JP2013081713A - Medical image processing apparatus - Google Patents

Abstract

An object of the present invention is to reduce an operator's burden related to display of a medical image for which an absolute scale cannot be defined for a pixel value.
A medical image processing apparatus compares a basic cross-sectional image group in which a cross-sectional position with respect to a subject is specified for each image and a cross-sectional image group in which a cross-sectional position with respect to a subject is unspecified for each image. A cross-section specifying unit 4e that specifies the cross-sectional position of the cross-sectional image that matches the basic cross-sectional image to be the same as the cross-sectional position of the basic cross-sectional image is provided. Thereby, the burden on the operator related to the display of the medical image can be reduced.
[Selection] Figure 1

Description

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

  In a medical image diagnostic apparatus, usually, as post-processing after image collection, an image is selected from a storage device, an image server, or a storage medium (storage medium) that stores the medical image, and is displayed for the purpose. There is a series of tasks to execute the corresponding clinical application analysis function. At this time, the displayed image may include images captured by various medical image diagnostic apparatuses such as an X-ray CT apparatus (X-ray computed tomography apparatus) and an MRI apparatus (magnetic resonance imaging apparatus). In many cases, even in the same medical image diagnostic apparatus, images having different parts may be mixed.

  In an image (cross-sectional image) captured by the above-described X-ray CT apparatus, a CT value is determined for each pixel, and a CT value is defined as a pixel value constituting the image. This CT value (HU: Hansfield unit) represents the X-ray absorption coefficient of a substance as a relative value from a reference substance (for example, water), and is a value proportional to the X-ray absorption coefficient. For example, the CT value of reference water is set to 0 (zero), the CT value of bone is set to 1000, and the CT value of air is set to -1000.

  When this image is displayed on a display device such as a liquid crystal display, it is necessary to set display parameters for gradation conversion of the CT value, which is a pixel value, to a gradation value (luminance value) of, for example, monochrome 256 gradations. For example, the operator determines which range of the above CT values (-1000 to 1000) is to be displayed with light and shade by WL (window level) and WW (window width), and converts the CT value in the range to gradation. To do. Actually, WL and WW are set empirically according to the part to be displayed. After this setting, if the images are in the same part, the gray values (luminance values) corresponding to the pixel values that are CT values are the same. In this way, in a medical image in which a CT value, which is an absolute scale, can be defined as a pixel value, an image of the same part is displayed under the same conditions, so that display parameters can be set relatively easily. .

JP 2006-61601 A

  However, in a medical image in which a CT value, which is an absolute scale, cannot be defined for the pixel value, the pixel value varies depending on the imaging method and imaging parameters even in the same region. For this reason, the operator sets appropriate display parameters through trial and error in order to display images of the same part under the same conditions. Even if the display parameters are preset, the display parameters are only a reference level, and the operator needs to change the preset display parameters to the optimum display parameters by experience. For this reason, when displaying a medical image in which an absolute scale cannot be defined for the pixel value, an operator's burden related to the display is increased.

  The problem to be solved by the present invention is to provide a medical image processing apparatus that can reduce the burden on the operator related to the display of a medical image for which an absolute scale cannot be defined for the pixel value.

  The medical image processing apparatus according to the embodiment compares a basic cross-sectional image group in which the cross-sectional position with respect to the subject is specified for each image and a cross-sectional image group in which the cross-sectional position with respect to the subject is unspecified for each image, A cross-section specifying unit that specifies the cross-sectional position of the cross-sectional image that matches the basic cross-sectional image to be the same as the cross-sectional position of the basic cross-sectional image is provided.

1 is a block diagram illustrating a schematic configuration of a medical image processing system according to an embodiment. It is a flowchart which shows the flow of the image processing which the medical image processing apparatus with which the medical image processing system shown in FIG. 1 is provided. It is a flowchart which shows the flow of the cross-section position specific | specification process and display parameter calculation process in the image processing shown in FIG. It is explanatory drawing for demonstrating the area | region collation of an image. It is explanatory drawing for demonstrating correction | amendment of rotation and translation of an image. It is explanatory drawing for demonstrating the area collation using a mask image.

  An embodiment will be described with reference to the drawings.

  As shown in FIG. 1, a medical image processing system 1 according to this embodiment includes a template database 2 that stores templates, an image database 3 that stores image data of a subject, and a medical image processing apparatus that processes image data. 4 and a display device 5 for displaying a medical image based on the image data.

  The template database 2 accumulates and manages basic cross-sectional image information including a basic cross-sectional image group in which the cross-sectional position with respect to the subject has been specified for each image as a template. The basic cross-sectional image group is a group in which the cross-sectional position of the cross-sectional image is specified in which part of the subject, and is used as a template. The basic cross-sectional image information has incidental information including photographing information (for example, photographing date and device type) as necessary. As the template database 2, for example, a magnetic disk device or a semiconductor disk device can be used.

  The image database 3 accumulates and manages unspecified cross-sectional image information including a cross-sectional image group in which the cross-sectional position with respect to the subject is unspecified for each image as the image data of the subject. The cross-sectional image group is a slice image group captured by a medical image diagnostic apparatus such as an MRI apparatus that cannot define an absolute scale for pixel values. The unspecified cross-sectional image information also includes incidental information including a patient ID, a patient name, imaging information (for example, imaging date and device type), and the like. As the image database 3, for example, a magnetic disk device, a semiconductor disk device, or the like can be used.

  The medical image processing apparatus 4 includes an image selection unit 4a for selecting desired image data from the image database 3, an image reading unit 4b for reading the selected image data, an image memory 4c for storing the read image data, and clinical application. A clinical application analysis unit 4d that provides an analysis function, a cross-section specifying unit 4e that specifies the cross-sectional position of the stored image data, and a storage unit 4f that stores various information such as display parameters and examination menus for each region of the subject. A setting unit 4g for setting display parameters, an inspection menu, and the like, and an image generation unit 4h for generating an image for display. Each of these units is constituted by hardware, software, or both.

  The image selection unit 4a selects a cross-sectional image group that is image data of a desired patient from the image database 3 in accordance with an input operation of an operator with respect to an input unit (not shown) such as a mouse or a keyboard, and the selection result Is transmitted to the image reading unit 4b.

  The image reading unit 4b reads a cross-sectional image group, which is image data selected by the image selection unit 4a, from the image database 3 from the selection result transmitted from the image selection unit 4a, and arranges it in the image memory 4c.

  The image memory 4c stores and holds the cross-sectional image group read by the image reading unit 4b according to the arrangement by the image reading unit 4b. As the image memory 4c, for example, a RAM, a magnetic disk device, a semiconductor disk device, or the like can be used.

  The clinical application analysis unit 4d can provide various clinical application analysis functions. As an example of the clinical application analysis function, the clinical application analysis unit 4d creates three-dimensional image data for analysis from two-dimensional image data. Is stored in the image memory 4c or the like.

  The cross-section specifying unit 4e compares the basic cross-sectional image group stored in the template database 2 with the cross-sectional image group arranged in the image memory 4c, and if the basic cross-sectional image and the cross-sectional image coincide with each other, The cross-sectional position of the matched cross-sectional image is specified to be the same as the cross-sectional position of the matched basic cross-sectional image. Therefore, the cross-sectional position of the cross-sectional image is the same as the cross-sectional position of the basic cross-sectional image that matches the cross-sectional image.

  The storage unit 4f stores various information such as display parameters and examination menus for each part of the subject. The display parameter is a parameter for converting the pixel value into an appropriate gray value (luminance value) for image display, and the examination menu is a menu showing examination items for each region (for example, items of various clinical application analysis functions). For example, a ROM, a magnetic disk device, or a semiconductor disk device can be used as the storage unit 4f.

  The setting unit 4g sets display parameters for the cross-sectional image according to the cross-sectional position of the cross-sectional image specified by the cross-section specifying unit 4e. For example, the setting unit 4g automatically sets display parameters according to the cross-sectional position of the above-described cross-sectional image, that is, the region in order to display the image of the same region under the same conditions (details will be described later). When this automatic setting is insufficient, the display parameter for the cross-sectional image is set according to the cross-sectional position of the cross-sectional image specified by the cross-section specifying unit 4e from the display parameters for each part stored in the storage unit 4f. Select and set. On the other hand, when the optimum display parameter does not exist in the storage unit 4f, the cross-section is determined from the display parameters for each part stored in the storage unit 4f according to the cross-sectional position of the cross-sectional image specified by the cross-section specifying unit 4e. A plurality of candidate display parameters for the image are selected and set.

  In addition, the setting unit 4g sets an examination menu (for example, items of various clinical application analysis functions) related to the cross-sectional image according to the cross-sectional position of the cross-sectional image specified by the cross-section specifying unit 4e. For example, the setting unit 4g selects and sets the inspection menu related to the cross-sectional image from the inspection menu for each part stored in the storage unit 4f according to the cross-sectional position of the cross-sectional image specified by the cross-section specifying unit 4e. . Furthermore, the setting unit 4g sets the part name of the basic cross-sectional image as the part name of the cross-sectional image that matches the basic cross-sectional image. This part name is included in the incidental information of the basic cross-sectional image, and is read out from the incidental information and used.

  The image generation unit 4 h generates a cross-sectional image to be displayed from the cross-sectional image group in the image memory 4 c based on the display parameter set by the setting unit 4 g and supplies the cross-sectional image to the display device 5. Further, the image generation unit 4h generates an image including candidate display parameters and examination menus, and further includes a part name corresponding to the cross-sectional image, and supplies the generated image to the display device 5.

  The display device 5 is a display device that displays various images such as an image generated by the image generation unit 4h and other images. As the display device 5, for example, a liquid crystal display, a CRT (Cathode Ray Tube) display, or the like can be used.

  Next, the image processing performed by the medical image processing apparatus 4 will be described in detail. When an operator such as a clinical laboratory technician or a doctor performs an input operation on the input unit and designates desired image data, the following processing is executed.

  As shown in FIG. 2, first, image data (cross-sectional image group) is selected by the image selection unit 4a (step S1). Next, the image data is arranged in the image memory 4c by the image reading unit 4b (step S2). Thereafter, the cross-section position is specified by the cross-section specifying unit 4e and the setting unit 4g and the display parameters are calculated (step S3), and an image (usually a two-dimensional image) is generated by the image generating unit 4h (step S4). An image is displayed by the display device 5 (step S5).

  If display of a three-dimensional image, which is an example of a clinical application analysis function, is instructed by an input operation of an operator with respect to the input unit, in step S4, the set of cross-sectional images in the image memory 4c are set. Three-dimensional analysis image data is generated using the display parameters, and the three-dimensional image is displayed by the display device 5 in step S5.

  Here, the process flow of the above-described step S3 will be described in detail.

  As shown in FIG. 3, first, image position correction is performed (step S11), then region division is performed (step S12), and region matching between the basic cross-sectional image and the cross-sectional image is performed (step S12). S13) Finally, display parameters are calculated (step S14). These processes are executed by the cross-section specifying unit 4e and the setting unit 4g.

  In step S11, since the basis of the above-described processing is region collation between images, the cross-sectional image group to be collated in the image memory 4c is set to the same cross-sectional state as the basic cross-sectional image group in the template database 2 that is the collation source. Correction (for example, enlargement, reduction, and reversal of the image) is performed. In this enlargement and reduction correction, enlargement reconstruction, reduction reconstruction, partial collection, and the like are performed, and in the inversion correction, viewpoint movement (VFF, VFH) is performed. For example, in the enlargement / reduction correction, enlargement or reduction is performed based on pixel spacing (actual pixel length) so that the cross-sectional image to be collated matches the basic cross-sectional image of the template. In the reversal correction, the cross-sectional image to be collated is also mirror-inverted in accordance with the basic cross-sectional image of the template, using information on the orientation (normal vector of the image plane) of the basic cross-sectional image. Various types of information of these templates are included in the supplementary information of the basic cross-sectional image, and are read out from the supplementary information and used.

  In step S12, various methods can be used as the region dividing method. As an example, a method based on the division integration method is used. This division integration method is composed of two steps. In the first step, the distribution of the sections is generated from a single population (composition) while the cross-sectional image is divided into a plurality of sections (for example, 2 × 2). If the distribution of plots is generated from a single population, the partitioning is stopped. If the distribution of partitions is not generated from a single population, the split is continued. However, the processing is stopped when a certain partition unit is reached. In the next step, if adjacent sections of the divided sections are composed of the same population, these sections are integrated. This process is repeated to integrate the divided sections.

  In a medical image diagnostic apparatus such as an MRI apparatus, pixel values may vary even if the same part is imaged by the same imaging method, and it is difficult to take a statistical method. Therefore, the following approximate solution is used from the assumption that the region to be observed in the cross-sectional image has a certain area and has a high contrast that can be distinguished from the others. In this solution, first, the cross-sectional image is divided into certain sections (for example, 16 × 16), maximum pixel values in these sections are obtained, and the entire section is filled with the maximum pixel values. Next, division is performed by the division integration method. In the division, the test is performed according to the continuous uniform distribution. If the continuous uniform distribution is followed, the division is stopped. If not, the division is continued, and the processing is stopped at a certain unit or less, for example, 10 × 10 or less. Thereafter, the obtained regions are clustered by the k-average method. Such region division processing is performed on the basic cross-sectional image group of the template and the cross-sectional image group to be collated.

  In step S13, area matching is performed using the area ratio in the round-robin inspection between the cluster of the basic cross-sectional image of the template and the cluster of the cross-sectional image to be verified. As shown in FIG. 4, the procedure starts with a basic cross-sectional image Ti (i = 1 to n1: n1 is a natural number) of a basic cross-sectional image group (for example, a whole-body cross-sectional image group) in the template database 2. A cluster number image Tia (a = 1 to m1: m1 is a natural number, where m1 = 4 as an example in FIG. 4) is generated. Next, an image having a certain cluster number from a cross-sectional image Aj (j = 1 to n2: n2 is a natural number) of a cross-sectional image group (for example, a cross-sectional image group of a part such as a heart or head) in the image memory 4c. Ajb (b = 1 to m2: m2 is a natural number, where m2 = 4 as an example in FIG. 4) is generated.

  After that, bit operation or subtraction is performed on each image Tia and each image Ajb to determine the matching area. If the area ratio exceeds the specified value, the basic cross-sectional image Ti of the template and the cross-sectional image Aj to be collated are regarded as the same, and the process ends. At this time, the matching ratio between the basic cross-sectional image Ti of the template and the cross-sectional image Aj to be collated is also calculated. The specified value can be changed. All the basic cross-sectional images Ti and the cross-sectional image Aj to be collated are compared, and when the comparison is completed, the cross-sectional position of the basic cross-sectional image Ti having the highest relevance rate is specified as the cross-sectional position of the cross-sectional image Aj to be collated. . As a result, the cross-sectional position of the cross-sectional image Aj to be collated becomes the same as the cross-sectional position of the basic cross-sectional image Ti that matches the cross-sectional image Aj. Since the position of which part of the subject is the cross-sectional position of the basic cross-sectional image Ti is specified, the position of the cross-sectional position of the cross-sectional image Aj to be collated is also the position of which part of the subject. Will be specified.

  In step S14, an optimum display parameter is calculated by considering a high contrast portion as an observed portion according to the cross-sectional position of the cross-sectional image Aj described above. For example, in the case of luminance, the pixel value of a portion having a high pixel value (high signal value) and a large area is obtained using information such as the cross-sectional position of the cross-sectional image Aj to be collated and the high pixel value area obtained above. Is set to the luminance center, the luminance conversion processing is performed to set the minimum value and the maximum value in the high pixel value area to the luminance width, and the display parameters for luminance conversion are set. In step S14, the cross-sectional position and high pixel value region of the cross-sectional image Aj to be collated are specified.

  Further, when performing three-dimensional image display, it is possible to determine which part (for example, blood vessel or organ) the high-contrast region is based on the cross-sectional position of the cross-sectional image Aj. Display parameters can be calculated. For example, in a three-dimensional image display, an appropriate color table is selected from a part (for example, an organ or a blood vessel) located at a high pixel value, and a linear transparency curve centered on the luminance is obtained to obtain a three-dimensional display parameter. Set to.

  Here, before performing the region collation described above, the cross-sectional image Aj to be collated may have already been rotated or translated at the time of photographing or the like. Since partitioning is performed in a certain area at the time of region division, it is not so much affected by small rotations and translations. Therefore, first, as described above, the region matching process including only enlargement / reduction and reversal correction is performed, and when matching fails in all the basic cross-sectional images Ti of the template, it is determined that the influence of rotation or translation is large, and rotation is performed. And translation correction. In this correction, clusters are arranged according to area, two sets having the same center-of-gravity distance between clusters are selected, and the amount of movement and the amount of rotation are calculated.

  For example, as shown in FIG. 5, first, line segments (P1, P2) and (Q1, Q2) are obtained from the basic cross-sectional image Ti of the template, and line segments (R1, R2) are obtained from the cross-sectional image Aj to be collated. , (S1, S2). These line segments are obtained by the area collation process in which only the first enlargement, reduction, and reversal correction is performed.

  Next, a quadrilateral is formed, and in the basic cross-sectional image Ti of the template, new line segments (P1, Q1) and (P2, Q2) are obtained (see the dotted lines in FIG. 5). , Line segments (R1, S1), (R2, S2) are obtained (see dotted lines in FIG. 5). The distance of the line segment (P1, Q1) is compared with the distance of (R1, S1), and the distance of the line segment (P2, Q2) is compared with the distance of (R2, S2). Since information between points is not lost in rotation and translation, it is possible to confirm whether or not the cross-sectional image Aj to be verified is the same as the basic cross-sectional image Ti of the template by comparing the distances between the points. If they are not the same, processing is performed with another basic cross-sectional image Ti.

  Thereafter, a set of clusters corresponding to the areas (P1 and R1 in FIG. 5) is selected, and parallel movement amounts dx and dy are calculated from the positional relationship between these P1 and R1. The line segment (R1, R2) of the cross-sectional image Aj to be collated and the line segment (P1, P2) of the basic cross-sectional image Ti of the template corresponding to the line segment are represented by vector notation, and the depression angle (rotation angle) θ is set as the vector notation. Obtained from inner product. In this way, the movement amount and the rotation amount are calculated, and the rotation and translation of the cross-sectional image Aj to be verified are corrected based on the movement amount and the rotation amount. Thereby, since rotation and translation correction are added to enlargement, reduction, and reversal correction, accurate region matching can be performed.

  In addition, before performing the above-described region collation, there is a defect between the cross-sectional image Aj to be collated and the basic cross-sectional image Ti of the template due to enlarged imaging (collection), enlargement reconstruction, reduction reconstruction, etc. There is. For this reason, for the purpose of improving the collation accuracy, a mask image that excludes the missing portion from the collation target (not the evaluation target) is generated from the information on the enlarged imaging and the enlargement / reduction reconstruction, and is excluded from the collation target.

  For example, as shown in FIG. 6, when the cross-sectional image Aj to be collated has a missing region R1, a mask image B1 corresponding to the missing region R1 is generated. This mask image B1 has the same shape and the same area as the defect region R1, and is an image that covers the defect region R1. When performing region matching, the mask image B1 is superimposed on the basic cross-sectional image Ti of the template, and region matching between the basic cross-sectional image Ti of the template in that state and the cross-sectional image Aj to be verified is performed. As a result, the missing region R1 is excluded from the verification target, so that accurate region verification can be performed.

  Further, a three-dimensional template can be obtained by developing the above-described region division from two dimensions to three dimensions, and the three-dimensional template can be stored in the template database 2. Further, by performing multi-section reconstruction along the cross-sectional direction (direction in which cross-sectional image groups are arranged) of the cross-sectional image Aj to be collated using a three-dimensional template, a two-dimensional template (basic cross-sectional image group) in the cross-sectional direction is obtained. Can be obtained. For example, if all the cross-sectional image groups to be collated do not match the basic cross-sectional image group of the template (two-dimensional), the cross-sectional directions of the cross-sectional image group to be collated and the basic cross-sectional image group of the template are different. The basic cross-sectional image group of the two-dimensional template is reconstructed according to the cross-sectional direction of the cross-sectional image group to be verified from the three-dimensional template. Thereby, area collation can be performed using the basic cross-sectional image group of the two-dimensional template in which the cross-sectional direction matches the cross-sectional image group to be collated. The cross-sectional direction is obtained from the normal vector of the cross-sectional image to be verified.

  Further, according to the cross-sectional position of the cross-sectional image Aj, it is possible to automatically display the part name (including the organ name) from the cross-sectional position. The display of the part name can be used for grasping an organ position in an image with poor projection or for education. Furthermore, it is possible to present a necessary inspection menu from the cross-sectional position of the cross-sectional image Aj. For example, a site (including an organ) to be observed is identified from the cross-sectional position of the cross-sectional image Aj and high-luminance information, a clinical application function necessary for the site related to the cross-sectional image Aj is selected, and an examination menu (various clinical application analysis) It can be presented as a function item), and only examination menus related to the site can be listed. Specifically, if the cross-sectional position of the cross-sectional image Aj is the head, an inspection menu related to the brain is selected, and if the cross-sectional position is the chest, an inspection menu such as the heart or lung related to the chest is selected. Further, if the cross-sectional position is the abdomen, an examination menu such as a liver or a kidney related to the abdomen is selected and displayed.

  In addition, since the cross-sectional position of the cross-sectional image Aj can be specified, the two image groups can be aligned. For example, it is possible to obtain cross-sectional positions of two different image groups, automatically calculate the same position, and display the cross-sectional images at the same position side by side. Thereby, labor saving of operation is realizable. Normally, when two different image groups are displayed in comparison, the position information is often different even with different modalities or the same modality, and it is difficult to display the sectional images at the same position side by side. Will increase the work.

  Further, it is possible to inspect whether or not a part (including an organ and a blood vessel) is extracted from the cross-sectional position and contrast information of the cross-sectional image Aj, and calculate an appropriate three-dimensional visualization parameter (transparency and color table). For example, it is possible to specify a region such as a blood vessel to be observed from the cross-sectional position and contrast information (for example, high luminance information), select a color table for three-dimensional creation and transparency, and set display parameters. Thereby, labor saving of operation is realizable.

  As described above, according to this embodiment, the basic cross-sectional image group in which the cross-sectional position with respect to the subject has been specified for each image and the cross-sectional image group in which the cross-sectional position with respect to the subject is not specified for each image are included. In comparison, the cross-sectional position of the cross-sectional image Aj that automatically matches the cross-sectional position of the cross-sectional image Aj with the cross-sectional position of the cross-sectional image Aj that automatically matches the cross-sectional position of the basic cross-sectional image Ti Will be identified. This makes it easy for the operator to set display parameters from the cross-sectional position of the medical image even when displaying a medical image for which an absolute scale cannot be defined for the pixel value. Compared with the case where display parameters are set, the burden on the operator related to the display of medical images can be reduced.

  In particular, by providing a setting unit 4g that sets display parameters for the cross-sectional image Aj in accordance with the cross-sectional position of the specified cross-sectional image Aj, the display parameter corresponding to the cross-sectional position of the cross-sectional image Aj to be displayed, that is, the region. Since it can be set automatically, the burden on the operator can be further reduced.

  Further, the storage unit 4f that stores display parameters for each part of the subject and the display parameters for the cross-sectional image Aj are selected and set according to the cross-sectional position of the specified cross-sectional image Aj from the display parameters for each part. By providing the setting unit 4g, the display parameter corresponding to the part can be automatically set even when the above-described automatic setting is insufficient, so that the burden on the operator is more reliably ensured. Can be reduced.

  If there is no optimal display parameter in the storage unit 4f, the setting unit 4g selects a display parameter that is a candidate for the cross-sectional image Aj according to the cross-sectional position of the cross-sectional image Aj from the display parameter for each part. By selecting, setting, and generating an image including candidate display parameters by the image generation unit 4h, the display device 5 can display the candidate display parameters. As a result, the operator can select and set the display parameter, and as a result, the burden on the operator can be more reliably reduced.

  In addition, the storage unit 4f that stores the examination menu for each part of the subject and the examination menu related to the cross-sectional image Aj are selected and set according to the cross-sectional position of the specified cross-sectional image Aj from the examination menu for each part. By providing the setting unit 4g to perform and the image generation unit 4h for generating an image including the set inspection menu and the cross-sectional image Aj corresponding to the set inspection menu, the inspection menu regarding the cross-sectional image Aj is displayed together with the cross-sectional image Aj. Will be. Thereby, the selection of the inspection menu is facilitated, and the burden on the operator can be further reduced.

  In addition, an image including a setting unit 4g that sets the part name of the basic cross-sectional image Ti to the part name of the cross-sectional image Aj that matches the basic cross-sectional image Ti, and the set part name and the cross-sectional image Aj corresponding to the part name By providing the image generating unit 4h for generating the cross-sectional image Aj, the part name of the cross-sectional image Aj is displayed. Thereby, since the site | part which concerns on cross-sectional image Aj becomes easy to identify, an operator's burden can be further reduced.

  Although one embodiment of the present invention has been described above, this embodiment is presented as an example and is 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.

4 Medical Image Processing Device 4e Cross Section Identification Unit 4f Storage Unit 4g Setting Unit 4h Image Generation Unit Aj Cross Section Image Ti Basic Cross Section Image

Claims (7)

  The cross-sectional image in which the cross-sectional position for the subject has been specified for each image is compared with the cross-sectional image group in which the cross-sectional position for the subject is not specified for each image, and the cross-sectional image that matches the basic cross-sectional image A medical image processing apparatus comprising: a cross-section specifying unit that specifies that the cross-sectional position is the same as the cross-sectional position of the basic cross-sectional image.   The medical image processing apparatus according to claim 1, further comprising: a setting unit that sets display parameters for the cross-sectional image according to a cross-sectional position of the cross-sectional image specified by the cross-sectional specifying unit. A storage unit for storing display parameters for each part of the subject;
A setting unit that selects and sets the display parameter for the cross-sectional image according to the cross-sectional position of the cross-sectional image specified by the cross-section specifying unit from the display parameters for each part stored in the storage unit,
The medical image processing apparatus according to claim 1, further comprising: A storage unit for storing an examination menu for each part of the subject;
From the examination menu for each part stored by the storage unit, according to the cross-sectional position of the cross-sectional image specified by the cross-section specifying unit, a setting unit that selects and sets the inspection menu related to the cross-sectional image;
An image generating unit that generates an image including the inspection menu set by the setting unit and the cross-sectional image corresponding to the inspection menu;
The medical image processing apparatus according to claim 1, further comprising: A setting unit that sets a part name of the basic cross-sectional image to a part name of the cross-sectional image that matches the basic cross-sectional image;
An image generation unit that generates an image including the part name set by the setting unit and the cross-sectional image corresponding to the part name;
The medical image processing apparatus according to claim 1, further comprising:   The cross section specifying unit executes the specification of the cross section position for a plurality of the cross section image groups, and performs alignment of the cross section image groups. Medical image processing apparatus.   The medical image processing apparatus according to claim 1, wherein the cross-section specifying unit generates another basic cross-sectional image group from the basic cross-sectional image group.