motion parameter calculation means uses the motion vector group to identify a movement trajectory over one period of the heartbeat of each reference voxel, and based on the movement trajectory of the reference voxel, the reference voxel The motion parameter may be calculated every time.

  In a preferred embodiment, the movement parameter may be a maximum movement amount indicating a distance from a position in the reference phase volume data as a starting point to a position farthest from the movement locus.

  In a preferred embodiment, the movement parameter may be a maximum movement phase indicating a phase when the movement locus reaches a position farthest from a position in the reference phase volume data as a starting point.

  In a preferred embodiment, based on the volume data of any one phase and the motion parameter of the predetermined region, an image using the motion parameter of the predetermined region is displayed instead of the voxel value of the volume data of the one phase. You may provide further the image display means to be made.

  In a preferred embodiment, the storage means stores volume data of a first subject and volume data of one or more second subjects in the storage means, and the motion vector calculation means includes: For each of the volume data of the first subject and the one or more second subjects, a motion vector group between each phase is calculated, and the motion parameter calculation means is configured to calculate the first subject and the one or more second subjects. The motion parameter of each subject may be calculated, and the image display means may display each image based on the motion parameter of the first subject and the motion parameter of the one or more second subjects. .

  In a preferred embodiment, for any subject, the image display unit may further display an image corresponding to the volume data of any one phase in a display mode corresponding to the maximum movement amount of each voxel. .

  In a preferred embodiment, the motion vector calculation means may calculate the motion vector group based on a density gradient between volume data of two phases adjacent to each other.

  In a preferred embodiment, the volume data may be SPECT (Single Photo Emission Computed Tomography) image data.

1 is an overall configuration diagram of a SPECT image processing system according to an embodiment of the present invention. It is explanatory drawing of an electrocardiogram synchronous SPECT. It is explanatory drawing of a motion vector. It is a flowchart of the process which the motion vector calculation part 13 performs. An example of the movement locus of the reference voxel R specified by the movement locus extraction unit 171 is shown. It is a flowchart which shows the procedure of the motion vector calculation process which the motion parameter calculation part 17 performs. 4 is a flowchart showing an overall processing procedure of the SPECT image processing apparatus 100. It is a display screen of the maximum movement amount on the phase image. It is a display screen of the maximum movement amount on the phase image. The display example of a movement locus is shown. The display example of a movement locus is shown.

  Hereinafter, a SPECT image processing system according to an embodiment of the present invention will be described with reference to the drawings. In the present embodiment, an electrocardiogram-synchronized SPECT image analysis that analyzes an image captured based on an electrocardiogram-synchronized SPECT method for analyzing the blood flow and function of the myocardium will be described as an example. In addition, the present invention can be similarly applied to each image such as PET (Positive Emission Computed Tomography), MRI (Magnetic Resonance Imaging), CT (Computed Tomography), and ultrasonic waves synchronized with the electrocardiogram.

  FIG. 1 is an overall configuration diagram of a SPECT image processing system according to the present embodiment. That is, the present system includes an image reconstruction system 1 that generates a three-dimensional image of a subject's heart by an ECG-synchronized SPECT method, and SPECT image processing that analyzes time-series image data reconstructed by the image reconstruction system 1 Device 100.

  The image reconstruction system 1 performs electrocardiogram synchronization SPECT that generates a three-dimensional SPECT image of the heart in each phase in synchronization with the electrocardiogram. For example, as shown in FIG. 2, an interval between R waves of an electrocardiogram (RR interval: one cycle of heart motion) is equally divided into N (N is an integer of 2 or more), and 1 / of the RR interval is obtained. A SPECT image of each phase (hereinafter referred to as a phase image) is taken at N sampling periods. FIG. 2 illustrates a short-axis tomographic image (Short Axis; SA image), which is one tomographic image of a three-dimensional image. In addition to this, a long-axis vertical tomographic image (Vertical Long Axis) of the left ventricle is also shown. ; VLA image), and long axis horizontal tomogram (Horizontal Long Axis; HLA image).

  This photographing is continuously performed for at least one cycle of the heartbeat. The image reconstruction system 1 generates N phase images (volume data) by superimposing images of the same phase over a plurality of cycles for the same part. 2 shows an example where N = 8, but N is arbitrary, and may be 16, 20, 32, for example. The ECG-synchronized SPECT image generated by the image reconstruction system 1 is stored in the ECG-synchronized SPECT data storage unit 11 of the SPECT image processing apparatus 100.

  Returning to FIG. 1, the SPECT image processing apparatus 100 includes an image processing apparatus body 10, an input device 3 such as a keyboard, a pointing device, and a touch panel, and a display device 5 such as a liquid crystal display.

  The image processing apparatus main body 10 is configured by a general-purpose computer system including a processor and a memory, for example, and individual components or functions in the image processing apparatus main body 10 described below are executed by executing a computer program, for example. Realized. The computer program can be stored in a computer-readable recording medium.

  The image processing apparatus main body 10 includes an electrocardiogram-synchronized SPECT data storage unit 11 that stores an electrocardiogram-synchronized SPECT image (an electrocardiogram-synchronized image), a motion vector calculation unit 13 that calculates a motion vector from the electrocardiogram-synchronized SPECT image, and a heart motion. A vector data storage unit 15 that stores motion vector data, a motion parameter calculation unit 17 that calculates motion parameters indicating features of heart motion, a healthy person data processing unit 18 that processes motion parameters of healthy persons, and a motion A motion parameter data storage unit 19 that stores parameters, a normalization processing unit 20, a polar map generation unit 21, and a display control unit 23 are provided.

  The ECG-synchronized SPECT data storage unit 11 stores the ECG-synchronized SPECT data 111 of the patient (first subject) and the ECG-synchronized SPECT data 113 of one or more healthy persons (second subjects). The ECG-synchronized SPECT images 111 and 113 are composed of phase images (volume data) of a plurality of phases, which are taken by dividing one cycle of the heartbeat into a plurality of parts by the ECG-synchronized SPECT. Since each phase image is a three-dimensional image, the ECG-synchronized SPECT images 111 and 113 are volume data in which respective count values (pixel values) are stored in three-dimensional voxels.

  The motion vector calculation unit 13 calculates a motion vector indicating the motion of the heart between the phases by using two phase images of phases adjacent to each other for a plurality of phase images of the electrocardiogram synchronization SPECT image. The motion vector calculation unit 13 performs processing described below for each of the patient's ECG-synchronized SPECT image 111 and one or more healthy ECG-synchronized SPECT images 113 stored in the ECG-synchronized SPECT data storage unit 11. To calculate the motion vector of the patient and the motion vector of the healthy person. The patient motion vector data (patient vector data) 151 corresponding to the ECG-synchronized SPECT image 111 and the healthy person motion vector data (healthy person vector data) 153 corresponding to the ECG-synchronized SPECT image 113 are calculated as follows. Are stored in the vector data storage unit 15, respectively.

  The motion vector calculation unit 13 individually indicates where each voxel corresponding to the heart region in the phase image in the previous phase among the two phase images in the phase adjacent to each other has moved in the phase image in the subsequent phase. The three-dimensional motion vector is calculated. That is, the motion vector calculation unit 13 calculates a motion vector group including individual motion vectors for the number of voxels from two phase images in adjacent phases. The motion vector calculation unit 13 calculates a motion vector group for all phases. In the case of an 8-phase ECG-synchronized SPECT image as shown in FIG. 2, seven motion vector groups are calculated.

  The motion vector calculation unit 13 may calculate each individual motion vector with a plurality of voxels as one unit, or the last phase image and the first phase image (phase images P8 and P1 in the case of FIG. 2). A motion vector group in between may be calculated.

  The motion vector calculation unit 13 calculates a motion vector based on a density gradient between two phase images whose phases are adjacent to each other. For example, the motion vector calculation unit 13 may calculate a motion vector group between phases using an optical flow method (particularly, a gradient method using a concentration gradient or a block matching method). The motion vector calculation unit 13 may calculate the motion vector by other methods.

  A processing example of the motion vector calculation unit 13 will be specifically described with reference to FIG. Here, for convenience of explanation, a two-dimensional image and a two-dimensional vector are illustrated, but in reality, the motion vector calculation unit 13 uses a three-dimensional image (volume data) to generate a three-dimensional vector. calculate.

  FIG. 3 shows SA images in phase image P1, phase 2 phase image P2, and phase 3 phase image P3 as examples of continuous phase images. The motion vector calculation unit 13 calculates a motion vector group V1 between phases 1-2 from the phase images P1 and P2. Similarly, the motion vector calculation unit 13 calculates a motion vector group V2 between phases 2-3 from the phase images P2 and P3. The motion vector calculation unit 13 performs the same processing for the images after phase 4. Each arrow and point in the motion vector groups V1 and V2 shown in FIG. 3 indicates individual motion vectors.

  For example, when calculating the motion vector group, the vector calculation unit 13 uses any of the voxels of the phase image of the previous phase (for example, phase 1) to the phase image of the subsequent phase (for example, phase 2) using the optical flow method. Individual motion vectors for each voxel are calculated. Each individual motion vector included in the motion vector group is associated with each voxel of the phase image of the previous phase.

  FIG. 4 is a flowchart of processing performed by the motion vector calculation unit 13. The motion vector calculation unit 13 performs the following process on each of the patient's ECG-synchronized SPECT image 111 and one or more healthy persons' ECG-synchronized SPECT images 113.

  First, the motion vector calculation unit 13 specifies two adjacent phase images as target images (S11). The motion vector calculation unit 13 calculates a motion vector group from the previous phase image of the target image to the subsequent phase image by the optical flow method using the target image specified in step S11 (S13). The motion vector calculation unit 13 stores the motion vector group calculated here in the vector data storage unit 15 (S15). The motion vector calculation part 13 performs the process of step S11-S15 between all the phases (S17). The processes from Steps S11 to S17 are repeated until the vector group between all the phases calculated here converges within a predetermined reference range (S19).

  Returning to FIG. 1, the vector data storage unit 15 stores the motion vector data calculated by the vector calculation unit 13. For example, when the ECG-synchronized SPECT images 111 and 113 are divided into eight phases as one cycle of the heartbeat as in the above example, the vector data storage unit 15 stores the ECG-synchronized SPECT images 111 and 113 of the respective patients and healthy persons. For 113, seven motion vector groups are stored as vector data 151 and 153, respectively. In the vector data 151 and 153 of the patient and the healthy person, one three-dimensional vector is assigned to each three-dimensional voxel as described above.

  Based on the motion vector group calculated by the motion vector calculation unit 13, the motion parameter calculation unit 17 analyzes a motion for each predetermined region and calculates a motion parameter indicating the feature of the heart motion. Here, the predetermined area is composed of one or more voxels. In the present embodiment, a case will be described as an example where motion parameters are calculated in units of voxels, which is the minimum unit of the region.

  For example, the motion parameter calculation unit 17 uses a plurality of motion vector groups, sets a plurality of voxels on a reference phase image, which is one of a plurality of phase images, as reference voxels, and sets 1 of the heartbeat of each reference voxel. A movement trajectory over a period is specified, and a motion parameter is calculated for each reference voxel based on the movement trajectory of the reference voxel. The motion parameter calculated by the motion parameter calculation unit 17 is stored in the motion parameter data storage unit 19.

  In the present embodiment, as an example of the motion parameter, a parameter related to the maximum movement in which the movement amount of each part of the heart becomes the maximum in the movement of the heart in one cycle of the heartbeat, and an amount of change (movement amount) ) Is calculated as a parameter related to the maximum change that maximizes. As parameters related to maximum movement, for example, when a certain phase is set as a reference phase, each part of the heart has moved by the maximum movement amount at which the movement distance moved from the position in the reference phase is the maximum, and the maximum movement amount. Phase (maximum movement phase) and a vector (maximum movement vector) from the position in the reference phase to a position moved by the maximum movement amount. The parameters related to the maximum change include, for example, the maximum change amount in which the change (movement distance) between adjacent phases becomes the maximum, the phase between the phases where the maximum change amount is reached, and the vector ( Maximum change vector). Hereinafter, these calculation methods will be described in detail.

  The motion parameter calculation unit 17 includes a movement locus extraction unit 171, a maximum movement calculation unit 173, and a maximum change calculation unit 175.

  The movement trajectory extraction unit 171 uses a plurality of motion vector groups, and sets a plurality of voxels on the reference phase image, which is one of the plurality of phase images, as reference voxels, and sets the reference voxel in one cycle of the heartbeat. Identify the traversing trajectory. The movement trajectory extraction unit 171 sets one phase image as a reference phase image. Then, each voxel on the reference phase image is set as a reference voxel, the individual motion vector corresponding to each reference voxel is traced, and the position on the phase image other than the reference phase image is specified, whereby the reference voxel Extract the movement trajectory.

  FIG. 5 shows an example of the movement locus of the reference voxel R specified by the movement locus extraction unit 171.

  Here, the phase image P1 will be described as a reference phase image. However, a reference phase image other than the phase image P1 may be used. The movement locus extraction unit 171 specifies the movement locus M as follows for each voxel on the reference phase image as the reference voxel R.

  The movement trajectory extraction unit 171 performs the individual motion associated with the reference voxel R from the motion vector group (here, the motion vector group V1) between the reference phase image and the next phase image (here, the phase image P2). The vector v1 is specified. Based on the individual motion vector v1, the corresponding voxel R2 that is the movement destination of the reference voxel R in the phase image P2 that is the next phase image is determined.

  Next, the movement locus extraction unit 171 specifies the individual motion vector v2 associated with the corresponding voxel R2 from the motion vector group V2 between the phase images P2 and P3 in the same manner as described above. Based on the individual motion vector v2, the corresponding voxel R3 that is the movement destination of the reference voxel R in the phase image P3 that is the next phase image is determined.

  By performing such processing using all motion vector groups and phase images, it is possible to extract the movement trajectory M of the reference voxel R in which individual vectors starting from the reference voxel R are connected over one heartbeat period.

  The maximum movement calculation unit 173 calculates a parameter relating to the maximum movement for each voxel of the reference phase image based on the movement locus M specified by the movement locus extraction unit 171. For example, the maximum movement calculation unit 173 calculates a maximum movement amount, a maximum movement phase, and a maximum movement vector.

  Hereinafter, description will be given with reference to FIG. The maximum movement calculation unit 173 calculates the movement distances from the reference voxel R to the corresponding voxels R2 to R8 based on the position coordinates of the reference voxel R and the corresponding voxels R2 to R8, respectively, and sets the maximum distance among them to the maximum The movement amount is Dmax. That is, the maximum movement amount Dmax is a distance from a position (reference voxel) in the reference phase image that is the starting point in the movement locus M to a position (corresponding voxel) that is farthest from the position. The maximum movement calculation unit 173 sets the phase having the maximum movement amount Dmax as the maximum movement phase DPmax. That is, the maximum movement phase DPmax is a phase that is the position (corresponding voxel) farthest from the position (reference voxel) in the reference phase image that is the starting point in the movement trajectory. Furthermore, the maximum movement calculation unit 173 sets a vector from the reference voxel R to the corresponding voxel in the maximum movement phase DPmax as the maximum movement vector DVmax.

  The maximum change calculation unit 175 calculates a parameter relating to the maximum change for each voxel of the reference phase image based on the movement trajectory M specified by the movement trajectory extraction unit 171. For example, the maximum change calculation unit 175 calculates the maximum change amount, the maximum change phase, and the maximum change vector.

  The maximum movement calculation unit 173 and the maximum change calculation unit 175 calculate the respective parameters from the patient vector data 151 based on the movement trajectory extracted by the movement trajectory extraction unit 171, and perform motion as the patient motion parameter data 191. The parameter data is stored in the parameter data storage unit 19. Similarly, the maximum movement calculation unit 173 and the maximum change calculation unit 175 calculate each parameter from the vector data 153 of one or more healthy persons, and use this as the motion parameter data 193 of one or more healthy persons. Save in the storage unit 19.

  Hereinafter, description will be given with reference to FIG. The maximum change calculation unit 175 determines a vector having the largest magnitude (long movement distance) among the individual motion vectors v1 to v7 constituting the movement trajectory M of the reference voxel R as the maximum change vector CVmax (here, the individual motion vector). v2). The maximum change vector CVmax is the maximum change amount Cmax, and the phase between the phases indicating the phase between which the maximum change vector CVmax is a vector (here, between phases 2-3) is the maximum change phase CPmax. .

  FIG. 6 is a flowchart showing a procedure of motion vector calculation processing performed by the motion parameter calculation unit 17. The motion parameter calculation unit 17 executes the following processing using the vector data 151 and 153 of each of the patient and the subject.

  The motion parameter calculation unit 17 first determines one of the phase images stored in the electrocardiogram synchronization SPECT data storage unit 11 as a reference image (S21). Further, the motion parameter calculation unit 17 determines one voxel in the reference image as a reference voxel (S23).

  The movement trajectory extraction unit 171 extracts a movement trajectory over one cycle of the heartbeat using the data of each motion vector group for the reference voxel (S25). Then, the maximum movement calculation unit 173 calculates the motion parameter relating to the maximum movement as described above based on the movement trajectory extracted in step S25 (S27). Further, the maximum change calculation unit 175 calculates a motion parameter related to the maximum change as described above based on the movement trajectory extracted in step S25 (S29). Thereby, a motion parameter for one reference voxel is calculated. The motion parameters calculated in steps S27 and S29 are stored in the motion parameter data storage unit 19 (S31).

  The motion parameter calculation unit 17 performs the processing from step S23 to S31 for all the voxels of the reference image, and when the motion parameters of all the voxels are obtained, this processing ends (S33).

  Thereby, the motion parameter which shows the feature of the motion of the heart of a patient and one or more healthy persons can be extracted using the motion vector calculated | required from the electrocardiogram synchronous SPECT image. With these parameters, it is possible to quantitatively evaluate the motion of the heart.

  Returning to FIG. 1, the motion parameter data storage unit 19 stores patient motion parameter data 191 and healthy subject motion parameter data 193, respectively. In the present embodiment, the motion parameters include parameters related to maximum movement (maximum movement amount, maximum movement phase, maximum movement vector) and parameters related to maximum change (maximum change amount, maximum change phase, maximum change vector). included. In the patient motion parameter data 191 and the healthy person motion parameter data 193, the above motion parameters are stored in association with each voxel unit of the reference image.

  Here, the motion parameter data storage unit 19 further stores average motion parameter data 195 for healthy subjects. The healthy person average motion parameter data 195 is the healthy person average parameter data calculated by the healthy person data processing unit 18 based on the motion parameter data 193 of one or more healthy persons. For example, the healthy person data processing unit 18 averages the motion parameter data 193 of each of a plurality of healthy persons to generate a healthy person average motion parameter 195. In the subsequent processes, the healthy person data processing unit 18 that may use the average healthy person motion parameter data 195 as the motion parameters of the healthy person is a normalization processing unit 20 to be described below. After normalizing, the average motion parameter data 195 of healthy persons may be generated.

  The normalization processing unit 20 normalizes the motion parameter data stored in the motion parameter data storage unit 19. Because there are individual differences in the size of the heart, the comparison is performed after normalization is performed to remove individual differences.

  The polar map generation unit 21 generates a polar map (bull's eye map) based on three-dimensional image data of the heart such as the electrocardiogram synchronization SPECT images 111 and 113. In the present embodiment, the polar map generator 21 reflects the motion parameter in the polar map. That is, the polar map generation unit 21 generates a polar map using motion parameters instead of the voxel values of the reference phase image, based on the reference phase image and the motion parameters of each reference voxel.

  For example, the polar map generation unit 21 specifies voxels to be reflected in the polar map for the ECG-synchronized SPECT images 111 and 113 according to a known polar map generation method. Normally, a polar map is generated using the count value of the voxel, but in this embodiment, a polar map is generated using the value of the motion parameter associated with the voxel. For example, instead of the voxel count value, a polar map using the maximum movement amount or a polar map using the maximum change amount may be generated. As a result, a polar map based on the patient data and a polar map based on the healthy person data are generated, and both are displayed on the display device 5 via the display control unit 23, thereby comparing the motion parameters of the patient and the healthy person. can do.

  The polar map generation unit 21 may generate a polar map from the motion parameter data 193 of each healthy person for one or more healthy persons, or a healthy person average motion parameter obtained by averaging motion parameters of a plurality of healthy persons. A polar map may be generated from the data 195.

  In addition, the polar map production | generation part 21 can normalize a test subject's data by producing | generating a polar map, and can compare subjects (for example, a patient and a healthy person). Therefore, the SPECT image processing apparatus 100 may perform comparison between subjects using a normalization method other than the polar map.

  Based on the volume data of any one phase and the motion parameter of the predetermined area, the display control unit 23 displays an image using the motion parameter of the predetermined area instead of the voxel value of the volume data of the one phase. To display. As a display mode of the image displayed on the display device 5 by the display control unit 23, a “polar map” in which the entire heart can be seen at a time, a “3D display” in which the heart can be seen, and a cross section of the myocardial tissue are displayed. There are “tomographic images” that can be seen.

  For example, when displaying a polar map, the display control unit 23 causes the display device 5 to display the polar map generated by the polar map generation unit 21.

  Further, the display control unit 23 may cause the display device 5 to display the ECG-synchronized SPECT images 111 and 113 stored in the ECG-synchronized SPECT data storage unit 11 and the vector data 151 stored in the vector data storage unit 15. Good. Further, the display control unit 23 may output the numerical values of the motion parameter data 191, 193, 195 stored in the motion parameter data storage unit 19 to the display device 5 as they are. At this time, the display control unit 23 displays both the patient movement parameters and the healthy person movement parameters on the display device 5, whereby the two can be compared.

  The display control unit 23 may display an image corresponding to the motion parameters 191, 193, and 195 of the patient and the healthy person so as to overlap the heart image. For example, the display control unit 23 displays, on the two-dimensional tomographic image or three-dimensional image of the heart, an image having a display mode corresponding to the value of the motion parameter, superimposed on the corresponding voxel position. The heart image may be, for example, the patient or healthy ECG synchronized SPECT images 111 and 113 stored in the ECG synchronized SPECT data storage unit 11, or may be another image. The display mode according to the value of the motion parameter may be, for example, a display color-coded according to the value of the parameter, or a region where the parameter value exceeds a predetermined threshold.

  Moreover, the display control part 23 may display each phase image and the image which shows the characteristic of each phase of a patient and a healthy person's motion parameter 191,193,195 overlaid. For example, the display control unit 23 displays the phase in which the maximum movement phase is recorded in a predetermined color for each voxel in each phase image in the same subject. Or the phase which moved more than the predetermined ratio (for example, 50%) of the maximum moving amount of each voxel may be specified, and the corresponding voxel of the corresponding phase image may be displayed with a specific color. Thereby, the synchrony of the myocardium can be grasped. For example, a subject with high synchrony is displayed in a predetermined color centered on a specific phase, but a subject with low synchrony may display a region displayed in a predetermined color in many phases. Conceivable. As a result, it is possible to grasp a shift in synchrony of the myocardium in units of voxels, and to detect a shift in synchrony that is a sign of myocardial infarction at an early stage.

  For example, the display control unit 23 displays an image corresponding to a phase image (volume data) of any one phase for any subject in a display mode corresponding to the maximum movement amount of each voxel. In the example shown below, the maximum movement amount of a certain patient is displayed, but in the same manner, the maximum movement amount of a certain healthy person or average of healthy persons can be displayed.

  8 and 9 show examples of display screens 1000 and 1100 for the maximum movement amount on the phase image. As shown in the figure, the display control unit 23 displays a phase image of a certain phase (here, a reference phase). FIG. 8 is a display example of slice images in the reference phase (eight SA images, four VLA images and four HLA images), and FIG. 9 is an example of 3D display in the same phase. In these images, the maximum movement amount of the voxel included in the motion parameter data 191 is set for each voxel value, and is displayed in a display mode (here, display color) corresponding to the voxel value. Has been.

  Thereby, the magnitude | size of the largest moving amount | distance for every site | part of the heart can be grasped | ascertained. In particular, it is possible to easily find a portion where the maximum movement amount is small (a portion where movement is not good). Further, when the cross-sectional view is displayed as shown in FIG. 8, the difference in the maximum movement amount in the thickness direction of the heart can be grasped. For example, it is possible to find differences in movement between the inner wall and the outer wall.

  10 and 11 show display examples of the movement trajectory. 10 is a voxel selection screen, FIG. 11A is a movement trajectory screen of a plurality of voxels, and FIG. 11B is an enlarged display screen of a movement trajectory of one voxel. That is, the display control unit 23 displays the voxel selection screen 1200 of FIG. 10 and causes the operator to select a heart region (voxel) 1210. On the voxel selection screen 1200, a plurality of parts can be selected. Based on the vector data 151 and 153, the display control unit 23 causes the movement locus of the part 1210 selected here to be displayed in 3D on the movement locus display screen 1300 as shown in FIGS. The movement trajectory joins individual motion vectors starting from a dot and ends with a square. In this example, the movement trajectory in units of voxels is displayed. However, an individual motion vector of an area composed of a plurality of voxels may be obtained and used to display the movement trajectory.

  Furthermore, the display control unit 23 may display the display mode image based on the patient motion parameter 191 and the display mode image based on the healthy person motion parameter 195 side by side.

  FIG. 7 is a flowchart showing an overall processing procedure of the SPECT image processing apparatus 100 having the above-described configuration. The electrocardiogram-synchronized SPECT data storage unit 11 stores an electrocardiogram-synchronized SPECT image 111 of a patient reconstructed in advance by the image reconstruction system 1 and an electrocardiogram-synchronized SPECT image 113 of one or more healthy subjects.

  First, the motion vector calculation unit 13 calculates a patient motion vector group based on the patient's ECG-synchronized SPECT image 111, and stores it as the patient vector data 151 in the vector data storage unit 15 (S41). The motion vector calculation unit 13 further calculates a motion vector group of the healthy person based on one or more electrocardiogram-synchronized SPECT images 113 of the healthy person, and stores it as the healthy person vector data 153 in the vector data storage unit 15 (S43). .

  The motion parameter calculation unit 17 calculates a patient motion parameter based on the patient vector data 151 and stores it as the patient motion parameter data 191 in the motion parameter data storage unit 19 (S45). The motion parameter calculation unit 17 further calculates a motion parameter of the healthy person based on the healthy person vector data 153 of one or more healthy persons, and saves it as the healthy person motion parameter data 193 in the motion parameter data storage unit 19. (S47). Furthermore, the healthy person data processing unit 18 generates average healthy person motion parameter data 195 and stores it in the motion parameter data storage unit 19. Note that either step S45 or step S47 may be performed first.

  Based on the patient motion parameter data 191 stored in the motion parameter data storage unit 19, the polar map generation unit 21 generates a patient polar map reflecting the motion parameters (S49). The polar map generation unit 21 further generates a polar map of the healthy person reflecting the motion parameters based on the motion parameter data 195 of the healthy person stored in the movement parameter data storage unit 19 (S51). Either step S49 or step S51 may be performed first.

  And the display control part 23 displays the polar map of a patient and a healthy person on the display apparatus 5 (S53). Furthermore, the display control unit 23 displays the movement parameters of the patient and the healthy person on the display device 5 (S55). The polar map display in step S53 and the motion parameter display in step S55 may be performed simultaneously as described above, or only one of them may be performed.

  Thereby, comparison between subjects, such as comparing a patient and a healthy person, can be easily performed by a motion parameter indicating a feature of heart motion extracted from an ECG-synchronized SPECT image.

  The above-described embodiments of the present invention are examples for explaining the present invention, and are not intended to limit the scope of the present invention only to those embodiments. Those skilled in the art can implement the present invention in various other modes without departing from the gist of the present invention.

  For example, in the above-described embodiment, an example in which various motion parameters are calculated for each voxel has been described. However, a motion parameter may be calculated for each region configured by a plurality of voxels. The region composed of a plurality of voxels may be determined in advance in the reference phase image, for example, or the operator performs a predetermined input operation on the reference phase image or any one of the phase images using the input device 3. You may specify by doing. The movement trajectory of each region may be obtained, for example, by obtaining an average vector obtained by averaging voxel vectors in the region for each motion vector group and connecting the average vectors. The processing after the movement locus is calculated is the same as the processing for each voxel.

DESCRIPTION OF SYMBOLS 1 Image reconstruction system 10 Image processing apparatus main body 11 Data storage part 13 Vector calculation part 15 Vector data storage part 17 Motion parameter calculation part 19 Motion parameter data storage part 21 Polar map generation part 23 Display control part 100 SPECT image processing apparatus 171 Movement Trajectory extraction unit 173 Maximum movement calculation unit 175 Maximum change calculation unit

Claims (11)

Storage means for storing electrocardiogram-synchronized volume data composed of volume data of a plurality of phases, which is taken by dividing one cycle of the heartbeat into a plurality of times in synchronization with the electrocardiogram;
Motion vector calculation means for calculating a plurality of motion vector groups indicating heart motion between phases using volume data of a plurality of phases stored in the storage means;
A volume data processing apparatus comprising: a motion parameter calculation unit that analyzes a motion for each predetermined region based on the motion vector group calculated by the motion vector calculation unit and calculates a motion parameter indicating a feature of the heart motion. When one of the plurality of phase volume data is set as reference phase volume data, each voxel on the reference phase volume data is set as the predetermined area, and each voxel on the reference phase volume data is set as a reference voxel. ,
The motion parameter calculation means uses the motion vector group to identify a movement trajectory over one period of the heartbeat of each reference voxel, and calculates the motion parameter for each reference voxel based on the movement trajectory of the reference voxel. The volume data processing apparatus according to claim 1.   The volume data processing apparatus according to claim 2, wherein the movement parameter is a maximum movement amount indicating a distance from a position in the reference phase volume data serving as a starting point to a position farthest from the movement locus.   4. The volume data processing device according to claim 2, wherein the movement parameter is a maximum movement phase indicating a phase when the movement locus reaches a position farthest from a position in the reference phase volume data serving as a starting point. 5. .   Based on the volume data of any one phase and the motion parameter of the predetermined area, image display means for displaying an image using the motion parameter of the predetermined area instead of the voxel value of the volume data of the one phase, The volume data processing apparatus according to claim 1, further comprising: The storage means stores volume data of a first subject and volume data of one or more second subjects,
The motion vector calculation means calculates a motion vector group between phases for each of the volume data of the first subject and one or more second subjects,
The movement parameter calculation means calculates the movement parameters of the first subject and the one or more second subjects, respectively.
The volume data processing apparatus according to claim 5, wherein the image display unit displays each image based on the movement parameter of the first subject and the movement parameter of the one or more second subjects.   4. The volume data processing apparatus according to claim 3, further comprising an image display means for displaying an image corresponding to the volume data of any one phase in a display mode corresponding to the maximum movement amount of each voxel for any subject. .   The volume data processing device according to claim 1, wherein the motion vector calculation unit calculates the motion vector group based on a density gradient between volume data of two phases adjacent to each other.   The volume data processing apparatus according to claim 1, wherein the volume data is SPECT (Single Photo Emission Computed Tomography) image data. A method performed by a volume data processing apparatus having storage means for storing electrocardiogram-synchronized volume data consisting of volume data of a plurality of phases, which is taken by dividing one cycle of a heartbeat into a plurality of times in synchronization with an electrocardiogram,
Using a plurality of phase volume data stored in the storage means to calculate a plurality of motion vector groups indicating heart motion between phases;
Analyzing the movement of each predetermined region based on the calculated motion vector group, and calculating a motion parameter indicating the feature of the heart motion. A computer program for a volume data processing apparatus having storage means for storing electrocardiogram-synchronized volume data consisting of volume data of a plurality of phases, which is taken by dividing one cycle of a heartbeat into a plurality of times in synchronization with an electrocardiogram,
Using a plurality of phase volume data stored in the storage means to calculate a plurality of motion vector groups indicating heart motion between phases;
A computer program for causing the volume data processing device to execute a step of analyzing a motion for each predetermined region based on the calculated motion vector group and calculating a motion parameter indicating a feature of heart motion.