JP2023013455A - Medical image processing device - Google Patents

Abstract

To support check of filtration within the vertebral canal.SOLUTION: A medical image processing device according to the embodiment comprises an extraction part, a derivation part, and a display control part. The extraction part extracts a first region being a region of the vertebral canal included in a medical image. The derivation part derives an index concerning the degree of infiltration in the vertebral canal based on the first region and a second region in which a pixel value is a threshold or more in the region of the vertebral canal. The display control part causes a display part to display the index.SELECTED DRAWING: Figure 2

Description

The embodiments disclosed in the specification and drawings relate to a medical image processing apparatus.

The spinal cord is a nerve bundle that exists behind the vertebral bodies of the spine, and the spinal canal is a tubular structure that surrounds the spinal cord. Here, when cancer infiltrates into the spinal canal, the spinal cord is compressed in the lumen of the spinal canal, and paralysis of the limbs and trunk may occur. Early detection of intraspinal canal infiltration is important mainly for maintaining patient's QOL (Quality Of Life). However, confirmation of infiltration in the spinal canal is currently performed visually by a doctor, and technical development to assist this is desired.

JP 2010-131127 A

One of the problems that the embodiments disclosed in the specification and drawings attempt to solve is to assist in confirming intraspinal infiltration. However, the problems to be solved by the embodiments disclosed in this specification and drawings are not limited to the above problems. A problem corresponding to each effect of each configuration shown in the embodiments described later can be positioned as another problem.

A medical image processing apparatus according to this embodiment includes an extraction unit, a derivation unit, and a display control unit. The extraction unit extracts a first region, which is a spinal canal region, included in the medical image. The derivation unit derives an index related to the degree of invasion in the spinal canal based on the first area and a second area in which the pixel value is equal to or greater than a threshold value in the spinal canal area. The display control unit causes the display unit to display the index.

FIG. 1 is a diagram showing an example of the configuration of a medical image processing system including a medical image processing apparatus according to this embodiment. FIG. 2 is a diagram showing an example of the configuration of the medical image processing apparatus according to this embodiment. FIG. 3 is a flow chart showing the procedure of processing by the medical image processing apparatus according to this embodiment. FIG. 4 is a diagram showing an example of an axial cross-sectional image acquired by the acquisition function of the medical image processing apparatus according to this embodiment. FIG. 5 is a diagram showing an example of an extraction image generated by the extraction function of the medical image processing apparatus according to this embodiment. FIG. 6 is a diagram showing a display example by the display control function in the medical image processing apparatus according to this embodiment. FIG. 7 is an enlarged view of the image shown in FIG. FIG. 8 is an enlarged view of the image shown in FIG. FIG. 9 is an enlarged view of the image shown in FIG. FIG. 10 is an enlarged view of the image shown in FIG. FIG. 11 is an enlarged view of the image shown in FIG. FIG. 12 is an enlarged view of the image shown in FIG.

Hereinafter, embodiments of a medical image processing apparatus will be described in detail with reference to the drawings. A medical image processing system including a medical image processing apparatus will be described below as an example.

FIG. 1 is a diagram showing an example of the configuration of a medical image processing system 1 including a medical image processing apparatus 100 according to this embodiment. A medical image processing system 1 shown in FIG. 1 includes a medical image processing apparatus 100 , a medical image diagnostic apparatus 200 , and an image storage apparatus 300 . A medical image processing apparatus 100 is connected to a medical image diagnostic apparatus 200 and an image storage apparatus 300 via a network 2 such as an in-hospital LAN (Local Area Network) installed in a hospital. Here, each device is in a state of being able to communicate with each other directly or indirectly. mutually transmit and receive medical images and the like according to the DICOM (Digital Imaging and Communications in Medicine) standard.

The medical image diagnostic apparatus 200 includes an X-ray diagnostic apparatus, an X-ray CT (Computed Tomography) apparatus, an MRI (Magnetic Resonance Imaging) apparatus, an ultrasonic diagnostic apparatus, a SPECT (Single Photon Emission Computed Tomography) apparatus, and a PET (Positron Emission Computed Tomography) apparatus. ) apparatus, a SPECT-CT apparatus in which a SPECT apparatus and an X-ray CT apparatus are integrated, a PET-CT apparatus in which a PET apparatus and an X-ray CT apparatus are integrated, or a group of these apparatuses. The medical image diagnostic apparatus 200 can generate two-dimensional medical images, three-dimensional medical images (volume data), time-series two-dimensional medical images, and time-series three-dimensional medical images.

Here, the medical image diagnostic apparatus 100 collects medical images by photographing a subject. For example, the X-ray CT apparatus, which is the medical image diagnostic apparatus 100, pivots an X-ray tube and an X-ray detector on a subject to whom a contrast medium has been administered, detects X-rays that have passed through the subject, and obtains projection data. collect. Then, based on the acquired projection data, the X-ray CT apparatus generates two-dimensional CT images, three-dimensional CT images (volume data), two-dimensional CT images in time series, and three-dimensional images in time series. to generate a CT image of Alternatively, the X-ray CT apparatus generates a plurality of two-dimensional CT images along a predetermined direction based on acquired projection data. For example, an X-ray CT apparatus generates two-dimensional CT images of multiple axial sections along the body axis direction.

The medical image diagnostic apparatus 200 transmits the generated medical images to the image storage apparatus 300 . In addition, when the medical image diagnostic apparatus 200 transmits the medical image to the image storage apparatus 300, the medical image diagnostic apparatus 200 includes additional information such as a patient ID for identifying a patient, an examination ID for identifying an examination, and an identification of the medical image diagnostic apparatus 200. An apparatus ID, a series ID for identifying one imaging by the medical image diagnostic apparatus 200, and the like are transmitted.

The image storage device 300 is a database that stores medical images. Specifically, the image storage apparatus 300 includes a storage circuit, and stores the medical images transmitted from the medical image diagnostic apparatus 200 in the storage circuit, thereby storing the medical images. The storage circuit of the image storage device 300 is, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. Medical images stored in the image storage apparatus 300 are stored in association with patient IDs, examination IDs, apparatus IDs, series IDs, and the like. Therefore, the medical image processing apparatus 100 can acquire necessary medical images from the image storage apparatus 300 by searching using patient IDs, examination IDs, apparatus IDs, series IDs, and the like.

The medical image processing apparatus 100 is an image processing apparatus that performs image processing on medical images. . The medical image processing apparatus 100 performs various processes on medical images acquired from the medical image diagnostic apparatus 200 or the image storage apparatus 300 .

FIG. 2 is a diagram showing an example of the configuration of the medical image processing apparatus 100 according to this embodiment. As shown in FIG. 2 , the medical image processing apparatus 100 has an input interface 110 , displays 120 and 123 , a communication interface 130 , a memory circuit 140 and a processing circuit 150 .

The input interface 110 has a pointing device such as a mouse, a keyboard, and the like, receives input of various operations to the medical image processing apparatus 100 from the user, and transfers instructions and setting information received from the user to the processing circuit 150 .

The display 120 is a monitor that is referred to by the user, and under the control of the processing circuit 150, displays images to the user, and provides a GUI for receiving various instructions, various settings, etc. from the user via the input interface 110. Graphical User Interface). The communication interface 130 is a NIC (Network Interface Card) or the like, and communicates with other devices. Display 120 is an example of a display unit. The storage circuit 140 is, for example, a semiconductor memory device such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk.

The processing circuitry 150 controls the components of the medical image processing apparatus 100 . For example, processing circuitry 150 performs acquisition function 151, extraction function 152, derivation function 153, and display control function 154, as shown in FIG. Here, for example, each processing function executed by the acquisition function 151, the extraction function 152, the derivation function 153, and the display control function 154, which are components of the processing circuit 150, is stored in the storage circuit in the form of a computer-executable program. 140 is recorded. The processing circuit 150 is a processor that reads each program from the storage circuit 140 and executes it, thereby realizing functions corresponding to each program. In other words, the processing circuit 150 with each program read has each function shown in the processing circuit 150 of FIG. The acquisition function 151, the extraction function 152, the derivation function 153, and the display control function 154 are examples of an acquisition unit, an extraction unit, a derivation unit, and a display control unit, respectively.

The term "processor" used in the above description includes, for example, CPU (Central Processing Unit), GPU (Graphics Processing Unit), Application Specific Integrated Circuit (ASIC)), programmable logic device (for example, simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD), Field Programmable Gate Array (FPGA), and other circuits. When the processor is, for example, a CPU, the processor reads out and executes a program stored in the storage circuit 140 to achieve its functions. On the other hand, if the processor is, for example, an ASIC, then instead of storing the program in the storage circuit 140, the program is directly embedded within the circuitry of the processor. Note that each processor of the present embodiment is not limited to being configured as a single circuit for each processor, and may be configured as one processor by combining a plurality of independent circuits to realize its function. good. Furthermore, a plurality of components in FIG. 2 may be integrated into one processor to realize its functions.

The overall configuration of the medical image processing system 1 including the medical image processing apparatus 100 according to this embodiment has been described above. Based on such a configuration, the medical image processing apparatus 100 includes an extraction function 152, a derivation function 153, and a display control function 154 so as to support confirmation of infiltration in the spinal canal. The extracting function 152 extracts the first region, which is the spinal canal region, included in the medical image. The derivation function 153 derives an index related to the degree of invasion in the spinal canal based on the first area and the second area in which the pixel value is equal to or greater than the threshold value in the spinal canal area. Display control function 154 causes display 120 to display the indicator.

Each function of the medical image processing apparatus 100 will be specifically described below with reference to FIG. FIG. 3 is a flowchart showing the procedure of processing by the medical image processing apparatus 100 according to this embodiment.

Step S101 in FIG. 3 is a step executed by the processing circuit 150 calling a program corresponding to the acquisition function 151 from the storage circuit 150 . In step S<b>101 , the acquisition function 151 receives a user's operation of the input interface 110 to acquire medical images from the medical image diagnostic apparatus 200 or the image storage apparatus 300 .

A medical image is an image including the spinal canal of a subject, and is a plurality of cross-sectional images along a predetermined direction. For example, the medical images are multiple axial cross-sectional images along the body axis direction. FIG. 4 is a diagram showing an example of an axial cross-sectional image 400 acquired by the acquisition function 151. As shown in FIG. The acquisition function 151 acquires a plurality of axial cross-sectional images 400 as medical images.

Step S102 in FIG. 3 is a step executed by the processing circuit 150 calling a program corresponding to the extraction function 152 from the storage circuit 150. FIG. In step S102, the extraction function 152 extracts the spinal canal region from each of the plurality of axial cross-sectional images 400 to generate an extracted image.

FIG. 5 is a diagram showing an example of an extraction image 500 generated by the extraction function 152. As shown in FIG. For example, if the medical image is a three-dimensional CT (Computed Tomography) image, the extraction function 152 extracts the spinal canal region by binarization processing using a threshold set based on the CT value. A CT value is an example of a pixel value. Specifically, the extraction function 152 binarizes the axial cross-sectional image 400 and extracts the spinal canal region. The extraction function 152 then produces an extracted image 500 representing the extracted spinal canal.

Step S103 in FIG. 3 is a step executed by the processing circuit 150 calling a program corresponding to the derived function 153 from the storage circuit 150. FIG.

In step S103, the derivation function 153 derives an index related to the degree of invasion in the spinal canal based on the first region and the second regions in which the pixel values of each extracted image 500 are greater than or equal to the first threshold.

For example, when the medical image is a three-dimensional CT image and infiltration has occurred in the spinal canal of the subject, the pixel value, which is the CT value of the part where infiltration may have occurred, indicates that infiltration has not occurred. Higher than the portion. Therefore, as shown in FIG. 5, the derivation function 153 performs the following calculation based on the first region 510, which is the region of the spinal canal, and the second region 520, in which the pixel values are equal to or greater than the first threshold, in each extracted image 500. , to derive an index for the degree of invasion in the spinal canal.

Here, the first threshold may be a preset value or a value calculated for each subject by the derivation function 153 . For example, when the derivation function 153 calculates the first threshold value, the derivation function 153 generates a histogram with the pixel values of the extracted image 500 of the subject with infiltration in the spinal canal. In the generated histogram, when the horizontal axis is the pixel value and the vertical axis is the frequency, there are two parts: a normal part where infiltration has not occurred and an abnormal part where infiltration may have occurred. A mountain appears. Here, the derivation function 153 calculates a pixel value that can separate the two mountains as the first threshold.

Also, the first threshold value may be determined according to the degree of progress such as the stage of cancer. For example, when the derivation function 153 determines the first threshold according to the stage of cancer, the subjects (patients) may be grouped by each stage and the first threshold may be set for each group. Here, the first threshold set for each group is determined according to patient attributes such as sex and age.

For example, the index derived by the deriving function 153 is a numerical value representing the area ratio between the first region 510 and the second region 520 . Specifically, the derivation function 153 calculates the area of the first region 510 and the area of the second region 520 in each extracted image 500 . The derivation function 153 then calculates an area ratio representing the ratio between the area of the first region 510 and the area of the second region 520 . For example, the area ratio is calculated by dividing the second region 520 (the area of pixels equal to or greater than the first threshold) by the first region 510 (the area of the spinal canal region). Then, the derivation function 153 derives an index regarding the degree of infiltration in the spinal canal based on the calculated area ratio. A higher value of this index indicates a higher degree of infiltration, and a lower value indicates a lower degree of infiltration.

Alternatively, the derivation function 153 may determine whether the area ratio is equal to or greater than the second threshold, and output the determination result. For example, the derivation function 153 outputs a determination result indicating that there is a high possibility that infiltration has occurred if the area ratio is equal to or greater than the second threshold, and if the area ratio is smaller than the second threshold, A determination result is output indicating that the possibility of infiltration is low. Note that the derivation function 153 may output both the numerical value representing the area ratio and the information representing the determination result of the area ratio as indices.

Here, the pixels whose pixel values are greater than or equal to the first threshold may exist in clusters or may exist in a scattered manner. When infiltration occurs, pixels whose pixel values are greater than or equal to the first threshold are clustered, and when noise occurs, pixels whose pixel values are greater than or equal to the first threshold are dispersed. is assumed. Therefore, in step S103, the derivation function 153 further derives an index regarding the degree of invasion in the spinal canal based on the spatial distribution of the pixels forming the second region 520 of each extracted image 500. FIG.

Specifically, the derivation function 153 calculates the area ratio between the first region 510 and the second region 520 of each extracted image 500 as the area ratio calculation process, and then executes the variance value calculation process. In the variance value calculation process, the derivation function 153 performs contraction/expansion/filling process of the second area 510 to determine a third area including the second area 510 . Then, the derivation function 153 calculates a value obtained by dividing the area of the third region by the area of the second region 510 as a variance value representing the degree of variation in the positions of pixels whose pixel values are equal to or greater than the first threshold. For example, in the second region 520, when pixel values equal to or greater than the first threshold are clustered, the variance value is small. For example, when the variance value of the second region 520 is equal to or greater than the third threshold, the derivation function 153 determines that the second region 520 is affected by noise and is unlikely to be infiltrated. determined and excluded from processing. On the other hand, when the variance value of the second region 520 is smaller than the third threshold, the derivation function 153 determines that the second region 520 is a portion where infiltration may occur, and treats it as a processing target.

In this way, the derivation function 153 executes the above-described variance value calculation processing after executing the above-described area ratio calculation processing, so that the second region 520 is a portion where infiltration may occur. It is possible to distinguish whether the noise is affected by noise. In the above example, the derivation function 153 executes the variance value calculation process after executing the area ratio calculation process. processing may be performed.

Considering not only the extracted image 500 of one slice but also the extracted images 500 of the preceding and following slices, it is possible to determine whether the second region 520 is a portion where infiltration may occur. It is necessary to distinguish whether it is In this case, in step S103, the derivation function 153 further derives an index regarding the degree of invasion in the spinal canal based on the continuity of the second regions 520 in each extracted image 500 in the predetermined direction.

Specifically, the derivation function 153 executes the above-described variance value calculation processing for the extracted images 500 of the preceding and succeeding slices. For example, the derivation function 153 executes the variance value calculation process described above on the extracted image 500 for five slices. For example, if the variance value of the second region 520 is equal to or greater than the third threshold in the extraction images 500 of the slices before and after among the extraction images 500 for five slices, the derivation function 153 extracts the extraction images of the slices before and after the A second region 520 of 500 is affected by noise, is determined to have a low possibility of infiltration, and is excluded from processing. On the other hand, if the variance value of the second region 520 in the extracted image 500 of the slice before and after the slice is smaller than the third threshold, the derivation function 153 determines that the second region 520 of the extracted image 500 of the slice before and after the infiltration occurs. It is determined that there is a possibility that the

In this way, the derivation function 153 performs the above-described variance value calculation processing on the extracted images 500 of the slices before and after the first region 510 of the extracted images 500 of the slices before and after the possibility that infiltration has occurred. It is possible to distinguish whether the part is affected by noise or is affected by noise.

Step S104 in FIG. 3 is a step executed by the processing circuit 150 calling a program corresponding to the display control function 154 from the storage circuit 150. FIG. In step S<b>104 , the display control function 154 causes the display 120 to display the indices derived by the derivation function 153 .

For example, the display control function 154 causes the display 120 to superimpose the determination result based on the index derived by the derivation function 153 on the medical image.

FIG. 6 is a diagram showing a display example by the display control function 154. As shown in FIG. As shown in FIG. 6, the display control function 154 displays an image 550 described later in a first display area, which is a display area on the left side of the display 120 as seen from the user, and displays an image 550 on the right side of the display 120 as seen from the user. Images 560 and 570, which will be described later, are displayed in the second display area. Also, as shown in FIG. 6, the display control function 154 displays images 410, 420, 430, and 540, which will be described later, in a third display area between the first display area and the second display area. Specifically, the display control function 154 divides the third display area into four, and displays images 410, 420, 430, and 540, which will be described later, in the four divided display areas.

For example, the derivation function 153 determines whether or not the area ratio between the first region 510 and the second region 520 of the extracted image 500 is equal to or greater than the second threshold. Suppose there is In this case, the index derived by the derivation function 153 is the determination result indicating that the area ratio is equal to or greater than the second threshold. Alternatively, it is a determination result indicating that the area ratio is equal to or greater than the second threshold and the variance value is smaller than the third threshold.

FIG. 7 is an enlarged view of image 540 shown in FIG. For example, as shown in FIG. 7, the display control function 154 extracts the determination result 530 "ALERT" indicating that the area ratio is equal to or greater than the second threshold and the variance value is smaller than the third threshold. It is displayed on the display 120 in a state of being superimposed on the image 500 . Specifically, in the example shown in FIG. 7, the display control function 154 generates an MPR (Multi Planar Reconstruction) image 540 corresponding to the extracted image 500, and superimposes the determination result 530 “ALERT” on the MPR image 540. is displayed on the display 120.

Further, in FIG. 7, the display control function 154 causes the display 120 to display a color image in which a color corresponding to the value of the area ratio is assigned to each pixel of the second region 520 in the MPR image 540 as an index. Specifically, in the example shown in FIG. 7, when the area ratio is equal to or greater than the second threshold, the color image assigned to the second region 520 is shown in black on the drawing, but the area ratio For example, blue is displayed as a color corresponding to the value of . Thereby, the doctor can check the spinal canal infiltration by referring to the determination result 530 “ALERT” on the MPR image 540 and the color corresponding to the index.

Here, in the example shown in FIG. 7, the display control function 154 superimposes the determination result indicating that the area ratio is equal to or greater than the second threshold value as the index derived by the derivation function 153 on the MPR image 540. Although it is displayed on the display 120 in the state, it is not limited to this. For example, the display control function 154 may cause the display 120 to display the area ratio superimposed on the MPR image 540 as an index derived by the derivation function 153, or display the area ratio and the determination result as the MPR image. 540 may be displayed on the display 120 .

FIG. 8 is an enlarged view of image 410 shown in FIG. For example, as shown in FIG. 8, the display control function 154 causes the display 120 to display the MPR image 540 corresponding to the extracted image 500 and the current image 410 side by side. A current image 410 is the axial cross-sectional image 400 from which the extracted image 500 has been extracted. That is, the current image 410 shown in FIG. 8 is the same image as the axial cross-sectional image 400 shown in FIG.

Note that the MPR image 540 has the same cross section as the current image 410, but the cross section as the MPR image 540 may be a different cross section from the current image 410, and any cross section that allows the second region 520 to be confirmed in a wide range. There may be. For example, the MPR image 540 may be a cross-cut image that is an image of a cross section closest to the current image 410 as an arbitrary cross section that allows the second region 520 to be confirmed over a wide range.

FIG. 9 is an enlarged view of image 420 shown in FIG. For example, as shown in FIG. 9, the display control function 154 causes the display 120 to display the MPR image 540, the current image 410, and the past image 420 side by side. The past image 420 is a medical image of the same subject taken in the past, and is an axial cross-sectional image 400 at the same position as the current image 410 . For example, the past image 420 is an image generated as an image of the cross-sectional position closest to the current image 410 using the Warp Field obtained by non-rigid registration.

FIG. 10 is an enlarged view of image 430 shown in FIG. For example, as shown in FIG. 10, the display control function 154 causes the display 120 to display an MPR image 540, a current image 410, a past image 420, and a difference image 430 side by side. A difference image 430 is an image representing the difference between the current image 410 and the past image 420 .

FIG. 11 is an enlarged view of image 550 shown in FIG. The display control function 154 causes the display 120 to display information that associates the area ratio between the first region 510 and the second region 520 of the extracted image 500 with the position of the spinal canal in the medical image.

For example, the display control function 154 renders a three-dimensional medical image composed of a plurality of axial cross-sectional images 400 in the sagittal direction. For example, the display control function 154 generates an SVR image 550 shown in FIG. 11 by performing SVR (Shaded Volume Rendering) processing as rendering processing. Then, the display control function 154 assigns a color corresponding to the index to the spinal canal region 551 where the second regions 520 of the axial cross sections in the SVR image 550 are gathered. That is, the display control function 154 causes the display 120 to display a color image in which each pixel of the spinal canal region 551 in the SVR image 550 is assigned a color corresponding to the index.

In FIG. 11, a color bar 553 is used to assign colors corresponding to area ratio values as indices. Specifically, in the example shown in FIG. 11, when the area ratio is equal to or greater than the second threshold, the color images assigned to the regions 551a and 551b of the spinal canal region 551 are shown in black on the drawing. However, the color corresponding to the value of the area ratio is, for example, blue. Thereby, the doctor can refer to the color corresponding to the index on the SVR image 550 to confirm the spinal canal infiltration.

FIG. 12 is an enlarged view of the images 560, 570 shown in FIG. The display control function 154 causes the display 120 to display information that associates the area ratio between the first region 510 and the second region 520 of the extracted image 500 with the position of the spinal canal in the medical image.

For example, as shown in FIG. 12, the display control function 154 generates an SPR (Stretched Curved Planar Reconstruction) image 560 or CPR (Curved MPR (Multi Planar Reconstruction) image 560 of the spinal canal based on the spinal canal of the three-dimensional medical image. Reconstruction)). FIG. 12 shows an SPR image 560 in which the spinal canal is straightened. Further, as shown in FIG. 12, the display control function 154 indicates the area ratio between the first region 510 and the second region 520 of the extracted image 500 on the horizontal axis, and the position of the spinal canal on the SPR image 560 on the vertical axis. generates a graph 570 showing . Then, the display control function 154 causes the display 120 to display the SPR image 560 and the graph 570 side by side. For example, if the color images assigned to the regions 551a and 551b of the SVR image 550 shown in FIG. The area ratio of the positions corresponding to the regions 551a and 551b of the spinal canal is displayed high.

As described above, in the medical image processing apparatus 100 according to the present embodiment, based on the first region 510 in which the pixel value is equal to or greater than the threshold in the region of the spinal canal and the second region 520 representing the region of the spinal canal, An index relating to the degree of infiltration in the vessel is derived, and displayed on the display 120 in a state where the index is superimposed on the medical image. As a result, the medical image processing apparatus 100 according to the present embodiment can assist confirmation of infiltration into the spinal canal.

It should be noted that each component of each device illustrated in the present embodiment is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the one shown in the figure, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured. Furthermore, all or any part of each processing function performed by each device can be implemented by a CPU and a program analyzed and executed by the CPU, or implemented as hardware based on wired logic.

Also, the method described in this embodiment can be implemented by executing a program prepared in advance on a computer such as a personal computer or a workstation. This program can be distributed via a network such as the Internet. In addition, this program is recorded on a computer-readable non-temporary recording medium such as a hard disk, flexible disk (FD), CD-ROM, MO, DVD, etc., and is executed by being read from the recording medium by a computer. can also

According to at least one embodiment described above, confirmation of intraspinal canal invasion can be assisted.

While several embodiments have been described, these embodiments are provided by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, changes, and combinations of embodiments can be made without departing from the scope of the invention. These embodiments and their modifications are included in the scope and spirit of the invention, as well as the scope of the invention described in the claims and equivalents thereof.

1 medical image processing system 100 medical image processing apparatus 152 extraction function 153 derivation function 154 display control function 510 first area 520 second area

Claims (7)

an extraction unit that extracts a first region that is the region of the spinal canal included in the medical image;
a derivation unit for deriving an index related to the degree of invasion in the spinal canal based on the first region and a second region in which the pixel value in the spinal canal region is equal to or greater than a threshold;
a display control unit for displaying the index on a display unit;
A medical image processing apparatus comprising: The derivation unit derives an area ratio between the first region and the second region as the indicator,
The medical image processing apparatus according to claim 1. The derivation unit further derives the index based on the spatial distribution of the pixels that make up the second region.
The medical image processing apparatus according to claim 2. The medical image is a plurality of cross-sectional images along a predetermined direction,
The extraction unit extracts the first region from each of the plurality of cross-sectional images,
The derivation unit derives the index based on the continuity of the second region in the predetermined direction.
The medical image processing apparatus according to any one of claims 1-3. The display control unit causes the display unit to display a color image in which a color corresponding to the value of the index is assigned to each pixel of the second region.
The medical image processing apparatus according to any one of claims 1-4. The display control unit causes the display unit to superimpose the determination result based on the index on the medical image.
The medical image processing apparatus according to any one of claims 1-5. The display control unit causes the display unit to display information that associates the index with the position of the spinal canal in the medical image.
The medical image processing apparatus according to any one of claims 1-6.

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