JP2018069022A - Medical image processing apparatus and medical image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a medical image processing apparatus and a medical image processing method which can easily acquire functional classification of functional areas corresponding to nerve fiber bundles.SOLUTION: A medical image processing apparatus comprises an extraction unit, a first transfer unit, an analysis unit, and a second transfer unit. The extraction unit extracts position information of a nerve distribution from subject data. The first transfer unit transfers a subject nerve area based on the extracted position information to atlas data. The analysis unit analyzes a positional relation between a functional area in a brain and the transferred subject nerve area in the atlas data. The second transfer unit transfers an analysis result by the analysis unit to the subject data.SELECTED DRAWING: Figure 1

Description

  Embodiments described herein relate generally to a medical image processing apparatus and a medical image processing method.

  In recent years, with the development of image recognition technology, a technique for analyzing the positional relationship between a nerve fiber bundle captured in a medical image and an affected area has attracted attention.

  Many brain diseases affect the deformation of white matter fibers and may cause deformations such as, for example, blocked, infiltration, or extrusion. Knowing these changes can provide useful information for neurosurgery. In particular, in the case of infiltration, the extent of resection is closely related to the prognosis. In fact, highly invasive lesions can significantly change morphology and damage the function of infiltrated white matter fibers, while less invasive tumors may only need to extrude surrounding brain tissue. These different situations influence the establishment of a surgical policy. Therefore, by accurately determining the positional relationship between the white matter fibers having different functions and the affected part, it contributes to finding an optimal method that strikes a balance between the extent of tissue resection and the maintenance of brain function as much as possible.

  When planning a tumor surgery, the physician needs to segment the function of the nerve fiber bundles involved. Tracking nerve fiber bundles can provide information about this point.

  The prior art discloses a method for classifying the functions of nerve fiber bundles. For example, in Patent Document 1, first, after determining the nerve fiber bundle that has penetrated the affected area, the reaching point in the brain region of the nerve fiber bundle that has penetrated the affected area is specified, and using the functional area template of the cerebral cortex, It is disclosed that a possible influence on a subject is predicted by determining a functional region of the cerebral cortex that is connected to a reaching point of a nerve fiber bundle.

  However, this analysis method can only be used to detect affected fiber bundles that have penetrated the affected area, and cannot detect affected fiber bundles that have been extruded but not penetrated the affected area. In addition, using this analysis method, it is only possible to predict the functional classification of the affected fiber bundle, showing the connection relationship between the fiber bundle and the cerebral cortical segment, and the actual form and position of the affected fiber bundle. It is impossible to extract and display.

  Further, in the conventional document 2, selection is made based on a collection of nerve fiber bundles extracted by the nerve fiber bundle tracking unit and a region of interest (also referred to as a ROI (Region of Interest) or seed region) of the nerve fiber bundle. A nerve fiber bundle extraction method is disclosed in which a specific nerve fiber bundle set is determined by performing a logical operation with the set of nerve fiber bundles. This set is a set of fiber bundles that penetrate a certain region of interest and anisotropy exceeds a predetermined threshold value. However, these sets of fiber bundles have only positional correlation and are functional. Since there is no correlation, it is impossible to know the functional classification of the fiber bundle while extracting the fiber bundle.

  Further, in the conventional technique, the region of interest is usually acquired using the result of magnetic resonance imaging (BOLD-fMRI) of the blood oxygen level dependent function, thereby tracking the fiber bundle. Of these, it is not only necessary to obtain magnetic resonance imaging results of blood oxygen level dependent function, but it is not easy to obtain high quality magnetic resonance imaging results of blood oxygen level dependent function in actual operation .

JP 2012-235934 A JP 2012-66005 A

  The problem to be solved by the present invention is to provide a medical image processing apparatus and a medical image processing method capable of easily acquiring the functional classification of the functional area corresponding to the nerve fiber bundle.

  The medical image processing apparatus according to the embodiment includes an extraction unit, a first transfer unit, an analysis unit, and a second transfer unit. The extraction unit extracts position information of nerve distribution from the subject data. The first transfer unit transfers the subject nerve region based on the extracted position information to the atlas data. The analysis unit analyzes the positional relationship between the functional region in the brain in the atlas data and the transferred subject nerve region. The second transfer unit transfers the analysis result by the analysis unit to the subject data.

FIG. 1 is a block diagram showing the configuration of the medical image processing apparatus according to the first embodiment. FIG. 2 is a diagram showing functional fiber bundles included in the fiber bundle atlas. FIG. 3 is a schematic diagram showing the correspondence between the corpus callosum fiber bundle and the region of interest in the fiber bundle atlas. FIG. 4 is a schematic diagram showing the correspondence between the corticospinal tract and the region of interest in the fiber bundle atlas. FIG. 5 is a flowchart showing image processing steps according to the first embodiment. FIG. 6 is a schematic diagram illustrating image processing according to the first embodiment. FIG. 7 is a block diagram illustrating a configuration of a medical image processing apparatus according to the second embodiment. FIG. 8 is a flowchart showing image processing steps according to the second embodiment. FIG. 9 is a schematic diagram illustrating image processing according to the second embodiment. FIG. 10 is a schematic diagram for specifying a fiber bundle that is affected when the fiber bundle is pushed out in an affected area according to the third embodiment. FIG. 11 is a flowchart showing image processing steps according to the third embodiment. FIG. 12 is a block diagram illustrating a configuration of a medical image processing apparatus according to the fourth embodiment. FIG. 13 is a schematic diagram for analyzing the damage index of the functional fiber bundle according to the fourth embodiment. FIG. 14 is a flowchart illustrating image processing steps according to the fourth embodiment. FIG. 15 is a schematic diagram of a screen that simultaneously displays a damage index and subject data.

  Embodiments relate to a medical image processing apparatus that processes medical images. This medical image processing apparatus is realized by executing software having each function of the medical image processing apparatus in equipment having a CPU (Central Process Unit) such as an independent computer connected to an image acquisition apparatus such as an X-ray apparatus. Alternatively, it may be realized in the form of hardware as a circuit capable of executing each function of the medical image processing apparatus. In addition, the medical image processing apparatus according to the embodiment may be incorporated in advance in the above-described medical image collection apparatus as a part of a medical image collection apparatus such as a CT apparatus or an ultrasonic apparatus.

  Hereinafter, preferred embodiments will be described in detail with reference to the drawings. The embodiment is merely an example, and is not limited to the configuration represented in the embodiment.

  Hereinafter, a brain region will be described as an example, but the embodiment is not limited to the brain region, and can also be applied to image processing for other regions.

(First embodiment)
FIG. 1 is a block diagram showing the configuration of the medical image processing apparatus according to the first embodiment.

  As shown in FIG. 1, the medical image processing apparatus 100 includes an extraction unit 101, a first transfer unit 102, an analysis unit 103, a second transfer unit 104, a display processing unit 105, and an index display unit 106. Prepare.

  The extraction unit 101 extracts nerve distribution position information from the subject data. The subject data includes a fiber bundle image. The fiber bundle image is a nerve fiber image related to a nerve fiber bundle in the brain of the subject. The fiber bundle image is generated, for example, by applying a fiber bundle tracking technique to a diffusion tensor image generated by imaging the brain of a subject. In the diffusion tensor imaging technique, it is possible to evaluate the integrity of white matter fiber bundles by imaging the diffusion characteristics of water molecules. Currently, diffusion tensor imaging technology and fiber bundle tracking technology are used to display specific fiber bundles in vivo.

  The first transfer unit 102 can transfer the fiber bundle image in the subject data to a predefined fiber bundle atlas. That is, the first transfer unit 102 transfers the subject nerve region based on the position information of the nerve distribution extracted from the fiber bundle image to the fiber bundle atlas (atlas data).

  The information defined in advance in the fiber bundle atlas includes standardized nerve region information and functional region information associated with each nerve region. Among them, the nerve region is a region corresponding to a nerve fiber bundle, the functional region may be called a region of interest, a region corresponding to a brain function (for example, a visual function region on the cerebral cortex, a motor function region, etc.), Or it is an area | region according to the tissue structure (for example, an internal capsule, a cerebral leg, etc.) in a brain. The functional area may be manually selected by an operator of the device or may be automatically selected by the device. The correspondence relationship between the nerve region and the functional region in the fiber bundle atlas will be described later.

  The nerve fiber bundle in this embodiment is a fiber bundle marked by the functional classification of the fiber bundle, that is, a functional fiber bundle. FIG. 2 is a schematic diagram showing functional fiber bundles predefined in the fiber bundle atlas. In Fig. 2, the corpus callosum (CC) fiber bundle that connects the left and right hemispheres, the cortico spinal tract (CST) that connects the motor cortex and the spinal cord, the motor cortex and the spinal cord are connected Longitudinal bundle (superior longitudinal fasciculus: SLF), cerebral arch (fornix: FORX) connecting the hippocampus and hypothalamic nucleus, inferior longitudinal fasciculus (ILF), parahippocampal cingulum (PHC), saddle shape Functional fiber bundles including bundles (uncinate fasciculus: UNC), inferior occipitofrontal fasciculus (IOFF or IFOF) and the like are shown.

  The fiber bundle atlas needs to be completely created before the transfer by the first transfer unit 102 is started. This fiber bundle atlas may be an atlas defined in advance and stored in the extraction unit 101, an atlas introduced into the medical image processing apparatus before the transfer by the first transfer unit 102, or according to the embodiment. An atlas generated by a medical image processing apparatus may be used.

  Further, in the process of transferring the fiber bundle image from the subject to the fiber bundle atlas, the first transfer unit 102 generally performs image registration (hereinafter referred to as “registration”) for the fiber bundle image from the subject. (Abbreviated) is transferred to the fiber bundle atlas. Specifically, image registration is performed on the fiber bundle image from the subject and the image in the fiber bundle atlas using a conventional registration method, and the fiber bundle image and the fiber bundle of the subject are obtained as a result of the image registration. A transfer matrix with the atlas is generated, and based on this transfer matrix, a part or all of the fiber bundle image of the subject is transferred to a predefined fiber bundle atlas.

  The analysis unit 103 analyzes the positional relationship between the functional region in the brain in the fiber bundle atlas and the subject nerve fiber bundle transferred to the fiber bundle atlas (that is, the transferred subject nerve region).

  Specifically, each functional fiber bundle of the subject transferred to the fiber bundle atlas is identified (recognized) based on the transcription matrix, and then the functional fiber bundle defined in the fiber bundle atlas and the region of interest are defined. Based on the correspondence relationship, the region of interest associated with the functional fiber bundle of the specified subject is acquired as the analysis result.

  The second transfer unit 104 transfers the analysis result from the analysis unit 103 to the subject data. For example, the second transfer unit 104 transfers the region of interest acquired by the analysis unit 103 to the subject data. Specifically, the region of interest acquired by the analysis unit 103 is transferred to the image of the subject data using the transfer matrix generated before that.

  The display processing unit 105 simultaneously displays a fiber bundle image of the subject and a region of interest corresponding to each fiber bundle on a display device (for example, a display). In addition, it is preferable that the regions of interest corresponding to the different functional fiber bundles are represented by different colors or different gray scales, so that the operator can more intuitively understand the functional section of the region of interest.

  Further, the display processing unit 105 can further classify various functional fiber bundles from the subject data using the fiber bundle tracking technique based on the region of interest corresponding to each functional fiber bundle. When displaying a fiber bundle image of a subject, it is preferable to represent different functional fiber bundles and corresponding regions of interest in different colors or different gray scales, so that the operator can more intuitively identify the functional compartment of each fiber bundle. It becomes possible to grasp it.

  However, in the case of the medical image processing apparatus 100, the display processing unit 105 is not indispensable. The display processing unit 105 may be provided in an external device other than the medical image processing apparatus 100. As a result, the processing result by the medical image processing apparatus 100 may be output by another method without displaying.

  Hereinafter, the correspondence between the nerve region and the functional region in the fiber bundle atlas will be described with reference to FIGS. 3 and 4.

  FIG. 3 is a schematic diagram showing the correspondence between the corpus callosum fiber bundle and the region of interest in the fiber bundle atlas. In the upper left part of FIG. 3, a plurality of functional fiber bundles predefined in the atlas are shown. In the lower left part of FIG. 3, three regions of interest are shown, depending on the corpus callosum fiber bundle, on a particular anatomical location. In the right part of FIG. 3, a form in which the corpus callosum fiber bundle and three regions of interest are displayed simultaneously is shown. In FIG. 3, there are three regions of interest for specifying the corpus callosum, and there is a logical relationship of “OR” between the three regions of interest, that is, a fiber bundle penetrating one of these three regions of interest. Identified as a corpus callosum fiber bundle.

  FIG. 4 is a schematic diagram showing the correspondence between the corticospinal tract and the region of interest. In the figure, the corticospinal tract and four regions of interest for identifying the corticospinal tract are shown. As shown in the figure, all of the corticospinal tract penetrates the region of interest 1 (central posterior rotation) and the region of interest 2 (inner hind leg). And penetrates the region of interest 3 (the forebrain bridge) and the region of interest 4 (the hindbrain), respectively. Therefore, the logical relationship between several regions of interest for specifying the corticospinal tract becomes “SD1 & SD2 & (SD3 or SD4)” (SD represents the region of interest). In other words, a functional fiber bundle that penetrates SD1 and SD2 and penetrates SD3 or SD4 can be identified as the corticospinal tract. In addition, the affected part in FIG. 4 is a tumor etc., for example.

  In FIG. 3 and FIG. 4, a method of specifying each region of interest of the corpus callosum fiber bundle and corticospinal tract and a logical relationship between each region of interest are shown. In addition to the corpus callosum fiber bundle and corticospinal tract, There are other functional fiber bundles in the brain, and a region of interest for uniquely identifying these functional fiber bundles and a logical relationship between the regions of interest are defined in the fiber bundle atlas. The number of regions of interest in each functional fiber bundle and the logical relationship that exists between the regions of interest are different.

  Next, an image processing process according to the first embodiment will be described with reference to FIGS. FIG. 5 is a flowchart showing image processing steps according to the first embodiment. FIG. 6 is a schematic diagram illustrating image processing according to the first embodiment.

  Although the actual subject data includes a plurality of subject fiber bundles, only the image processing process for one nerve fiber bundle is illustrated in FIG. 6 for the sake of simplicity. In addition, actual image processing may be processing for a three-dimensional image, but in order to simplify the description, description will be made using only a two-dimensional planar image.

  First, in step S101, the extraction unit 101 extracts position information of the subject fiber bundle X1 from the subject data. The position information is composed of coordinate information of a plurality of points in the three-dimensional nerve fiber bundle, and the density and number of points may be preset by the operator as necessary. In the upper left part of FIG. 6, a subject fiber bundle X1 from which position information is extracted is shown. This subject fiber bundle X1 is composed of eight nerve fibers.

  The subject data may be stored in advance in a storage unit (not shown) or an external storage device, or the subject's brain is imaged by a medical imaging device, and the subject's brain is captured by a fiber bundle tracking technology, a medical image diagnostic technology, or the like. The subject data including the fiber bundle image related to the nerve fiber bundle may be acquired.

  Next, in step S102, the subject fiber bundle X1 based on the extracted position information is transferred to the fiber bundle atlas (atlas data) by the first transfer unit 102.

  Before transcription, the fiber bundle atlas on the right side of FIG. 6 includes a fiber bundle X1 ', and further includes a region of interest A and a region of interest B corresponding to this fiber bundle X1'. The fiber bundle X1 'is composed of ten nerve fibers connected between the region of interest A and the region of interest B.

  The generation of the fiber bundle atlas (that is, the specification of the region of interest, the specification of the logical relationship between the plurality of regions of interest, the specification of the functional fiber bundle) may be completed before the transfer by the first transfer unit 102. It may be before S101 or after S101. Of course, a fiber bundle atlas template may be generated in advance and stored in a storage unit (not shown) or an external storage device, and this template may be applied each time it is used.

  In step S102, the subject fiber bundle X1 from the subject is transferred to the fiber bundle atlas using a transfer matrix by registration. In FIG. 6, the fiber bundle X1 'defined in advance in the fiber bundle atlas is represented by a solid line, and the subject fiber bundle X1 transferred to the fiber bundle atlas is represented by a dotted line.

  In step S103, the analysis unit 103 analyzes the positional relationship between the region of interest A and the region of interest B in the fiber bundle atlas and the subject fiber bundle X1 transferred to the fiber bundle atlas. In the fiber bundle atlas, the correspondence relationship between the fiber bundle X1 ′ and the region of interest A and the region of interest B is defined in advance. That is, the fiber bundle X1 ′ is a fiber bundle connected between the region of interest A and the region of interest B. It is. Therefore, the region of interest A and the region of interest B corresponding to the subject fiber bundle X1 are acquired as analysis results.

  In step S104, the second transfer unit 104 transfers the analysis result obtained by the analysis unit 103 to the subject data. That is, as shown in the lower left part of FIG. 6, the region of interest A and the region of interest B corresponding to the subject fiber bundle X1 are transferred to the subject data.

  Further, in step S105, the display processing unit 105 displays subject data including the region of interest A and the region of interest B. Of course, the display step S105 may be omitted for a medical image processing apparatus that performs only medical image processing.

  The process ends.

  According to the image processing according to the first embodiment, it is possible to acquire a region of interest corresponding to the subject fiber bundle from the fiber bundle atlas without using the result of magnetic resonance imaging of the blood oxygen level dependent function. In addition, the region of interest in the fiber bundle atlas is pre-defined standardized data, which is obtained by this embodiment compared to the case of magnetic resonance imaging results of high-quality blood oxygen level-dependent functions that are difficult to obtain in actual operation. The area of interest is highly reliable.

  In addition, the first transfer unit 102 in the first embodiment may perform only image registration without transferring the fiber bundle image in the subject data to a predefined fiber bundle atlas. Each function of the subject according to each functional fiber bundle in the fiber bundle atlas using a transfer matrix by image registration without transferring the fiber bundle image in the subject data to the predefined fiber bundle atlas. This is because the fiber bundle can be identified (recognized).

  Further, the index display unit 106 according to the first embodiment calculates and displays a damage index due to an affected part such as a tumor for a subject fiber bundle (subject nerve region) in the subject data. Hereinafter, this point will be described with reference to FIG.

  For example, after the first transfer unit 102 has transferred the subject nerve region in the subject data to the fiber bundle atlas, the analysis unit 103 has the region of interest in the fiber bundle atlas and the subject nerve region transferred to the fiber bundle atlas. Analyze the positional relationship of. For example, the analysis unit 103 analyzes the positional relationship between the region of interest A or region B in the fiber bundle atlas and the transferred subject fiber bundle X1 as shown in the right diagram of FIG. Region of interest A and region of interest B corresponding to the transferred subject fiber bundle X1. Furthermore, the analysis unit 103 acquires a nerve region associated with the acquired function region based on the correspondence relationship between the region of interest and the nerve region defined in the fiber bundle atlas. For example, the analysis unit 103 acquires the fiber bundle X1 ′ as a nerve region associated with the region of interest A and the region of interest B acquired based on the positional relationship with the subject fiber bundle X1.

  Then, the index display unit 106 calculates a damage index by comparing the subject nerve region transferred to the fiber bundle atlas and the nerve region acquired by the analysis unit 103. For example, the index display unit 106 compares the subject fiber bundle X1 transferred to the fiber bundle atlas with the fiber bundle X1 ′ acquired by the analysis unit 103, thereby obtaining statistical information on the subject nerve region as a damage index. Is calculated.

  Here, as the statistical information calculated by the index display unit 106, for example, among functional fiber bundles related to the region of interest, functional fiber bundles that can be used before surgery (for example, usable at the time when subject data is acquired) (Functional Rate) representing the ratio occupied by the functional fiber bundle). For example, in the atlas data shown in FIG. 6, the fiber bundle X1 ′ relating to the region of interest A and the region of interest B is composed of 10 nerve fibers, and the subject fiber bundle X1 usable before the operation is 8 Since it consists of nerve fibers, the index display unit 106 can calculate and display the usage rate “80% (8/10)” as the statistical information of the subject nerve region.

(Second Embodiment)
The second embodiment is a modification of the first embodiment. The difference between the first embodiment and the second embodiment is that the medical image processing apparatus 200 further processes the tumor image in the subject data to identify the subject nerve fiber bundle affected by the tumor. There is to display. In the present embodiment, a tumor is described as an example of an affected part, but the actual affected part may be other cases such as a traumatism or a clotsamentum.

  The extraction unit 201, the first transfer unit 202, the analysis unit 203, the second transfer unit 204, the display processing unit 205, and the index display unit 206 in the medical image processing apparatus 200 according to the second embodiment are extracted in the first embodiment. Compared with the unit 101, the first transfer unit 102, the analysis unit 103, the second transfer unit 104, the display processing unit 105, and the index display unit 106, an additional function is exhibited. Hereinafter, differences between the second embodiment and the first embodiment will be mainly described, and overlapping descriptions will be appropriately omitted.

  FIG. 7 is a block diagram illustrating a configuration of a medical image processing apparatus according to the second embodiment.

  As illustrated in FIG. 7, the medical image processing apparatus 200 includes an extraction unit 201, a first transfer unit 202, an analysis unit 203, a second transfer unit 204, a display processing unit 205, and an index display unit 206. Prepare.

  In addition to extracting the position information of the nerve distribution from the subject data, the extracting unit 201 further extracts information on the affected area (for example, a tumor region) from the subject data. The subject data further includes a brain image. The brain image may be obtained by imaging the brain of a subject with a medical image diagnostic apparatus such as a magnetic resonance imaging apparatus, an X-ray computed tomography apparatus, an X-ray diagnostic apparatus, or a nuclear medicine diagnostic apparatus. When a tumor exists in the subject's brain, the tumor appears on the brain image. A position where a tumor is present is referred to as a tumor area.

  The first transfer unit 202 is included in the brain image in addition to transferring the fiber bundle image from the subject to the predefined fiber bundle atlas as compared to the first transfer unit 102 in the first embodiment. The tumor area is also transcribed further into the fiber bundle atlas. Here, the transferred tumor region may be a volume data image including a tumor inner region, or may be a three-dimensional image of a tumor contour from which a tumor contour is extracted.

  Specifically, the first transfer unit 202 first obtains a transfer matrix between the fiber bundle image of the subject and the fiber bundle atlas by performing image registration. Thereafter, using this transcription matrix, the tumor region of the subject is also transferred to the fiber bundle atlas. In the second embodiment, as in the first embodiment, the first transfer unit 202 may not transfer the fiber bundle image in the subject data to the fiber bundle atlas.

  The analysis unit 203 analyzes the positional relationship between the region of interest in the fiber bundle atlas, the fiber bundle in the fiber bundle atlas, and the tumor region transferred to the fiber bundle atlas. Specifically, the analysis unit 203 detects the fiber bundle affected by the tumor region based on the positional relationship between the fiber bundle in the fiber bundle atlas and the tumor region transferred to the fiber bundle atlas, and the fiber bundle atlas. The region of interest associated with the detected subject fiber bundle is acquired as an analysis result based on the correspondence relationship between the region of interest and the nerve region defined in (1).

  The second transfer unit 204 transfers the analysis result by the analysis unit 203 to the subject data. That is, the region of interest associated with the fiber bundle affected by the detected tumor region is transferred to the subject data.

  Further, the second transfer unit 204 does not transfer all the fiber bundles affected by the tumor region to the subject data, but transfers only the region of interest to the subject data. This is because the overall registration of fiber bundles is difficult, and the transfer difficulty can be reduced by transferring only the region of interest compared to the case of transferring all the fiber bundles. This is because the accuracy and efficiency can be further improved.

  The display processing unit 205 displays the subject fiber bundle affected by the tumor region. For example, based on the correspondence between the region of interest and the fiber bundle, the analysis unit 203 first selects a subject fiber bundle affected by the tumor region from the region of interest transferred to the subject data in the subject data. Then, the display processing unit 205 displays the detected subject fiber bundle. Specifically, the analysis unit 203 analyzes a subject fiber bundle that penetrates each region of interest in the subject data using the transferred region of interest based on each region of interest and the logical relationship between them. Thus, the actual position of each affected subject fiber bundle is detected and displayed.

  The analysis unit 203 further identifies each functional fiber bundle from the subject data using a fiber bundle tracking technique based on the region of interest corresponding to each functional fiber bundle, and the display processing unit 205 identifies Functionalized fiber bundles can be displayed.

  There are many methods for displaying the affected subject fiber bundle. For example, only the affected subject fiber bundle may be displayed, or the affected subject fiber bundle may be emphasized while displaying all the fiber bundles of the subject.

  The image processing process according to the second embodiment will be described below with reference to FIGS. FIG. 8 is a flowchart showing image processing steps according to the second embodiment. FIG. 9 is a schematic diagram illustrating image processing according to the second embodiment.

  First, in step S201, in addition to extracting the position information of the subject fiber bundle from the subject data, the extraction unit 201 further extracts a tumor region that is the position information of the tumor. In the upper left part of FIG. 8, the subject fiber bundle X1, the subject fiber bundle X2, and one tumor region C that is substantially elliptical from which position information is extracted are shown.

  In FIG. 8, for convenience of display, the subject fiber bundles X1 and X2 and the tumor region C are displayed together. As described above, the subject fiber bundles X1 and X2 are extracted from the fiber bundle image in the subject data. The tumor region C is extracted from the brain image of the subject data.

  In the present embodiment, the tumor region is expressed using the outline of the tumor, and the tumor region is transferred.

  Next, in step S202, the subject fiber bundles X1, X2 and the tumor region C based on the extracted position information are transferred to the fiber bundle atlas by the first transfer unit 202.

  Prior to transcription, the fiber bundle atlas on the right side of FIG. 9 includes the fiber bundles X1 ′ and X2 ′, the region of interest A and the region of interest B corresponding to the fiber bundle X1 ′, and the fiber bundle X2 ′. A region of interest D and a region of interest E are also included. The fiber bundle X1 ′ is composed of three nerve fibers connected between the region A and the region B on the left side, and the fiber bundle X2 ′ is connected between the region D and the region E on the right side. It consists of three nerve fibers.

  Further, in step S202, the subject fiber bundles X1 and X2 from the subject are transferred to the fiber bundle atlas using the registration transfer matrix, and the tumor region C is transferred to the fiber bundle atlas. In FIG. 9, the subject fiber bundles X1, X2, and the subject fiber bundles X1, X2 transferred to the fiber bundle atlas so as to be separated from the fiber bundles X1 ′, X2 ′ and the regions of interest A, B, D, E defined in the fiber bundle atlas. Tumor region C is represented by a dotted line.

  In step S203, the analysis unit 203 determines the positional relationship between the regions of interest A, B, D, and E in the fiber bundle atlas, the fiber bundles X1 ′ and X2 ′ in the fiber bundle atlas, and the tumor region C transferred to the fiber bundle atlas. To analyze. Specifically, as shown by the positional relationship between the fiber bundles X1 ′, X2 ′ included in the fiber bundle atlas and the tumor region C transferred to the fiber bundle atlas, one nerve in the fiber bundle X1 ′ Since the fibers enter the tumor region C and no nerve fibers in the fiber bundle X2 ′ enter the tumor region C, the fiber bundle affected by the tumor region becomes the fiber bundle X1 ′. Thereafter, the analysis unit 203 associates the region of interest defined in the fiber bundle atlas with the nerve region (in FIG. 9, the relationship between the fiber bundle X1 ′ and the regions of interest A and B is that the fiber bundle X1 ′ is the region of interest A The region of interest A and the region of interest B associated with the detected fiber bundle X1 ′ are acquired as analysis results.

  In step S204, the second transfer unit 204 transfers the analysis result by the analysis unit 203 to the subject data. That is, as shown in the lower left part of FIG. 9, the region of interest A and the region of interest B associated with the fiber bundle X1 'affected by the detected tumor region are transferred to the subject data.

  Furthermore, in step S205, the display processing unit 205 displays subject data including the region of interest A and the region of interest B.

  Specifically, since the logical relationship between the regions of interest A and B and the fiber bundle X1 is that the fiber bundle X1 is connected between the regions of interest A and B, the region of interest to which the analysis unit 203 has been transcribed. Based on A and B, the subject affected by analyzing the fiber bundle connecting the region of interest A and the region of interest B with the subject fiber bundle X1 from the subject data using the fiber bundle tracking technique. The actual position of the fiber bundle X1 is detected. The display processing unit 205 displays the actual position of the detected subject fiber bundle X1.

  Here, it is preferable to display the subject fiber bundle X1 affected by the tumor region C so as to be emphasized. For example, the subject fiber bundle X1 in FIG. 9 is displayed with a thick line, so that the operator can more intuitively understand the functional section of each fiber bundle.

  In the present embodiment, after the affected functional fiber bundle is identified by the second transfer unit 204, the medical image processing apparatus 200 converts each region of interest associated with the functional fiber bundle to the subject data. The analysis unit 203 analyzes the fiber bundles that have been transcribed and penetrated through these regions of interest, thereby knowing the actual positions of the affected functional fiber bundles in the subject.

  By using such a configuration, if you want to display the subject fiber bundle affected by the tumor region, only the region of interest corresponding to it without transferring the entire subject fiber bundle in the fiber bundle atlas to the subject data Can be transferred to the subject data, so that the efficiency and accuracy of the transfer can be improved. Further, by displaying the actual position of the functional fiber bundle affected by the subject data in the subject, a surgical operation or the like can be made convenient. That is, according to the medical image processing apparatus 200 according to the second embodiment, in addition to simply obtaining the functional classification of the functional region corresponding to the nerve fiber bundle, it is possible to accurately know the affected fiber bundle. The actual position of the affected fiber bundle in the subject can be accurately and easily identified.

  As a modification of the second embodiment, in step S205, the display processing unit 205 does not detect or emphasize the subject fiber bundle X1, and the region of interest according to the affected subject fiber bundle X1. Only A and the region of interest B may be displayed. As a result, the operator can intuitively view the region of interest corresponding to the affected subject fiber bundle, and can largely estimate the affected subject fiber bundle. Can be convenient.

  In addition, the index display unit 206 in the second embodiment calculates and displays a damage index due to a tumor region. Hereinafter, this point will be described with reference to FIG.

  For example, after the first transfer unit 202 transfers the tumor region in the subject data to the fiber bundle atlas, the analysis unit 203 transfers the region of interest in the fiber bundle atlas, the nerve region in the fiber bundle atlas, and the fiber bundle atlas. The positional relationship with the tumor area is analyzed. For example, the analysis unit 203 first analyzes the positional relationship between the fiber bundle X1 ′ or fiber bundle X2 ′ in the fiber bundle atlas and the transferred tumor region C as shown in the right diagram of FIG. The fiber bundle X1 ′ affected by the region C is detected. Next, the analysis unit 203 detects the detected fiber bundle X1 among the regions of interest A, B, D, and E in the fiber bundle atlas based on the correspondence between the region of interest and the nerve region defined in the fiber bundle atlas. The region of interest A and the region of interest B associated with 'are acquired.

  Next, the analysis unit 203 identifies the subject nerve region affected by the tumor region based on the acquired functional region. For example, after the region of interest A and the region of interest B are transferred to the subject data by the second transfer unit 204, the analysis unit 203 connects the region of interest A and the region of interest B among the subject neural regions in the subject data. The subject fiber bundle X1 is detected. That is, the analysis unit 203 detects the subject fiber bundle X1 having the same logical relationship as that of the fiber bundle X1 'affected by the tumor region (connecting the regions of interest A and B).

  Then, the index display unit 206 calculates the damage index by comparing the subject nerve region detected by the analysis unit 203 with the nerve region affected by the affected region. For example, the index display unit 206 compares the subject fiber bundle X1 detected by the analysis unit 203 with the fiber bundle X1 ′ affected by the tumor region C, so that the statistics of the subject nerve region can be used as a damage indicator. Calculate information. In the following, a case where the tumor region C shown in FIG. 9 includes a tumor and a tumor infiltration region around the tumor will be described.

  For example, the statistical information calculated by the index display unit 206 includes an extrusion rate, penetration rate, infiltration rate, damage rate, usage rate, and the like of the nerve region. It is done. For example, the statistical information calculated by the index display unit 206 is at least one of the extrusion rate, penetration rate, infiltration rate, destruction rate, and usage rate of the nerve region.

  The extrusion rate represents the ratio of the extruded fiber bundle to the functional fiber bundle related to the region of interest. As an example, in FIG. 9, one nerve fiber out of the three fiber bundles X1 'penetrates the tumor region C. On the other hand, the subject fiber bundle X1 does not penetrate the tumor region C, and it can be said that one nerve fiber of the subject fiber bundle X1 is pushed out by the tumor region C and displaced to the left. Therefore, the index display unit 206 can calculate the extrusion rate “33% (1/3)” as the statistical information of the subject nerve region.

  The penetration rate represents the ratio occupied by the penetration fiber bundle in the functional fiber bundle related to the region of interest. For example, in FIG. 9, since there is no penetrating fiber bundle (the nerve fiber that penetrates the tumor infiltrating region and tumor in the subject fiber bundle X1), the index display unit 206 displays statistical information on the subject nerve region. The penetration rate “0% (0/3)” can be calculated.

  The infiltration rate represents the proportion of the functional fiber bundle related to the region of interest occupied by the infiltrating fiber bundle. For example, in FIG. 9, since there is no infiltrating fiber bundle (the nerve fiber that penetrates the tumor infiltrating region and does not penetrate the tumor in the subject fiber bundle X1), the index display unit 206 displays The infiltration rate “0% (0/3)” can be calculated as the statistical information of the sample nerve region.

  The destruction rate represents the ratio of the functional fiber bundle related to the region of interest occupied by the functional fiber bundle destroyed by surgery. For example, in FIG. 9, nerve fibers in the subject fiber bundle X1 are not destroyed even if the tumor region C is excised regardless of whether the tumor is excised or whether the tumor and the tumor infiltrating area are excised. Therefore, the index display unit 206 can calculate the destruction rate “0% (0/3)” as the statistical information of the subject nerve region.

  Also, as an example, in FIG. 9, the fiber bundle X1 ′ in the fiber bundle atlas is composed of three nerve fibers, and the subject fiber bundle X1 that can be used before surgery is also composed of three nerve fibers. The index display unit 206 can calculate the usage rate “100% (3/3)” as the statistical information of the subject nerve region.

(Third embodiment)
After the region of interest is transferred to the subject data by the second transfer unit 204, a fiber bundle corresponding to the logical relationship of each region of interest may not be found. For example, in FIG. 10, the tumor region displaces the fiber bundle, and the region of interest B transferred to the subject data is inside the tumor region E. In this case, it can be seen that the fiber bundle X1 is extruded by the tumor region E, and there is no fiber bundle penetrating the region of interest B in the tumor region E. However, the functional fiber bundle needs to be identified based on the regions of interest A, B, and C. That is, the affected functional fiber bundle cannot be uniquely identified only by the regions of interest A and C located outside the tumor region E.

  The third embodiment is a modification of the second embodiment. The medical image processing apparatus according to the third embodiment is similar to the medical image processing apparatus according to the second embodiment, and includes an extraction unit 201, a first transfer unit 202, an analysis unit 203, a second transfer unit 204, and display processing. A unit 205 and an index display unit 206. Hereinafter, differences between the third embodiment and the second embodiment will be mainly described, and overlapping descriptions will be appropriately omitted.

  The difference of the third embodiment from the second embodiment is that the analysis unit 203 further determines whether or not there is a region of interest inside the tumor region in the subject data, and performs different processing based on the determination result. It is to analyze the actual location of the affected functional fiber bundle.

  When there is no region of interest inside the tumor region, the actual position of the affected subject fiber bundle can be detected and displayed by the same processing as step S205 in the second embodiment. do not do.

  Hereinafter, the case where the region of interest is inside the tumor region will be described with reference to FIG. Here, FIG. 10 shows the identification of the affected functional fiber bundle using the reciprocal transfer of the region of interest between the subject data and the fiber bundle atlas when the tumor region extrudes the fiber bundle. It is a schematic diagram to do. In the example of FIG. 10, for convenience of explanation, only one nerve fiber is included for each fiber bundle, and the fiber bundle and the region of interest both have an “AND” logical relationship.

  As shown in FIG. 10, when the region of interest B is inside the tumor region E, the region of interest B is the only region of interest in the internal region of interest (internal functional region), and the region of interest A and the region of interest C are external regions of interest. (External function area). First, in the subject data, an external region of interest composed of the region of interest A and the region of interest C is used to penetrate the external region of interest, and the logical relationship between the region of interest A and the region of interest C (in this embodiment, All the fiber bundles corresponding to the logical relationship “AND” are determined as the first fiber bundles (first nerve regions). The first fiber bundle shown in FIG. 10 includes two fiber bundles, which are a subject fiber bundle X1 and a subject fiber bundle X2. Among them, the subject fiber bundle X1 is a fiber bundle extruded by the tumor region E. Next, as shown in FIG. 10, in the fiber bundle atlas, the functional fiber bundle that penetrates the external region of interest and does not penetrate the internal region of interest (region of interest B) is converted into the second fiber bundle (second Specific neural area). In the fiber bundle atlas shown in FIG. 10, the second fiber bundle satisfying the condition is one fiber bundle, that is, fiber bundle X2 '. Finally, the second fiber bundle is subtracted from the first fiber bundle to obtain the affected functional fiber bundle (there is only one affected functional fiber bundle shown in FIG. 10). . That is, by removing the fiber bundle (subject fiber bundle X2) corresponding to the second fiber bundle (fiber bundle X2 ′) from the first fiber bundle (subject fiber bundle X1, subject fiber bundle X2), The affected fiber bundle (subject fiber bundle X1) can be detected.

  Actually, the fiber bundle X2 'in FIG. 10 not only penetrates the region of interest A and the region of interest C, but is further connected to the region of interest D. In other words, the regions of interest A, C, and D are the regions of interest for uniquely specifying the fiber bundle X2 '. Therefore, when the fiber bundle X2 'in the second fiber bundle is transferred to the subject data, it is necessary to transfer the regions of interest A, C, and D to the subject data again. Thereby, from the subject data, the subject fiber bundle that penetrates the regions of interest A, C, and D and corresponds to the logical relationship between the regions of interest A, C, and D (that is, the subject shown in FIG. 10). Obtain the sample fiber bundle X2).

  FIG. 10 is merely an example, and the affected functional fiber bundle is identified by the number of internal or external regions of interest in the subject data and the number of functional fiber bundles that have penetrated the external region of interest in the fiber bundle atlas. The method is different. However, any modification suitable for the gist of the present embodiment is included in the present embodiment.

  Hereinafter, description will be given with reference to FIG. 11 which is a flowchart showing image processing steps according to the third embodiment. The flow in FIG. 11 is a sub-process of step S204 in the second embodiment.

  Taking the situation shown in FIG. 10 as an example, the necessary steps in the process will be described.

  In step S301, the analysis unit 203 determines whether the region of interest is in the tumor region in the subject data. If the analysis unit 203 determines that the region of interest is not within the tumor region, the analysis unit 203 defines the fiber bundle that passes through each region of interest and corresponds to the logical relationship between the regions of interest as the affected functional fiber bundle. It is detected and displayed on the display processing unit 205 (step S302).

  If the analysis unit 203 determines that the region of interest is in the tumor region E, the analysis unit 203 detects a fiber bundle penetrating each region of interest in the external region of interest in the subject data as a first fiber bundle (step S303). In other words, when determining that the region of interest is in the tumor region, the analysis unit 203 detects a fiber bundle penetrating each region of interest other than the tumor region in the subject data as the first fiber bundle (step S303).

  Next, in step S304, the analysis unit 203 passes a functional fiber bundle that passes through each region of interest in the external region of interest from the fiber bundle atlas and does not pass through each region of interest in the internal region of interest to the second fiber bundle. And for each fiber bundle in the second fiber bundle, a region of interest for uniquely recognizing each fiber bundle is specified.

  In step S305, the second transfer unit 204 transfers each region of interest specified in step S304 from the fiber bundle atlas to the subject data.

  In step S306, the analysis unit 203 obtains, as the second fiber bundle in the subject data, a fiber bundle that penetrates each transferred region of interest and corresponds to the logical relationship between the regions of interest in the subject data.

  In step S307, the analysis unit 203 subtracts the second fiber bundle from the first fiber bundle to obtain an affected functional fiber bundle.

  According to the medical image processing apparatus according to the third embodiment, even when the tumor region E displaces the fiber bundle and the region of interest transferred from the fiber bundle atlas to the subject data is within the tumor region E, It is possible to accurately grasp and display the actual position of the affected functional fiber bundle.

  In addition, the index display unit 206 in the third embodiment calculates and displays a damage index due to a tumor region. For example, the index display unit 206 compares the functional fiber bundle affected in the subject data with the functional fiber bundle affected in the fiber bundle atlas, so that the damage indicator is the Calculate statistical information. Here, examples of the statistical information calculated by the index display unit 206 include an extrusion rate, a penetration rate, an infiltration rate, a fracture rate, a usage rate, and the like.

(Fourth embodiment)
The fourth embodiment is a modification of the second embodiment.

  FIG. 12 is a block diagram illustrating a configuration of a medical image processing apparatus according to the fourth embodiment. The difference of the fourth embodiment with respect to the first embodiment is that the first transfer unit 302, the analysis unit 303, the second transfer unit 304, the display processing unit 305, and the index display unit 306 are the same as those in the first embodiment. Compared with the first transfer unit 102, the analysis unit 103, the second transfer unit 104, the display processing unit 105, and the index display unit 106, the additional function is exhibited. Hereinafter, differences between the fourth embodiment and the second embodiment will be mainly described, and overlapping descriptions will be appropriately omitted. Further, the tumor region in the present embodiment includes the tumor in FIG. 13 and the tumor infiltration region around the tumor.

  The extraction unit 301 further extracts subject region-of-interest data representing each region of interest of the subject acquired from the subject, in addition to extracting the position information of the nerve distribution and the information of the tumor region from the subject data. For example, by acquiring an image of the functional region of the subject by magnetic resonance imaging of the blood oxygen level dependent function, data on the subject functional region (that is, the subject region of interest) in this image is extracted.

  The first transfer unit 302 transfers the subject region of interest extracted by the extraction unit 301 to a predefined fiber bundle atlas. FIG. 13 shows an example of transferring subject region-of-interest data to a predefined fiber bundle atlas. For convenience of explanation, only two regions of interest (ie, region of interest A and region of interest B) are shown in the fiber bundle atlas in FIG. 13, and normal regions of interest region A and region of interest B defined in advance are normal. The form is assumed to be approximately elliptical. FIG. 13 further shows two subject regions of interest (ie, subject region of interest C and subject region of interest D) transferred to the fiber bundle atlas. When a brain tumor occurs, does not only the phenomenon of extrusion, penetration, infiltration, etc. occur in the functional fiber bundle due to the influence of the tumor, but also the brain function area (region of interest) correspondingly disappears (becomes smaller)? In some cases, everything disappears. As shown in the subject data in FIG. 13, in the subject region of interest C and the subject region of interest D, a case where the region of interest A and the region of interest B are partially erased due to the tumor is shown. The specimen region of interest C and the subject region of interest D are reduced from the original substantially elliptical shape to an irregular shape.

  The analysis unit 303 is defined in the fiber bundle atlas after detecting the fiber bundle affected by the tumor region based on the positional relationship between the fiber bundle in the fiber bundle atlas and the tumor region transferred to the fiber bundle atlas. Based on the correspondence between the region of interest and the fiber bundle, the region of interest associated with the detected fiber bundle is acquired as an analysis result. In the example shown in FIG. 13, the fiber bundles affected by the detected tumor region are the fiber bundles X1 ′ to the fiber bundles X10 ′, and the region of interest associated with the fiber bundles X1 ′ to the fiber bundles X10 ′. Are region of interest A and region of interest B.

  The index display unit 306 includes, for the region of interest affected by the tumor region, the region of interest of the subject (that is, the actual region of interest) transferred to the fiber bundle atlas and the region of interest defined in advance in the fiber bundle atlas (that is, Regions of interest in normal form) are compared and regions of interest that do not match are detected as regions of interest affected by the tumor region.

  Further, the index display unit 306 can further calculate and display a damage index based on the tumor region based on the comparison result. In this case, the damage index due to the tumor region is a decrease rate with respect to the region of interest in the atlas data of the subject region of interest.

  Then, the second transfer unit 304 transfers the region of interest in the fiber bundle atlas corresponding to the region of interest affected by the tumor region to the subject data. In the lower left part of FIG. 13, a state after the region of interest A and the region of interest B are transferred to the subject data is shown, and two dotted ellipses in the figure are the region of interest A and the region of interest B defined in advance, respectively. Represents the outline.

  The index display unit 306 detects (tracks) the subject fiber bundle from the region of interest affected by the tumor region in the subject data, and affects the subject fiber bundle in the detected subject data and the tumor region in the atlas data. The damage index by the tumor region is calculated by comparing the received fiber bundle.

  In the example shown in FIG. 13, the subject fiber bundle corresponding to the region of interest A and the region of interest B is tracked based on the position of the tumor region and the region of interest A and the region of interest B that have been transferred to the subject data. Is done. In the subject data in FIG. 13, ten fiber bundles connected between the region of interest A and the region of interest B are shown, and are fiber bundles X1 to X10 in order from the left in the figure.

  Depending on the positional relationship between each fiber bundle and the tumor in FIG. 13, the fiber bundles X1 to X10 are classified into a plurality of types such as a blocked fiber bundle, an infiltrating fiber bundle, a penetrating fiber bundle, and an unaffected fiber bundle. The blocked fiber bundle is a fiber bundle blocked by a tumor, and the fiber bundle X5, fiber bundle X6, and fiber bundle X7 in FIG. 13 are blocked fiber bundles. The infiltrating fiber bundle is a fiber bundle that has penetrated the tumor infiltrating region around the tumor but has not penetrated the tumor, and the fiber bundle X2, the fiber bundle X3, the fiber bundle X4, and the fiber bundle X9 in FIG. 13 are infiltrating fiber bundles. . The penetrating fiber bundle penetrates the tumor infiltrating region around the tumor and penetrates the tumor, and the fiber bundle X8 in FIG. 13 is the penetrating fiber bundle. The unaffected fiber bundle is a fiber bundle that does not penetrate the tumor infiltrating region, and the fiber bundle X1 and the fiber bundle X10 in FIG. 13 are unaffected fiber bundles. Further, as can be seen in comparison with the fiber bundle X4 ′ in the atlas data in FIG. 13, the fiber bundle X4 in the subject data in FIG. 13 is displaced to the left under the influence of the tumor position, and thus displaced. The fiber bundle is called an extruded fiber bundle.

  A damage index of the functional fiber bundle can be obtained based on each tracked fiber bundle and the position of the affected part. The damage index is represented by, for example, statistical information of functional fiber bundles related to the region of interest, and examples of the statistical information include at least one of extrusion rate, penetration rate, infiltration rate, fracture rate, and usage rate.

  The extrusion rate represents the ratio of the extruded fiber bundle to the functional fiber bundle related to the region of interest. The penetration rate represents the ratio occupied by the penetration fiber bundle in the functional fiber bundle related to the region of interest. The infiltration rate represents the proportion of the functional fiber bundle related to the region of interest occupied by the infiltrating fiber bundle. The destruction rate represents the ratio of the functional fiber bundle related to the region of interest to the functional fiber bundle destroyed by the operation. The destruction rate varies depending on the type of surgery. For example, the destruction rates obtained when “only the tumor is excised” and “when the tumor and the tumor infiltrating area are excised” are usually different. The usage rate represents the ratio of the functional fiber bundle related to the region of interest to the functional fiber bundle that can be used before the operation.

  Table 1 shows statistical information of each subject fiber bundle in FIG. For example, the index display unit 306 calculates and displays each piece of statistical information shown in Table 1.

  The flow of image processing steps according to the fourth embodiment will be described with reference to FIG.

  First, in step S401, subject region-of-interest data representing each region of interest of the subject acquired from the subject is extracted in addition to the position information of the nerve distribution and the information of the tumor region.

  In step S402, in addition to the first transfer unit 302 transferring the fiber bundle image and the affected part image to the predefined fiber bundle atlas, the subject interest extracted by the extraction unit 301 using the transfer matrix is used. The region data is transferred to a predefined fiber bundle atlas.

  In step S403, the analysis unit 303 identifies a region of interest to which the fiber bundle affected by the tumor region is connected based on the position of the tumor.

  In step S404, for the region of interest identified in step S403 by the index display unit 306, the region of interest of the subject transferred to the fiber bundle atlas (ie, the actual region of interest) and the region of interest defined in advance in the fiber bundle atlas (I.e., the region of interest in the normal form) and the region of interest that does not match is detected as the region of interest affected by the tumor region.

  In step S405, the second transfer unit 304 transfers the region of interest in the fiber bundle atlas corresponding to the region of interest affected by the tumor region to the subject data.

  In step S406, the index display unit 306 detects (tracks) the subject fiber bundle from the region of interest affected by the tumor region in the subject data, and in the subject fiber bundle and the atlas data in the detected subject data. By comparing the fiber bundle affected by the tumor region, the damage index by the tumor region is calculated and displayed. The damage index due to the tumor region is represented by statistical information of the subject fiber bundle, and the statistical information is at least one of the extrusion rate, penetration rate, infiltration rate, destruction rate, and usage rate of the nerve region.

  In step S407, the display processing unit 305 may further display the subject data after transfer.

  FIG. 15 is a schematic diagram of a screen displayed by both the index display unit 306 and the display processing unit 305.

  As a modification of the present embodiment, in step S404, a reduction rate of the region of interest in the atlas data of the region of interest with respect to the region of interest may be calculated and displayed as a damage index due to the tumor region. In this case, step S406 may be omitted and the statistical information of the subject fiber bundle may not be calculated.

  In this embodiment, the medical image processing apparatus 300 tracks the functional fiber bundle from the subject data by transferring the region of interest in a normal form defined in advance to the subject data, and damages the functional fiber bundle. The degree can be judged intuitively. By using such a configuration, it is possible to avoid the problem that the subject fiber bundle corresponding to the region of interest cannot be accurately tracked in the subject data because the brain functional region of the subject has disappeared partially or completely. It is. This is because when the region of interest is small, the number of fiber bundles tracked in this region of interest may be smaller than the number to be actually tracked.

  In addition, based on the region of interest in the normal form and the position of the tumor, the functional fiber bundles are divided into types such as blocking fiber bundles, infiltrating fiber bundles, penetrating fiber bundles, and unaffected fiber bundles. Based on the relationship between the actual position of each functional fiber bundle of the specimen and the tumor position, statistical information of the functional fiber bundle related to the region of interest (for example, at least the extrusion rate, penetration rate, infiltration rate, destruction rate, and usage rate) 1) makes it possible to intuitively display the degree of damage to the functional fiber bundle.

  The medical image processing apparatus according to the embodiment may be incorporated in the medical apparatus as a circuit that can realize the functions described in the embodiments, or may be a magnetic disk (floppy disk (registered trademark): (floppy), hard disk, etc.), compact disk (CD-ROM, DVD, etc.), optical disk (MO), semiconductor memory, and other storage media.

  In addition, an OS (operating system) executed on a computer based on an instruction from a program installed in the computer from a storage medium, MW (middle work) such as database management software, network software, and the like also realize the above-described embodiment. A part of each process for performing can be executed.

  According to at least one embodiment described above, the functional classification of the functional area corresponding to the nerve fiber bundle can be easily acquired.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

DESCRIPTION OF SYMBOLS 100 Medical image processing apparatus 101 Extraction part 102 1st transcription | transfer part 103 Analysis part 104 2nd transcription | transfer part 105 Display processing part 106 Index display part

Claims (16)

An extraction unit for extracting position information of nerve distribution from the subject data;
A first transcription unit that transcribes a subject nerve region based on the extracted position information to atlas data;
An analysis unit for analyzing a positional relationship between a functional region in the brain in the atlas data and the transferred nerve region of the subject;
A second transfer unit for transferring the analysis result by the analysis unit to the subject data;
A medical image processing apparatus comprising: It further comprises an index display unit for calculating and displaying a damage index,
The analysis unit acquires, as an analysis result, the functional region corresponding to the transferred subject neural region, and acquired based on the correspondence between the functional region and the neural region defined in the atlas data Obtaining the neural region associated with the functional region;
The medical image processing apparatus according to claim 1, wherein the index display unit calculates and displays the damage index by comparing the transferred subject nerve region and the acquired nerve region.   The medical image processing apparatus according to claim 2, wherein the damage index includes statistical information of the subject nerve region, and the statistical information is a usage rate of the nerve region. The extraction unit extracts the position information of the affected part,
The first transfer unit transcribes the affected area based on the extracted position information of the affected area to the atlas data,
The medical image processing apparatus according to claim 1, wherein the analysis unit analyzes a positional relationship between a functional area in the atlas data, a nerve area in the atlas data, and the transferred affected area.   The analysis unit detects the nerve region affected by the affected area based on the positional relationship between the nerve area and the transferred affected area, and the functional area defined in the atlas data The medical image processing apparatus according to claim 4, wherein the functional area associated with the detected nerve area is acquired as an analysis result based on a correspondence relationship between the nerve area and the nerve area. A display processing unit;
The analysis unit detects the subject nerve region affected by the affected region based on the acquired functional region,
The medical image processing apparatus according to claim 5, wherein the display processing unit displays the subject nerve region detected by the analysis unit.   The medical image processing apparatus according to claim 6, wherein the display processing unit displays an image in which the subject nerve region affected by the affected region is emphasized. In the atlas data, one nerve region is associated with a plurality of functional regions,
When at least one of the plurality of functional areas is located in the affected area, the analyzing unit passes through the external functional area excluding the internal functional area located in the affected area of the plurality of functional areas. A sample nerve region is detected as a first nerve region, the nerve region that passes through the external function region and does not pass through the internal function region is detected as a second nerve region, and the first nerve region is detected from the first nerve region. The medical image processing apparatus according to claim 6, wherein the subject nerve region affected by the affected area is detected by removing the subject nerve region corresponding to two nerve regions.   The apparatus further comprises an index display unit that calculates and displays a damage index by the affected area by comparing the subject nerve area detected by the analysis unit and the nerve area affected by the affected area. The medical image processing apparatus according to any one of claims 6 to 8.   The damage index includes statistical information of the subject nerve region, and the statistical information is at least one of an extrusion rate, a penetration rate, an infiltration rate, a destruction rate, and a usage rate of the nerve region. Medical image processing apparatus. An indicator display unit,
The extraction unit extracts position information of a functional region in the brain from the subject data,
The first transfer unit transfers the subject functional area based on the extracted position information to the atlas data,
The said index display part calculates and displays the damage index by the said affected part area | region by comparing the said functional area | region which the said analysis part acquired, and the said subject functional area | region transferred. Medical image processing apparatus.   The medical image processing apparatus according to claim 11, wherein the damage index is a reduction rate of the subject functional area with respect to the functional area in the atlas data. The analysis unit detects the subject nerve region affected by the affected region based on a functional region associated with the detected nerve region,
12. The index display unit calculates and displays a damage index due to the affected area by comparing the detected subject nerve area with the nerve area affected by the affected area. Or a medical image processing apparatus according to 12;   The damage index includes statistical information of the subject nerve region, and the statistical information is at least one of an extrusion rate, a penetration rate, an infiltration rate, a destruction rate, and a usage rate of the nerve region. Medical image processing apparatus. The nerve region is a region corresponding to a nerve fiber bundle,
The medical image processing apparatus according to claim 2, wherein the functional region is a region corresponding to a brain function or a region corresponding to a tissue structure in the brain. An extraction step of extracting position information of the nerve distribution from the subject data;
A first transcription step of transcribing the subject nerve region based on the extracted position information to the atlas data;
An analysis step for analyzing a positional relationship between the functional region in the brain in the atlas data and the transferred subject nerve region;
A medical image processing method comprising: a second transfer step of transferring the analysis result of the analysis step to the subject data.