JP6855228B2 - Medical image diagnosis support device, its control method, and program - Google Patents

Description

The present invention relates to a medical image diagnosis support device capable of intuitively recognizing the progress of a lesion in an organ, a control method thereof, and a program.

In recent years, the number of patients suffering from COPD (Chronic Obstructive Pulmonary Disease) has been increasing. COPD is a type of obstructive pulmonary disease, and indicates, for example, a pathological condition in which the aerobic region expands after the destruction of alveoli progresses. One of the causes of COPD is an abnormal inflammatory reaction caused by gas such as smoking, air pollution, or harmful fine particles, and progressive airflow restriction accompanied by chronic obstructive airway inflammation and emphysema. It is a characteristic disease.

Therefore, in recent years, a method for quantitatively measuring COPD using a medical image (hereinafter, also referred to as a CT image) taken by an X-ray CT (Computed Tomography) device has been proposed. Among them, a method called "Goddard method" for scoring the degree of progression of emphysema is simple and has come to be widely used (Non-Patent Document 1). Therefore, analysis software that enables evaluation according to the Goddard method is desired.

In the evaluation method based on the Goddard method, three cross sections of the upper lung field (near the aortic arch), the middle lung field (position of the bronchial bifurcation), and the lower lung field (position 1 to 3 cm above the diaphragm) are used. LAA (Low Attention Area) in each of the left and right lung fields is a region with a CT value that is clearly lower than the normal lung field region on the CT image. Normally, the region with a CT value of -950 HU or less is the region of LAA. The ratio of the area is scored, and the severity of chronic obstructive pulmonary disease is judged based on the total.

Japanese Respiratory Society ed .: Guidelines for Diagnosis and Treatment of COPD (Chronic Obstructive Pulmonary Disease) 2nd Edition, Medical Review Co., Ltd., 2004, p12-p13

When treating a progressive disease such as COPD described above, a physician may want to know the degree of disease progression of the patient. In particular, it is important to know how much the disease has progressed compared to the previous medical treatment.

In the case of COPD, the CT image taken in the first period and the CT image taken in the second period are scored according to the Goddard method, and the respective values are compared to obtain the COPD of the patient. The degree of progress can be judged.

However, the comparison of the six left and right points shown above does not capture the overall condition of the lung, which is a vertically long organ, but is only a partial comparison. It is preferable to be able to present to the diagnostician with a mechanism that allows the entire lung to visually and intuitively recognize how the disease is progressing.

In addition, since the lungs have the characteristic that the size of the organ itself changes according to the respiration of the patient, it is not possible to simply compare the lungs with each other in CT images taken at different timings. Therefore, there is a need for a mechanism that enables easy comparison between organs in CT images taken at different timings.

Therefore, an object of the present invention is to provide a mechanism capable of intuitively recognizing the progress of a lesion in an organ by a user.

In order to achieve the above object, the medical image diagnosis support device of the present invention has a first medical image including a target organ of a patient and a second medical image taken at a time different from the first medical image. The ratio of the lesion portion in the cross section of the target organ of the first medical image acquired by the acquisition means and the acquisition means for acquiring the second medical image including the target organ of the patient. A graph generating means for generating a first graph showing the above and a second graph showing the proportion of lesions in the cross section of the target organ in the second medical image, and a reference for the target organ in the first medical image. The first graph and the second graph generated by the graph generating means, and the specific means for specifying the position of the cross section and the position of the reference cross section of the target organ in the second medical image, are described in the second graph. It is provided with a display control means for controlling so as to align and display the position of the reference cross section of the target organ in the medical image of 1 and the position of the reference cross section of the target organ in the second medical image. It is a feature.

According to the present invention, the user can intuitively recognize the progress of the lesion of the organ.

It is a conceptual diagram which shows an example of the hardware composition of the medical image diagnosis support apparatus 100 in this embodiment. It is a conceptual diagram which shows an example of the functional structure of the medical image diagnosis support apparatus 100 in this embodiment. It is a flowchart explaining the detailed process flow in this Embodiment. It is a conceptual diagram which shows an example of the generated graph 401. It is a flowchart explaining the detailed process flow of the alignment process of the graph in the flowchart of FIG. It is a conceptual diagram which shows that the graph 601 and the three-dimensional image 602 of the CT image A, and the graph 603 and the three-dimensional image 604 of the CT image B are displayed in parallel. It is a conceptual diagram for demonstrating the content of the process of aligning a plurality of graphs with corresponding sections. It is a conceptual diagram which shows an example of a report 800.

An embodiment of the present invention will be described with reference to the drawings.

First, the hardware configuration of the medical image diagnosis support device 100 according to the embodiment of the present invention will be described with reference to FIG. The hardware configuration of the medical image diagnosis support device 100 shown in FIG. 1 is an example, and there are various configuration examples depending on the application and purpose.

The medical diagnostic imaging support device 100 includes a CPU 201, a RAM 202, a ROM 203, a system bus 204, an input controller 205, a video controller 206, a memory controller 207, a communication I / F controller 208, an input device 209, a display 210, an external memory 211, and the like. ..

The CPU 201 comprehensively controls each device and controller connected to the system bus 204.

The RAM 202 functions as a main memory, a work area, and the like of the CPU 201. The CPU 201 realizes various operations by loading a program or the like necessary for executing a process into the RAM 202 and executing the program.

The ROM 203 or the external memory 211 stores a BIOS (Basic Input / Output System) which is a control program of the CPU 201, an operating system, various programs which will be described later, which are necessary for realizing functions executed by various devices.

The input controller 205 controls input from a pointing device (input device 209) such as a keyboard or a mouse.

The video controller 206 controls the display of a display device such as the display 210. The display 210 (display unit) is, for example, a CRT or a liquid crystal display.

The memory controller 207 is an external memory such as a hard disk or flexible disk for storing boot programs, browser software, various applications, font data, user files, various data, etc., or a card-type memory connected to a PCMCIA card slot via an adapter. Control access to 211.

The CPU 201 enables display on the display 210 by, for example, executing an outline font expansion (rasterization) process in the display information area in the RAM 202. Further, the CPU 201 enables a user instruction with a mouse cursor or the like (not shown) on the display 210.

Various programs and the like used by the medical image diagnosis support device 100 of the present invention to execute various processes described later are stored in the external memory 211, respectively, and are executed by the CPU 201 by being loaded into the RAM 202 as needed. Is to be done. Further, definition files, various information tables, medical images and the like used by the program according to the present invention are stored in the external memory 211. The medical image is stored in an external server or the like, and the medical image diagnosis support device 100 may be configured to acquire the medical image from the external server.

This completes the description of the hardware configuration of the medical image diagnosis support device 100 shown in FIG.

Next, the description of the functional configuration diagram of the medical image diagnosis support device 100 will be started with reference to FIG.

The medical image diagnosis support device 100 includes a medical image acquisition unit 1001, a lung field region extraction unit 1002, a lung emphysema region extraction unit 1003, a calculation unit 1004, a graph generation unit 1005, a display control unit 1006, and a graph adjustment unit 1007 as functional units. Be prepared. The medical image acquisition unit 1001 is a functional unit that acquires a medical image such as a CT image of a subject (patient) obtained by taking a picture with a modality. In the present embodiment, a CT image will be described as an example, but the present invention can also be applied to a medical image taken by another modality such as an MRI image. The lung field region extraction unit 1002 is a functional unit that extracts the lung field region of the subject based on the medical image acquired by the medical image acquisition unit 1001. The emphysema region extraction unit 1003 is a functional unit that extracts an emphysema region of a subject based on a medical image acquired by the medical image acquisition unit 1001. The calculation unit 1004 is a functional unit that calculates the ratio of the emphysema region in the extracted lung field region for each CT image. The graph generation unit 1005 is a functional unit that generates a graph showing the ratio of the emphysema region in the lung field region calculated by the calculation unit 1004 and the position of the subject of the CT image corresponding to the ratio. The display control unit 1006 is a functional unit that displays an image of the subject and a graph generated by the graph generation unit 1005 on the display screen. The graph adjustment unit 1007 is a functional unit that adjusts the length of a plurality of regions included in the graph generated by the graph generation unit 1005 among the corresponding regions.

This completes the description of the functional configuration of the medical image diagnosis support device 100 shown in FIG.

Next, a detailed processing flow in the present embodiment will be described with reference to the flowchart of FIG. In this embodiment, as an example, a graph showing the rate of emphysema in the lung is adjusted, but a graph plotting some information in other organs is also applicable. For example, it may be a value indicating the movement of the myocardium in the beating of the heart.

In step S301, the CPU 201 of the medical image diagnosis support device 100 acquires (acquires) a CT image which is a slice image (tomographic image; axial cross-sectional image) taken by, for example, an X-ray CT (Computed Tomography) device from the external memory 211. Corresponds to means). In the present embodiment, the lung is used as the target organ, but other organs may be used as the target organ. The CT image acquired in step S301 is a CT image including at least the lungs. Specifically, at least two CT images (groups) that are CT images of a specific patient and have different shooting timings (time) are designated by the user, and at least two CT images (first) that have received the designation. 1 medical image, corresponding to the 2nd medical image) is acquired.

In the medical field, medical images taken by such a modality device are generally transmitted to a PACS (Picture Archiving Communication System) connected via a network and centrally managed there. Therefore, the medical image diagnosis support device 100 is provided so that the medical image can be acquired not only from the inside of the medical image diagnosis support device but also from the PACS. The CT image acquired by the CPU 201 of the medical image diagnosis support device 100 may be not only a slice image but also a reslice image obtained by reslicing a three-dimensional image composed of a plurality of slice images.

In step S302, the CPU 201 of the medical image diagnosis support device 100 replaces the CT value of the background portion of the acquired slice image that is not the human body region with a CT value larger than the CT value corresponding to the lung field region. This is to prevent the CT value of the background portion from being accidentally extracted when the emphysema region is extracted later, and specifically, it is replaced with -700 HU.

Then, by identifying pixels having a CT value smaller than a predetermined threshold value (for example, CT value: -400HU) for extracting the lung field region (corresponding to the organ parenchyma), for each CT image. Extract the lung field area. The method for extracting the lung field region is not limited to this, and if the lung field region can be specified, the designation of the lung field region may be accepted by the user, and Japanese Patent Application Laid-Open No. 2003-70781 Any method such as the method described in the above may be used.

In step S303, the CPU 201 of the medical image diagnosis support device 100 extracts an emphysema region for each slice image (axial cross-sectional image) acquired in step S301. The emphysema region is extracted as LAA (low attenuation area) in the slice image. More specifically, the region of emphysema is extracted by identifying pixels having a CT value smaller than a known value corresponding to emphysema (eg, CT value: −900 HU). The method for extracting the region of emphysema is not limited to this, and the region of emphysema may be extracted by using another method such as the method described in JP-A-2003-70781.

In step S304, the CPU 201 of the medical image diagnosis support device 100 calculates the ratio of the emphysema region extracted in step S303 to the lung field region extracted in step S302 for each slice image. More specifically, the ratio is obtained by dividing N by M, where M is the number of pixels in the lung field region and N is the number of pixels in the emphysema region. In this way, a value indicating the ratio of the emphysema region to the lung field region is calculated for each slice image. The calculated value is managed in association with the slice image.

In step S305, the CPU 201 of the medical image diagnosis support device 100 generates a graph 401 by plotting a value indicating the ratio for each slice image calculated in step S304 at predetermined intervals (corresponding to the graph generation means). .. The generated graph is, for example, the graph 401 shown in FIG. In the graph 401 of FIG. 4, 25%, 50%, and 75% reference lines 410, which are reference values used for score determination by the Goddard method and are values indicating the rate of emphysema, are provided. .. As shown in FIG. 4, when the value of the ratio of emphysema is 0% or more and less than 25%, the line color of the graph is blue, and when the value of the ratio of emphysema is 25% or more and less than 50%, the line color of the graph is orange, 50. The line color of the graph is white in the range of% or more and less than 75%, and the line color of the graph is red in the range of 75% or more and less than 100%. By gradually changing the display form of the line of the graph according to the value indicating the ratio of the emphysema region in this way, it becomes clearer in which part the emphysema is abundant with respect to the entire lung field of the subject. It can be recognized by the user (diagnostic doctor). Although color coding has been described as an example as a method for different display forms, other methods such as changing the form of the line itself may be used.

The coronal cross-sectional image 402 of FIG. 4 is an image obtained by reslicing the CT image acquired in step S301. By displaying the coronal cross-sectional image 402 and the graph 401 in parallel, there is an effect that it is possible to visually recognize the plotted graph value and the position of the value on the body in association with each other. In other words, the user can easily compare a value indicating the rate of emphysema with the position of the subject corresponding to this value. In other words, the user can identify the position of the subject in which the portion showing the high proportion of emphysema in the graph corresponds to, and the distribution of emphysema that cannot be determined only by the score calculated based on the Goddard method. The state can be recognized at a glance.

Auxiliary lines 404, 405, and 406 indicating the position on the body structure of the patient are superimposed on the graph 401 and the coronal cross-sectional image 402. Auxiliary line 404 is an auxiliary line indicating the position of the upper side of the aortic arch of the patient. The position of the aortic arch may be specified by the user or may be extracted by analyzing a CT image. The auxiliary line 405 is an auxiliary line indicating the branch position of the bronchus. The branch position of the bronchus may be specified by the user or may be extracted by analyzing the CT image. The auxiliary line 406 is an auxiliary line indicating a position separated from the position of the diaphragm by a predetermined distance. The predetermined distance is, for example, 3 centimeters. This position may also be specified by the user or may be extracted by analyzing the CT image. The positions of these auxiliary lines 404 to 406 are the positions defined by the Goddard method described above.

In step S306, the CPU 201 of the medical image diagnosis support device 100 determines whether or not to align the plurality of graphs generated in step S305. If it is determined that the graph is to be aligned, the process proceeds to step S307, and if not, the process proceeds to step S308. The determination as to whether or not to align the graph may be made based on whether or not the user has previously received an instruction as to whether or not to align the graph, or a pop-up displayed on the display 210. The judgment may be made by instructing the user on the screen.

An example of the screen displayed in step S308 when it is determined in step S306 that the graph alignment is not performed will be described. In step S308, the CPU 201 of the medical image diagnosis support device 100 displays the graphs generated in step S305 in a comparable manner. For example, in FIG. 6, the graph 601 of CT image A (corresponding to the first graph) and the three-dimensional image 602, and the graph 603 of CT image B (corresponding to the second graph) and the three-dimensional image 604 are arranged in parallel. It is displayed. Although a plurality of graphs are separately displayed in parallel, a plurality of graphs may be superimposed and displayed within the same area.

When the graphs based on the CT images taken at different timings are compared and displayed without adjustment, it can be seen that the corresponding cross sections are displaced as shown in FIG. 6 at the positions of the auxiliary lines 404 to 406. This is due to the characteristic of the lung, that the lower part of the lung is more susceptible to the size of the lung by breathing than the upper part of the lung. The section from the highest position of the lung to the auxiliary line 404, the section from the auxiliary line 404 to the auxiliary line 405, the section from the auxiliary line 405 to the auxiliary line 406, the section from the auxiliary line 406 to the lowest position of the lung, etc. Comparing the length of the section between the graph 601 and the graph 603, the section from the uppermost position of the lung to the auxiliary line 404, the section from the auxiliary line 404 to the auxiliary line 405, and the section from the auxiliary line 405 to the auxiliary line 406. It can be seen that the rate of change in the size of the sections differs (increases) between the graphs 601 and the graph 603 in order. Therefore, even if the graph 601 and the three-dimensional image 602 of the CT image A and the graph 603 and the three-dimensional image 604 of the CT image B are displayed in parallel as shown in FIG. 6, the corresponding positional relationship between the two graphs is maintained. Since it is not retained, doctors have had to find and compare the corresponding positions.

In step S307, the CPU 201 of the medical image diagnosis support device 100 performs an alignment process for aligning a plurality of graphs created in step S305. The detailed flow of the alignment process will be described with reference to the flowchart of FIG.

FIG. 5 is a flowchart illustrating a detailed processing flow of the alignment process.

In step S501, the CPU 201 of the medical image diagnosis support device 100 performs a process of specifying the reference position (corresponding to the reference cross section) of the graph created in step S305 (corresponding to the specific means).

The method of specifying the reference position of the graph will be described. The reference position indicates a position specified based on another part of the patient's body structure different from the lung, and is, for example, the position of the auxiliary lines 404, 405, and 406 described above. These positions are relative to the body structure even if the size of the lungs fluctuates due to the respiratory movement of the lungs as described above.

In step S502, the CPU 201 of the medical image diagnosis support device 100 performs a process of specifying a section in the graph 601 of the CT image A and the graph 603 of the CT image B based on the position specified in step S501 (classification). Corresponds to means). The section of the graph is the section from the highest position of the lung to the auxiliary line 404, the section from the auxiliary line 404 to the auxiliary line 405, the section from the auxiliary line 405 to the auxiliary line 406, and the section from the auxiliary line 406 to the lowest position of the lung. It is a section of. Sections 701 and 711, section 702 and section 712, section 703 and section 713, and section 704 and section 714, which are shown in 700A of FIG. 7, are sections that correspond to each other in graph 601 and graph 603, respectively.

In step S503, the CPU 201 of the medical image diagnosis support device 100 performs a process of aligning the corresponding sections of the sections specified in step S502 (corresponding to the adjusting means). Specifically, it is a process of making the lengths of the corresponding sections the same. In the present embodiment, the length of the section of the graph 601 adjusts the length of the corresponding section of the graph 603.

More specifically with reference to 700A in FIG. 7, the length of the section 711 is the same as that of the section 701, the length of the section 712 is the same as that of the section 702, the length of the section 713 is the same as that of the section 703, and the length of the section 714 The process of making the length the same as the section 704 is performed. Specifically, in order to make it the same as the length of the section 701, a process of widening or narrowing the plot interval of the graph is performed. The method of adjusting the length between the sections may be another method.

An example after performing the process of performing the alignment in step S503 is 700B shown in FIG. 7. As shown in 700B, when the graph is displayed in parallel (may be superimposed) by adjusting the length of the graph for each section specified based on other parts of the patient's body structure that are different from the lungs. In addition, there is an effect that the doctor can recognize the progress of the disease of a specific organ at a glance.

This is the end of the explanation of the flowchart shown in FIG.
Returning to the description of the flowchart of FIG.

In step S308, the CPU 201 of the medical image diagnosis support device 100 displays the graph generated in step S305 on the display 210 in a comparable manner (corresponding to the display control means). In the present embodiment, the graphs are displayed in parallel, but the graphs may be superimposed. For example, it is a screen example shown in FIG. FIG. 6 is a screen example when the alignment process of step S307 is not performed, and the graph 601 and graph 603 of FIG. 6 are replaced with the graphs 601 and 603 of 700B of FIG. This is an example of a screen when the alignment process of is performed.

In this way, if the alignment is not performed, the graphs do not correspond to each other, so when comparing the graphs, the user (doctor, etc.) must specify the corresponding part in consideration of the characteristics of the lungs. I had to. By displaying the screen whose length is adjusted for each section of the graph on the display 210, the size does not change uniformly depending on the timing when a medical image such as a lung is taken, but the size changes for each section. Even if the organ has a change in size due to a change in the rate of fluctuation, it is possible to provide a mechanism capable of appropriately recognizing the progress of the disease to the user (doctor, etc.).

In step S309, the CPU 201 of the medical image diagnosis support device 100 determines whether or not the report output instruction has been received from the user. If it is determined that the report output instruction has been accepted, the process proceeds to step S310, and if not, the process proceeds to step S312.

In step S310, the CPU 201 of the medical image diagnosis support device 100 receives input of findings from the user via the input screen of findings regarding the graph displayed in a comparable manner in step S308 according to the determination in step S309. The post-processing that accepts the input of the findings proceeds to step S311.

In step S311, the CPU 201 of the medical image diagnosis support device 100 performs a process of outputting a report including the graph displayed in comparison in step S308 and the findings of which the input was accepted in step S310. For example, report 800 shown in FIG. The report 800 includes a patient column 803 showing patient information (for example, patient information obtained from DICOM information), a finding column 804 in which the findings received in step S310 are entered, and a graph 601 displayed in a comparable manner. And the graph 603 are displayed in parallel (the graph may be superimposed). Scores 801 and 802 based on the Goddard method corresponding to each graph are also displayed. In this way, there is an effect that it is possible to output a report that shows the progress of the patient's disease at a glance. In the report of FIG. 8, the display of the coronal cross-sectional image is omitted, but the coronal cross-sectional image may be displayed in parallel. The output report 800 may be stored in the external memory 211 or may be transmitted to the server.

In step S312, the CPU 201 of the medical image diagnosis support device 100 determines whether or not the end instruction has been received from the user. If it is determined that the end instruction has been accepted, the process is terminated, and if not, the process is returned to step S309.

This is the end of the explanation of the flowchart shown in FIG.

As described above, according to the present invention, the user can intuitively recognize the progress of the lesion portion of the organ.

The present invention can be, for example, an embodiment as a system, an apparatus, a method, a program, a storage medium, or the like, and specifically, may be applied to a system composed of a plurality of devices, or 1 It may be applied to a device consisting of two devices. The present invention includes a software program that realizes the functions of the above-described embodiments, which is directly or remotely supplied to a system or an apparatus. The present invention also includes a case where the information processing device of the system or the device is also achieved by reading and executing the supplied program code.

Therefore, in order to realize the functional processing of the present invention in the information processing device, the program code itself installed in the information processing device also realizes the present invention. That is, the present invention also includes a computer program itself for realizing the functional processing of the present invention.

In that case, as long as it has a program function, it may be in the form of an object code, a program executed by an interpreter, script data supplied to the OS, or the like.

Recording media for supplying programs include, for example, flexible disks, hard disks, optical disks, optical magnetic disks, MOs, CD-ROMs, CD-Rs, CD-RWs, and the like. There are also magnetic tapes, non-volatile memory cards, ROMs, DVDs (DVD-ROM, DVD-R) and the like.

In addition, as a program supply method, a browser of a client computer is used to connect to an Internet homepage. Then, the computer program itself of the present invention or a compressed file including the automatic installation function can be supplied from the homepage by downloading it to a recording medium such as a hard disk.

It can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from different homepages. That is, the present invention also includes a WWW server that allows a plurality of users to download a program file for realizing the functional processing of the present invention in the information processing apparatus.

In addition, the program of the present invention is encrypted, stored in a storage medium such as a CD-ROM, distributed to users, and the key information for decrypting the encryption is downloaded from the homepage to the user who clears the predetermined conditions. Let me. Then, by using the downloaded key information, it is also possible to execute an encrypted program and install it in the information processing device.

Further, the function of the above-described embodiment is realized by the information processing apparatus executing the read program. In addition, based on the instruction of the program, the OS or the like running on the information processing apparatus performs a part or all of the actual processing, and the function of the above-described embodiment can be realized by the processing.

Further, the program read from the recording medium is written to the memory provided in the function expansion board inserted in the information processing device and the function expansion unit connected to the information processing device. After that, based on the instruction of the program, the function expansion board, the CPU provided in the function expansion unit, or the like performs a part or all of the actual processing, and the function of the above-described embodiment is also realized by the processing.

It should be noted that the above-described embodiments merely show examples of embodiment in carrying out the present invention, and the technical scope of the present invention should not be construed in a limited manner by these. That is, the present invention can be implemented in various forms without departing from the technical idea or its main features.

100 Medical image diagnosis support device 201 CPU
202 RAM
203 ROM
204 System Bus 205 Input Controller 206 Video Controller 207 Memory Controller 208 Communication I / F Controller 209 Keyboard 210 Display 211 External Memory

Claims (8)

A first medical image group including the target organ of the subject, the first A has been medical image photographed in the medical images with different times, the subject said subject organs including second medical of An acquisition method for acquiring an image group and
A first that associates the proportion of lesions in the cross section of the target organ of the first medical image group acquired by the acquisition means with the position of each slice image constituting the first medical image group in the subject. and graphs, generating a second graph for associating the position in the subject of each slice images constituting ratio and the second medical image group of a lesion in the target organ of the cross section of the second medical image group Graph generation means and
The position of the target organ in the first medical image group is determined based on another part of the cross section of the target organ of the first medical image group, which is different from the target organ of the subject. identified as the position of the reference section, of a cross section of the target organ of the second medical images, the position determined based on the other site, the target organ in the second medical image group specifying means for specifying as the position of the reference section of,
When the first graph and the second graph generated by the graph generation means are displayed on the screen, the position of the reference cross section of the target organ in the first medical image group and the second medical image group are displayed. A medical image comprising: a display control means for controlling to display the screen in which the first graph and the second graph are aligned according to the position of the reference cross section of the target organ in the image group. Diagnostic support device. A dividing means for dividing the first graph and the second graph into a plurality of sections based on the position of the reference cross section specified by the specific means.
Based on the position of the reference plane specified by said specifying means, said plurality of sections of divided has been the first graph and the second graph the division unit performs each aligned with a corresponding section among The medical image diagnosis support device according to claim 1, further comprising an adjusting means. The medical image diagnosis support device according to claim 1 or 2, wherein the ratio of the lesion portion is a ratio to the organ parenchyma for each cross section. The target organ is the lung,
The medical image diagnosis support device according to any one of claims 1 to 3, wherein the position of the reference cross section specified by the specific means is the position of the aortic arch of the subject. The target organ is the lung,
The medical image diagnosis support device according to any one of claims 1 to 3, wherein the position of the reference cross section specified by the specific means is a position where the bronchus of the lung branches. The target organ is the lung,
The medical image diagnosis support according to any one of claims 1 to 3, wherein the position of the reference cross section specified by the specific means is a position determined based on the position of the diaphragm of the subject. apparatus. Medical image diagnosis support device
A first medical image group including the target organ of the subject, the first A has been medical image photographed in the medical images with different times, the subject said subject organs including second medical of The acquisition step to acquire the image group and
A first that associates the proportion of lesions in the cross section of the target organ of the first medical image group acquired in the acquisition step with the position of each slice image constituting the first medical image group in the subject. and graphs, generating a second graph for associating the position in the subject of each slice images constituting ratio and the second medical image group of a lesion in the target organ of the cross section of the second medical image group Graph generation steps to be performed and
The position of the target organ in the first medical image group is determined based on another part of the cross section of the target organ of the first medical image group, which is different from the target organ of the subject. identified as the position of the reference section, of a cross section of the target organ of the second medical images, the position determined based on the other site, the target organ in the second medical image group a specifying step of specifying as the position of the reference section of,
When the first graph and the second graph generated in the graph generation step are displayed on the screen, the position of the reference cross section of the target organ in the first medical image group and the second medical image group are displayed. A medical image comprising: a display control step for controlling to display the screen in which the first graph and the second graph are aligned according to the position of the reference cross section of the target organ in the image group. Control method of diagnostic support device. Medical image diagnosis support device,
A first medical image group including the target organ of the subject, the first A has been medical image photographed in the medical images with different times, the subject said subject organs including second medical of An acquisition method for acquiring an image group and
A first that associates the proportion of lesions in the cross section of the target organ of the first medical image group acquired by the acquisition means with the position of each slice image constituting the first medical image group in the subject. and graphs, generating a second graph for associating the position in the subject of each slice images constituting ratio and the second medical image group of a lesion in the target organ of the cross section of the second medical image group Graph generation means and
The position of the target organ in the first medical image group is determined based on another part of the cross section of the target organ of the first medical image group, which is different from the target organ of the subject. identified as the position of the reference section, of a cross section of the target organ of the second medical images, the position determined based on the other site, the target organ in the second medical image group specifying means for specifying as the position of the reference section of,
When the first graph and the second graph generated by the graph generation means are displayed on the screen, the position of the reference cross section of the target organ in the first medical image group and the second medical image group are displayed. A medical image characterized in that it functions as a display control means for controlling the display of the screen in which the first graph and the second graph are aligned according to the position of the reference cross section of the target organ in the image group. A program that can be executed by a diagnostic support device.

Images