JP2022073262A - Medical image processing device, medical image processing method, and program - Google Patents

Abstract

To provide information regarding a biological organ or a valve with a tubular structure.SOLUTION: A medical image processing device according to embodiment comprises an acquisition part, an axis setting part, a condition setting part, and a specification part. The acquisition part acquires a medical image containing a blood vessel or a valve. The axis setting part sets a plurality of axes on the basis of the blood vessel or the valve. The condition setting part sets a condition regarding a closed curve corresponding to the blood vessel or the valve. The specification part specifies the closed curve based on the axes or an area surrounded by the closed curve, on the basis of the condition.SELECTED DRAWING: Figure 2

Description

Embodiments disclosed herein and in the drawings relate to medical image processing devices, medical image processing methods and programs.

In the patient's body, there are various organs through which fluids or solids flow, such as biological organs or valves having a tubular structure such as blood vessels and esophagus. Information such as measured values in the organ is useful information for making a diagnosis. However, the organ is not always in a simple cylindrical shape, and it is not easy to obtain information such as measured values.

Japanese Unexamined Patent Publication No. 2004-283373 Japanese Unexamined Patent Publication No. 2020-76967

One of the challenges to be solved by the embodiments disclosed herein and in the drawings is to provide information about living organs or valves having a tubular structure. However, the problems to be solved by the embodiments disclosed in the present specification and the drawings are not limited to the above problems. The problem corresponding to each effect by each configuration shown in the embodiment described later can be positioned as another problem.

The medical image processing apparatus of the embodiment includes an acquisition unit, an axis setting unit, a condition setting unit, and a specific unit. The acquisition unit acquires a medical image including a blood vessel or a valve. The axis setting unit sets a plurality of axes based on the blood vessel or valve. The condition setting unit sets conditions related to the closed curve corresponding to the blood vessel or valve. Based on the above conditions, the specific unit specifies a closed curve based on the plurality of axes or a region surrounded by the closed curve.

FIG. 1 is a block diagram showing an example of the configuration of the medical image processing system according to the first embodiment. FIG. 2 is a flowchart showing an example of processing by the processing circuit of the medical image processing apparatus according to the first embodiment. FIG. 3 is a diagram showing an example of a region of interest according to the first embodiment. FIG. 4A is a flowchart showing an example of a process related to axis setting in the axis setting function according to the first embodiment. FIG. 4B is a diagram for explaining a method of setting an axis according to the first embodiment. FIG. 4C is a diagram for explaining a method of setting an axis according to the first embodiment. FIG. 4D is a diagram for explaining a method of setting an axis according to the first embodiment. FIG. 5A is a diagram showing an example of an end point setting method according to the first embodiment. FIG. 5B is a diagram showing an example of an end point setting method according to the first embodiment. FIG. 6A is a diagram for explaining the setting of the closed curve condition according to the first embodiment. FIG. 6B is a diagram for explaining the setting of the closed curve condition according to the first embodiment. FIG. 7A is a diagram for explaining the setting of evaluation points according to the first embodiment. FIG. 7B is a diagram for explaining the setting of evaluation points according to the first embodiment. FIG. 8A is a diagram showing a display example according to the first embodiment. FIG. 8B is a diagram showing a display example according to the first embodiment. FIG. 8C is a diagram showing a display example according to the first embodiment. FIG. 8D is a diagram showing a display example according to the first embodiment. FIG. 9 is a diagram showing a display example according to the first embodiment. FIG. 10 is a diagram showing an example of an intravascular stenosis site according to the first embodiment. FIG. 11 is a diagram showing a display example according to the first embodiment. FIG. 12 is a diagram showing an example of a shaft setting method according to the first embodiment. FIG. 13A is a diagram showing an example of a method for setting a closed curve condition according to the first embodiment. FIG. 13B is a diagram showing an example of a method for setting a closed curve condition according to the first embodiment. FIG. 14 is a diagram for explaining a method of setting the axis according to the fourth embodiment.

Hereinafter, the medical image processing apparatus, the medical image processing method, and the embodiment of the program will be described in detail with reference to the attached drawings.

(First Embodiment)
In the present embodiment, the medical image processing system 1 including the medical image processing device 20 will be described as an example. For example, the medical image processing system 1 includes a medical image diagnostic device 10, a medical image processing device 20, and an image storage device 30, as shown in FIG. FIG. 1 is a block diagram showing an example of the configuration of the medical image processing system 1 according to the first embodiment. The medical image diagnosis device 10, the medical image processing device 20, and the image storage device 30 are connected to each other via a network NW.

If the connection is possible via the network NW, the place where each device included in the medical image processing system 1 is installed is arbitrary. For example, the medical image diagnosis device 10, the medical image processing device 20, and the image storage device 30 may be installed in different facilities from each other. That is, the network NW may be configured by a local network closed in the facility, or may be a network via the Internet.

The medical image diagnostic device 10 is a device that takes an image of a patient and collects a medical image including a biological organ or a valve having a tubular structure. In this embodiment, as an example, a case where a medical image including a mitral valve is collected will be described. That is, in the present embodiment, the mitral valve will be described as a target organ.

The medical image diagnostic apparatus 10 includes, for example, 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) apparatus. computed Tomography) A medical modality such as a device. Although FIG. 1 shows a single medical image diagnostic device 10, the medical image processing system 1 may include a plurality of medical image diagnostic devices 10. Further, the medical image processing system 1 may include a plurality of types of medical image diagnostic devices 10. For example, the medical image processing system 1 may include an X-ray CT device and an MRI device as the medical image diagnosis device 10.

The image storage device 30 is an image database that stores medical images collected by the medical image diagnostic device 10. For example, the image storage device 30 is provided with an arbitrary storage device inside or outside the device, and manages medical images acquired from the medical image diagnostic device 10 via the network NW in the form of a database. For example, the image storage device 30 is a server of a PACS (Picture Archiving and Communication System). Further, the image storage device 30 may be realized by a server group (cloud) connected to the medical image processing system 1 via a network NW.

The medical image processing device 20 is a device that performs various processes described later in order to be able to provide information about a biological organ or a valve having a tubular structure. For example, the medical image processing apparatus 20 acquires a medical image including a mitral valve, sets a plurality of axes based on the mitral valve, sets a condition regarding a closed curve corresponding to the mitral valve, and sets the set condition. Based on this, a closed curve based on a plurality of set axes or a region surrounded by the closed curve is specified. For example, the medical image processing apparatus 20 includes a memory 21, a display 22, an input interface 23, and a processing circuit 24, as shown in FIG.

The memory 21 is realized by, for example, a RAM (Random Access Memory), a semiconductor memory element such as a flash memory, a hard disk, an optical disk, or the like. For example, the memory 21 stores medical images collected by the medical diagnostic imaging apparatus 10. Further, the memory 21 stores a program for the circuit included in the medical image processing device 20 to realize its function.

The display 22 displays various information. For example, the display 22 displays a GUI (Graphical User Interface) for receiving various instructions, settings, and the like from the user via the input interface 23. Further, the display 22 displays information such as a closed curve or a region specified by the processing circuit 24, or a measured value acquired based on the closed curve or the region. For example, the display 22 is a liquid crystal display or a CRT (Cathode Ray Tube) display. The display 22 may be a desktop type, or may be composed of a tablet terminal or the like capable of wireless communication with the main body of the medical image processing device 20.

Although it is assumed that the medical image processing device 20 includes the display 22 in FIG. 1, the medical image processing device 20 may include a projector in place of or in addition to the display 22. The projector can project onto a screen, a wall, a floor, a patient's body surface, or the like under the control of the processing circuit 24. As an example, the projector can also project onto an arbitrary plane, object, space, etc. by projection mapping.

The input interface 23 receives various input operations from the user, converts the received input operations into electric signals, and outputs the received input operations to the processing circuit 24. For example, the input interface 23 includes a mouse, a keyboard, a trackball, a switch, a button, a joystick, a touch pad for performing an input operation by touching an operation surface, a touch screen in which a display screen and a touch pad are integrated, and an optical sensor. It is realized by the non-contact input circuit, voice input circuit, etc. used. The input interface 23 may be composed of a tablet terminal or the like capable of wireless communication with the main body of the medical image processing device 20. Further, the input interface 23 may be a circuit that accepts an input operation from the user by motion capture. As an example, the input interface 23 can receive the user's body movement, line of sight, and the like as an input operation by processing the signal acquired through the tracker and the image collected about the user. Further, the input interface 23 is not limited to the one provided with physical operation parts such as a mouse and a keyboard. For example, an electric signal processing circuit that receives an electric signal corresponding to an input operation from an external input device provided separately from the medical image processing device 20 and outputs the electric signal to the processing circuit 24 is also an input interface 23. Included in the example.

The processing circuit 24 controls the operation of the entire medical image processing apparatus 20 by executing the control function 24a, the acquisition function 24b, the axis setting function 24c, the condition setting function 24d, the specific function 24e, and the output function 24f. The acquisition function 24b is an example of an acquisition unit. The axis setting function 24c is an example of the axis setting unit. The condition setting function 24d is an example of the condition setting unit. The specific function 24e is an example of a specific unit. The output function 24f is an example of an output unit.

For example, the processing circuit 24 reads a program corresponding to the control function 24a from the memory 21 and executes it, and based on various input operations received from the user via the input interface 23, the acquisition function 24b and the axis setting function. It controls various functions such as 24c, a condition setting function 24d, a specific function 24e, and an output function 24f.

Further, the processing circuit 24 acquires a medical image including a mitral valve by reading a program corresponding to the acquisition function 24b from the memory 21 and executing the program. For example, the acquisition function 24b receives the medical image captured by the medical image diagnostic apparatus 10 via the network NW and stores it in the memory 21. Here, the acquisition function 24b may acquire the medical image directly from the medical image diagnosis device 10 or may acquire the medical image via the image storage device 30.

Further, the processing circuit 24 sets a plurality of axes by reading a program corresponding to the axis setting function 24c from the memory 21 and executing the program. Further, the processing circuit 24 sets the conditions related to the closed curve by reading the program corresponding to the condition setting function 24d from the memory 21 and executing the program. Further, the processing circuit 24 reads a program corresponding to the specific function 24e from the memory 21 and executes it, so that the closed curve based on a plurality of set axes or a region surrounded by the closed curve is surrounded based on the set conditions. To identify. Further, the processing circuit 24 reads a program corresponding to the output function 24f from the memory 21 and executes the program to output the output based on the specified closed curve or region. Details of processing by the axis setting function 24c, the condition setting function 24d, the specific function 24e, and the output function 24f will be described later.

In the medical image processing apparatus 20 shown in FIG. 1, each processing function is stored in the memory 21 in the form of a program that can be executed by a computer. The processing circuit 24 is a processor that realizes a function corresponding to each program by reading a program from the memory 21 and executing the program. In other words, the processing circuit 24 in the state where the program is read has a function corresponding to the read program.

In FIG. 1, it has been described that the control function 24a, the acquisition function 24b, the axis setting function 24c, the condition setting function 24d, the specific function 24e, and the output function 24f are realized by a single processing circuit 24. Independent processors may be combined to form a processing circuit 24, and each processor may execute a program to realize a function. Further, each processing function of the processing circuit 24 may be appropriately distributed or integrated into a single or a plurality of processing circuits.

Further, the processing circuit 24 may realize the function by using the processor of the external device connected via the network NW. For example, the processing circuit 24 reads a program corresponding to each function from the memory 21 and executes it, and also uses a server group (cloud) connected to the medical image processing device 20 via a network NW as a computational resource. , Each function shown in FIG. 1 is realized.

The configuration example of the medical image processing system 1 including the medical image processing device 20 has been described above. Under such a configuration, the processing circuit 24 in the medical image processing apparatus 20 makes it possible to provide information about the mitral valve.

Hereinafter, the processing performed by the processing circuit 24 will be described with reference to the flowchart of FIG. FIG. 2 is a flowchart showing an example of processing by the processing circuit 24 of the medical image processing apparatus 20 according to the first embodiment.

First, the acquisition function 24b acquires a medical image including the mitral valve (step S1). The acquisition function 24b may acquire the medical image directly from the medical image diagnostic device 10 or may acquire the medical image via another device such as the image storage device 30.

The type of medical image is not particularly limited. For example, the acquisition function 24b acquires an X-ray CT image, an ultrasonic image, an MRI image, an X-ray image, a PET image, a SPECT image, or the like as a medical image including a mitral valve. In addition, the acquisition function 24b can also acquire any kind of image in which morphological information of the three-dimensional anatomical structure of the mitral valve is stored as a medical image including the mitral valve. Further, the acquisition function 24b may acquire a four-dimensional image obtained by capturing a plurality of three-dimensional images of the mitral valve in the time direction as a medical image including the mitral valve.

As an example, the acquisition function 24b acquires a medical image by using an instruction received from the user via the input interface 23 as a trigger. As another example, in the acquisition function 24b, a medical image including the mitral valve is captured by the medical image diagnostic device 10, or a medical image including the mitral valve is stored in the image storage device 30. Is used as a trigger to acquire a medical image. That is, the acquisition function 24b may automatically acquire the newly collected medical image.

Further, the acquisition function 24b may acquire the medical image when the newly collected medical image satisfies a predetermined condition. For example, the acquisition function 24b sets the imaging protocol as a predetermined condition, and acquires the medical image when the image is captured by the imaging protocol targeting the heart. Further, for example, the acquisition function 24b sets the reconstruction method as a predetermined condition, and acquires the medical image when the enlarged reconstruction is performed. Further, the acquisition function 24b may combine a plurality of items such as an imaging protocol and a reconstruction method to set predetermined conditions, and acquire a medical image when the predetermined conditions are satisfied.

Next, the axis setting function 24c acquires the region of interest in the medical image acquired by the acquisition function 24b (step S2). Here, the region of interest is the region indicated by the biological organ of interest in the medical image. For example, the axis setting function 24c acquires the coordinate information of each pixel indicating the mitral valve in the medical image as a region of interest. That is, the axis setting function 24c acquires a region of interest from a medical image based on the anatomical features of the mitral valve.

As an example, the output function 24f causes the display 22 to display a medical image. Then, the axis setting function 24c acquires the region of interest by receiving an operation of designating the position of the region of interest from the user via the input interface 23.

To give another example, the axis setting function 24c acquires a region of interest based on the anatomical structure depicted in a medical image by a known region extraction technique. Examples of known region extraction techniques include a discriminant analysis method based on pixel values such as CT values (also called Otsu's method), region expansion method, snake method, graph cut method, and mean shift method. can.

In addition, the axis setting function 24c can acquire the region of interest by any method. For example, the axis setting function 24c can also acquire a region of interest by machine learning techniques such as deep learning. As an example, the axis setting function 24c may acquire the region of interest by using the shape model of the region of interest constructed based on the learning data prepared in advance.

Further, the axis setting function 24c may first acquire a region larger than the region of interest but smaller than the entire image (hereinafter referred to as a related region), and may acquire the region of interest from the related region. For example, when the mitral valve is the target organ, the axis setting function 24c acquires the heart region, the sum region of the left atrium and the left ventricle, and the like as related regions in the entire image. For example, the axis setting function 24c can acquire a related area by accepting an operation from a user via the input interface 23. Then, the axis setting function 24c applies a process such as a graph cut method to the related area to acquire the area of interest. As a result, the calculation cost can be reduced as compared with the case where processing such as the graph cut method is performed on the entire image. Further, by limiting the processing target to the related area, it is possible to acquire the area of interest by a method having a higher calculation load, so that the area of interest can be acquired with higher accuracy.

For example, the acquisition function 24b acquires the medical image I1 shown in FIG. Further, the axis setting function 24c acquires the mitral valve region R1 from the medical image I1 based on the mitral valve. That is, the axis setting function 24c acquires the mitral valve region R1 from the medical image I1 based on the anatomical features of the mitral valve. The mitral valve region R1 is an example of a region of interest. Further, FIG. 3 is a diagram showing an example of a region of interest according to the first embodiment.

Next, the axis setting function 24c sets a plurality of axes based on the mitral valve (step S3). That is, the axis setting function 24c sets a plurality of axes based on the anatomical features of the mitral valve. For example, the axis setting function 24c sets a plurality of axes based on the mitral valve region R1 of FIG. That is, the axis setting function 24c sets a plurality of axes along the shape of the acquired mitral valve region R1.

Hereinafter, the axis setting by the axis setting function 24c will be described with reference to FIGS. 4A to 4D.
FIG. 4A is a flowchart showing an example of a process related to axis setting in the axis setting function 24c according to the first embodiment. In addition, step S31, step S32 and step S33 of FIG. 4A are steps included in step S3 of FIG. Further, FIGS. 4B, 4C and 4D are diagrams for explaining a method of setting an axis according to the first embodiment.

First, the shaft setting function 24c specifies the tip shape D1 and the annulus shape D2 as shown in FIG. 4B (step S31). The tip shape D1 specifies, for example, a region (pixel) indicating the tip of the valve as a closed curve. Further, the annulus shape D2 specifies a region (pixel) indicating the annulus as a closed curve. In FIG. 4B, the tip shape D1 and the annulus shape D2 are shown as a two-dimensional closed curve, but the tip shape D1 and the annulus shape D2 are usually three-dimensional closed curves accompanied by a change in the depth direction. The tip shape D1 is an example of the first closed curve. Further, the annulus shape D2 is an example of the second closed curve.

The method for specifying the tip shape D1 and the annulus shape D2 is not particularly limited. For example, the axis setting function 24c can specify the tip shape D1 and the annulus shape D2 based on the number of pixels belonging to the region of interest adjacent to the pixel in each pixel. In other words, the axis setting function 24c can specify a region adjacent to a large number of pixels belonging to a region other than the region of interest as the tip shape D1 and the annulus shape D2.

To give another example, the axis setting function 24c specifies the pixel located at the lowermost end or the upper end in each pixel row (voxel row or pixel row) in a predetermined direction as the tip shape D1 and the annulus shape D2. You may. Here, the predetermined direction is a direction from the tip of the valve toward the annulus or a direction from the annulus toward the tip of the valve.

For example, the predetermined direction may be determined based on image incidental information such as a DICOM (Digital Imaging and Communications in Medicine) header, or may be specified by the user using the input interface 23. Further, when the user specifies a predetermined direction, the UI (User Interface) may be a form in which the user directly specifies the direction, or a form in which the direction from the front to the back of the display screen is set as the predetermined direction. good. As an example, the output function 24f rotatably displays the mitral valve region R1, which is three-dimensional data, on the display 22. Further, the user rotates the mitral valve region R1 so that the opening of the mitral valve can be visually recognized, for example, as shown in FIGS. 4B to 4D. Then, the axis setting function 24c sets the direction from the front to the back of the display 22 as a predetermined direction based on the direction of the mitral valve region R1 after rotation.

Next, the axis setting function 24c sets an end point for each closed curve, for example, as shown in FIG. 4C (step S32). For example, the shaft setting function 24c sets the same number of end points for each of the tip shape D1 and the annulus shape D2 based on predetermined conditions. That is, the shaft setting function 24c sets 10 end points of the end points E101 to E110 for the tip shape D1 and sets 10 end points of the end points E201 to E210 for the annulus shape D2. The predetermined condition for setting the end point may be a fixed condition or may be set each time.

Predetermined conditions for setting the end points can be set by using, for example, the GUI shown in FIG. 5A. FIG. 5A is a diagram showing an example of an end point setting method according to the first embodiment. First, the output function 24f causes the GUI shown in FIG. 5A to be displayed on the display 22. Next, the axis setting function 24c receives input of each item shown in FIG. 5A from the user via the input interface 23. That is, the axis setting function 24c receives the input of the starting point when setting a plurality of end points in order and the condition when setting a plurality of end points by the GUI shown in FIG. 5A, thereby receiving the tip shape D1 or the annulus. A plurality of endpoints can be set for each of the shapes D2.

For example, the user inputs the directions (vectors) of the "tip" and "valley" as the starting point. When the item "linking the tip and the annulus" is checked, the axis setting function 24c reflects the direction input for either the "tip" or the "valve" to the other. For example, when the starting point directions of the "tip" and the "valve ring" are "90 degrees", the axis setting function 24c is located at the "90 degrees" position with respect to the reference point, as shown in FIG. 5B, at the starting point E111 and The starting point E211 is set. The starting point E111 is one of the end points set for the tip shape D1, and the starting point E211 is one of the end points set for the annulus shape D2. Further, FIG. 5B is a diagram showing an example of an end point setting method according to the first embodiment. In FIG. 5B, the direction on the screen is described as the reference direction (0 degree), but the embodiment is not limited to this, and the reference is based on, for example, the center of gravity or the center of the tip shape D1 or the annulus shape D2. You may decide the direction.

The method of setting the reference point is arbitrary. For example, the reference point may be the center of the display screen, or may be the center of the tip shape D1 or the annulus shape D2 or a coordinate point indicating the center of gravity. When the tip shape D1 and the annulus shape D2 are three-dimensional closed curves, the coordinate points indicating the center and the center of gravity of the tip shape D1 or the annulus shape D2 are projected perpendicularly to the cross section displayed on the display 22. The position may be used as a reference point. Further, the reference point may be specified by the user.

After setting the starting point, the axis setting function 24c sets a plurality of endpoints according to the setting of the "condition" in FIG. 5A. For example, when "number: 10" is set as shown in FIG. 5A, the axis setting function 24c sets the remaining nine end points on the tip shape D1 at regular intervals from the starting point E111. In this case, the longer the tip shape D1, the longer the distance between the end points. Similarly, the axis setting function 24c sets the remaining nine end points on the annulus shape D2 at regular intervals from the starting point E211.

Although the case where a plurality of end points are set at regular intervals has been described, the embodiment is not limited to this. For example, the axis setting function 24c may set a plurality of end points based on the starting point position, the set number, and the shape information of the closed curve. For example, the axis setting function 24c may calculate the curvature at each position of the closed curve as the shape information of the closed curve, and set a set number of endpoints in order from the position where the curvature is large or small.

Further, although the case where the starting point is set based on the reference point and the direction (vector) has been described, the starting point may be set manually by the user. For example, the user can set the starting point at an arbitrary position of the tip shape D1 or the annulus shape D2 via the input interface 23. For example, the output function 24f may display the starting point at an arbitrary position of the tip shape D1 or the annulus shape D2, and the user may operate the mouse pointer M shown in FIG. 5B to move the starting point position. That is, the axis setting function 24c may accept the user operation for displaying the tip shape D1 or the annulus shape D2 as the input of the starting point. Alternatively, the starting point may be set in advance. For example, the position in the direction on the screen may always be the starting point.

Further, although the case where the number of end points is set has been described in FIG. 5A, the “tip end point interval” and the “valley end point interval” may be set. That is, the axis setting function 24c may set the minimum distance between adjacent end points in the tip shape D1 or the annulus shape D2, the number of pixels, and the like.

When the "tip end point interval" is set, the axis setting function 24c sets a plurality of end points on the tip shape D1 at the set interval from the starting point. For example, the axis setting function 24c calculates the maximum number of end points that can be set at equal intervals and the distance between each end point is smaller than the set distance based on the length of the tip shape D1, and all the end points are set to the tip shape. Set on D1 and set the same number of endpoints on the annulus shape D2 at equal intervals. Similarly, when the "valley end point spacing" is set, a plurality of end points can be set for the tip shape D1 and the annulus shape D2.

When setting the end points, the axis setting function 24c associates the end points on the tip shape D1 with the end points on the annulus shape D2 and records the correspondence. For example, the axis setting function 24c can record the correspondence by assigning numbers in order from the starting point in a clockwise or counterclockwise direction with respect to the starting point.

Further, the axis setting function 24c may accept corrections from the user after setting the end points. For example, as shown in FIG. 4C, after setting a plurality of endpoints for each of the tip shape D1 and the annulus shape D2, the output function 24f causes the display 22 to display the plurality of endpoints. The output function 24f may display a plurality of end points in association with an image or a schematic diagram showing the mitral valve. Then, the axis setting function 24c accepts the correction regarding the end point via the input interface 23. For example, the user can move the end points using a mouse or the like, delete some end points, or add end points.

When accepting the correction regarding the end point, the axis setting function 24c may control so that the end point on the tip shape D1 and the end point on the annulus shape D2 are interlocked with each other. For example, the shaft setting function 24c may be controlled so that when the end point on the tip shape D1 is moved, the corresponding end point on the annulus shape D2 is moved in conjunction with each other.

Further, when accepting the correction regarding the end point, the axis setting function 24c may set a restriction on the correction content. For example, when the user moves the end point, the axis setting function 24c may be controlled so as not to move beyond the set condition. For example, when the minimum distance between the end points is set, the axis setting function 24c controls so that it cannot be moved beyond the minimum distance. Further, when the number of endpoints is set, the axis setting function 24c may be controlled so that the endpoints cannot be deleted or added.

Next, the axis setting function 24c sets the axis so as to pass through the corresponding end point, for example, as shown in FIG. 4D (step S33). For example, the axis setting function 24c sets the axis A101 based on the end point E101 set on the tip shape D1 and the end point E201 corresponding to the end point E101 among the plurality of end points set on the annulus shape D2. For example, the axis setting function 24c sets a line segment having the shortest distance passing through the end points E101 and the end point E201 and along the shape of the mitral valve region R1 as the axis A101. Similarly, the axis setting function 24c sets the axes A102 to A110.

In FIG. 4C, the same number of end points are set for each of the tip shape D1 and the annulus shape D2, but the shaft setting function 24c sets different numbers of end points for the tip shape D1 and the annulus shape D2. It may be set. Further, the correspondence relationship between the end points may not be provided.

That is, the axis setting function 24c may set many end points on one closed curve so that all the end points are not used, or may set a plurality of axes passing through one end point. Further, the axis setting function 24c may set all combinations as axes. The axes to be set may intersect. However, as shown in FIG. 5A or the like, when the endpoint is set and selected based on a predetermined condition and the axis is set in step S3, information about the axis can be acquired in the process of step S5 or the like described later. In addition, information about the axis may be recorded. That is, the axis setting function 24c can record information on the start point, direction, and distance of the axis as information on the axis even if the correspondence between the end points is not recorded.

After the plurality of axes are set by each process of steps S31 to S33, the condition setting function 24d sets the condition regarding the closed curve (step S4). In the following, the conditions relating to the closed curve will also be described as the closed curve condition. Here, as an example of the closed curve condition, the peripheral length of the closed curve, the area of the area surrounded by the closed curve, the circularity of the closed curve, the diameter of the sphere inscribed in the closed curve, and the like can be exemplified. Further, the condition setting function 24d may set a condition for a two-dimensional closed curve obtained by projecting a three-dimensional closed curve onto a plane from a specific direction as a closed curve condition. For example, the condition setting function 24d may set the perimeter of the projected two-dimensional closed curve as a closed curve condition. In addition, the condition setting function 24d can set various conditions related to the morphological information (shape, area, etc.) of the closed curve as the closed curve condition. The condition setting function 24d sets one or more of these items.

Further, the closed curve condition may be a condition that can basically determine one closed curve that satisfies the condition, or may be a condition that there are a plurality of closed curves that satisfy the condition. The conditions that can determine one closed curve are, for example, a maximum value, a minimum value, a value closest to an arbitrary value, and the like. Further, the condition that there are a plurality of closed curves satisfying the condition is, for example, a condition such as an arbitrary value or more and an arbitrary value or less.

For example, the output function 24f causes the UI shown in FIG. 6A to be displayed on the display 22. Then, the condition setting function 24d sets the closed curve condition by accepting the input operation from the user. Specifically, the user selects one of items such as "perimeter", "area", and "circularity". Further, the user selects one of the contents of the conditions such as "maximum", "minimum", and "nearest neighbor to XX". When selecting the condition of "nearest neighbor to XX", the user can also input an arbitrary value "XX". For example, in the case shown in FIG. 6A, the condition setting function 24d sets a condition of "minimum area" as a closed curve condition. According to the condition, it is possible to determine one closed curve that satisfies the condition. That is, in the case shown in FIG. 6A, the condition setting function 24d displays a plurality of items and contents of the closed curve condition, accepts selection from the user for the item and the content, and sets the closed curve condition based on the accepted item and content. Set. Further, FIG. 6A is a diagram for explaining the setting of the closed curve condition according to the first embodiment.

To give another example, the output function 24f displays a UI as shown in FIG. 6B on the display 22, and the condition setting function 24d sets a closed curve condition by accepting an input operation from the user. Specifically, the user selects an arbitrary item from items such as "periphery", "area", and "circularity". Here, the user may select a plurality of items. In addition, the user inputs conditions such as a threshold value for the selected item. For example, in the case shown in FIG. 6B, the condition setting function 24d sets a condition that "the area is 10 mm ² or less and the circularity is 0.8 or more" as the closed curve condition. There may be a plurality of closed curves that satisfy the condition. That is, in the case shown in FIG. 6B, the condition setting function 24d sets the closed curve condition by displaying a plurality of items of the closed curve condition, accepting the selection from the user, and further accepting the input of the contents in the accepted item. Further, FIG. 6B is a diagram for explaining the setting of the closed curve condition according to the first embodiment.

The UI shown in FIGS. 6A and 6B is merely an example, and various modifications are possible. For example, various logical expressions (AND, OR, NOT, etc.) may be input so that more complicated conditions can be set. Further, the condition setting function 24d may automatically set a predetermined condition as a closed curve condition.

Next, the specific function 24e specifies a closed curve based on a plurality of axes set in step S3 based on the conditions set in step S4 (step S5). For example, the specific function 24e specifies a closed curve that passes through all of the plurality of axes set in step S3, based on the conditions set in step S4. In other words, the specific function 24e specifies a closed curve that satisfies the condition set in step S4 and intersects all of the plurality of axes set in step S3.

For example, the specific function 24e sets an arbitrary point for each of the plurality of axes set in step S3. Hereinafter, the arbitrary point set on the axis will be referred to as an evaluation point. Next, the specific function 24e acquires a closed curve by connecting the evaluation points on the adjacent axes at the shortest distance along the shape of the mitral valve region R1. Hereinafter, the closed curve obtained by connecting the evaluation points will be described as a closed curve candidate. In order to reduce the calculation load, the specific function 24e may use a straight line as a line segment connecting adjacent evaluation points.

Next, the specific function 24e calculates the value of the item related to the closed curve condition set in step 4 for the closed curve candidate acquired based on the evaluation points. For example, when the condition of "minimum area" is set as shown in FIG. 6A, the specific function 24e calculates the area of the closed curve candidate. Further, for example, when the condition that "the area is 10 mm ² or less and the circularity is 0.8 or more" is set as shown in FIG. 6B, the specific function 24e calculates the area and circularity of the closed curve candidate. .. Further, the specific function 24e stores the calculated value in the memory 21.

Next, the specific function 24e changes the position of the evaluation point. That is, the specific function 24e resets the evaluation point set on a certain axis to another position on the axis to which the evaluation point belongs. The specific function 24e may change the position of the evaluation point on all of the plurality of axes set in step S3, or may change the position of the evaluation point only on a part of the plurality of axes. The method of determining the position of the evaluation point on each axis to be reset is not particularly limited. However, in order to improve the efficiency of calculation, it is preferable to control so that the combination of the positions of the evaluation points and the combination of the positions of the same evaluation points on each axis for which the values of the items related to the closed curve condition are calculated are not reset. ..

For example, when a plurality of axes are set on the region of the mitral valve as shown in FIG. 7A, the specific function 24e sets a plurality of measurement points on each axis as shown in FIG. 7B. For example, measurement points are set at regular intervals on each axis. Then, the specific function 24e selects any one of the plurality of measurement points as an evaluation point for each axis. In FIGS. 7A and 7B, a plurality of axes set by the axis setting function 24c are shown by a solid line, and the tip shape D1 and the annulus shape D2 are shown by a broken line. Further, in FIG. 7B, the measurement point located at the anterior leaflet of the mitral valve is indicated by a square white dot, and the measurement point located at the posterior leaflet is indicated by a triangular white dot. Further, FIGS. 7A and 7B are diagrams for explaining the setting of the evaluation points according to the first embodiment.

For example, the specific function 24e selects any one of a plurality of measurement points as an evaluation point for each axis. Next, the specific function 24e acquires a closed curve candidate by connecting the evaluation points, and calculates the value of the item related to the closed curve condition for the closed curve candidate. Next, the specific function 24e changes the selected measurement points in a part or all of the plurality of axes, resets the evaluation points, acquires the closed curve candidates connecting the evaluation points after the resetting, and obtains the closed curve. Calculate the value of the item related to the closed curve condition for the candidate. Similarly, the specific function 24e repeatedly executes the resetting of the evaluation points and the calculation of the values of the items related to the closed curve condition.

That is, the specific function 24e sets evaluation points for each of the plurality of axes, acquires closed curve candidates by connecting the evaluation points, and repeatedly resets the evaluation points to acquire a plurality of closed curve candidates. .. Further, the specific function 24e calculates the value of the item related to the closed curve condition for each of the plurality of closed curve candidates.

In the specific function 24e, all combinations of measurement points may be processed targets, or only some combinations may be processed targets. For example, the specific function 24e may repeatedly reset the evaluation points until the values of the items related to the closed curve condition are calculated for the combination of all the measurement points in the range from the end points on each axis. Alternatively, the specific function 24e may be controlled to reset the evaluation points only within a predetermined range. For example, the specific function 24e may be controlled to reset only the measurement points from the end points to a certain distance as evaluation points. Further, the specific function 24e may be controlled so as to end the resetting of the evaluation points when it is repeated a certain number of times or a processing time.

Then, the specific function 24e specifies a closed curve that satisfies the closed curve condition based on the value of the item related to the closed curve condition. For example, when the condition of "minimum area" is set as shown in FIG. 6A, the specific function 24e acquires a plurality of closed curve candidates by repeatedly resetting the evaluation points, and each of the plurality of closed curve candidates is obtained. Calculate the area for. Then, the specific function 24e specifies the closed curve having the smallest area among the plurality of closed curve candidates as the closed curve satisfying the closed curve condition.

Further, for example, when the condition that "the area is 10 mm ² or less and the circularity is 0.8 or more" is set as shown in FIG. 6A, a plurality of specific functions 24e are obtained by repeatedly setting the evaluation points. The closed curve candidates of are obtained, and the area and circularity are calculated for each of the plurality of closed curve candidates. Then, the specific function 24e specifies a closed curve that satisfies the condition of "area is 10 mm ² or less and circularity is 0.8 or more" among a plurality of closed curve candidates. Here, the specific function 24e may specify a plurality of closed curves that satisfy the closed curve conditions.

The specific function 24e may be compared every time the evaluation points are reset. That is, the specific function 24e records the information of the closed curve candidate for calculating the value closest to the closed curve condition (the position of each evaluation point, the value of the item related to the closed curve condition, etc.), and compares it with the value in the reset closed curve candidate. However, only when the values in the reset closed curve candidates are closer, the information in the reset closed curve candidates may be recorded, and the compared information may be deleted (overwritten). For example, when the closed curve condition "minimum area" is set, the area of a certain closed curve candidate is X1, and the area of the reset closed curve candidate is X2, the specific function 24e is "X1> X2". If there is, overwriting may be performed, and if “X1 ≦ X2”, the information in the reset closed curve candidate may be discarded.

Further, the specific function 24e may acquire a plurality of closed curve candidates by repeatedly resetting the evaluation points according to the values of the items related to the closed curve conditions calculated for the closed curve candidates. For example, the specific function 24e searches for a value after moving an evaluation point on a certain axis in a certain direction when the value is farther from the closed curve condition than the value before the change. May be terminated. That is, the specific function 24e may acquire a plurality of closed curve candidates by moving the evaluation points so that the value of the item related to the closed curve condition satisfies the closed curve condition or approaches the closed curve condition.

For example, when the closed curve condition of "minimum area" is set, the area of the closed curve candidate after calculating the area for a certain closed curve candidate and then moving the evaluation point on a certain axis in a certain direction becomes large. If so, the specific function 24e ends the movement of the evaluation point in the direction. As a result, the specific function 24e can reduce the amount of calculation and speed up the search process. However, in this method, the result depends on the initial position of each evaluation point, so it is preferable to set the initial position to the position where the measured value can be the best. For example, when the closed curve condition of "minimum area" is set and the mitral valve is the target organ, the specific function 24e is the cross section near the valve opening or the cross section perpendicular to the core wire with the smallest area. Set the initial position of each evaluation point at the position where the axes intersect. Further, the specific function 24e may set a plurality of initial positions of each evaluation point. For example, the specific function 24e performs a similar search at a plurality of initial positions, and acquires a combination of evaluation points having the best measured value among the searches using each initial position. For example, the specific function 24e specifies a closed curve having the smallest area for each of the plurality of initial positions, and further specifies a closed curve having the smallest area from the specified plurality of closed curves.

Further, although the case where step S5 is executed after step S4 has been described, the processing order at this point can be changed. For example, the specific function 24e sets evaluation points for each of the plurality of axes set by the axis setting function 24c, and acquires a plurality of closed curve candidates based on the evaluation points. Next, the condition setting function 24d sets a condition related to the closed curve, for example, by accepting an operation from the user. Then, the specific function 24e specifies a closed curve based on a plurality of axes based on the closed curve condition. That is, the processing circuit 24 may calculate a plurality of closed curve candidates in advance before the user specifies the closed curve conditions.

Here, the output function 24f may display the closed curve specified in step S5 or the area surrounded by the closed curve. For example, the output function 24f may display the measurement points as shown in FIG. 7B, and may further display the evaluation points constituting the specified closed curve. In FIG. 7B, the evaluation points constituting the specified closed curve are indicated by round black dots. For example, if the closed curve condition is "minimum area", the round points in FIG. 7B indicate the closed curve with the smallest area in the mitral valve. Alternatively, the output function 24f may omit the display of the measurement points and display only the evaluation points constituting the specified closed curve.

Further, the output function 24f may display different angles as shown in, for example, FIG. 8A, in addition to the display of FIG. 7B. Note that FIG. 7B is a view of the mitral valve from above, whereas FIG. 8A is a view of the mitral valve viewed from the side. In FIG. 8A, the evaluation points constituting the specified closed curve are indicated by round black dots. FIG. 8A is a diagram showing a display example according to the first embodiment.

7B and 8A have described a case where three-dimensional data showing the distribution of evaluation points and measurement points constituting the specified closed curve is displayed, but the embodiment is not limited to this. For example, as shown in FIG. 8B, the output function 24f may select an arbitrary cross section from the three-dimensional data and display it as the two-dimensional data. FIG. 8B is a diagram showing a display example according to the first embodiment. In FIG. 8B, the evaluation points constituting the specified closed curve are indicated by round black dots, the measurement points located at the anterior leaflet of the mitral valve are indicated by square white dots, and the measurement points located at the posterior leaflet are triangular. It is indicated by the white dot of.

That is, the output function 24f may display the distribution of the evaluation points and measurement points constituting the specified closed curve on an arbitrary cross section. The position and angle of the arbitrary cross section may be preset or may be arbitrarily changed by the user. When the arbitrary cross section intersects the specified closed curve, the output function 24f can display two evaluation points constituting the specified closed curve, for example, as shown in FIG. 8B.

Further, as shown in FIG. 8B, for example, the output function 24f may superimpose and display the measurement points and the evaluation points constituting the specified closed curve on the medical image. For example, the output function 24f generates a two-dimensional image of an arbitrary cross section passing through the mitral valve from a three-dimensional image including the mitral valve, and corresponds a measurement point or an evaluation point to each position on the two-dimensional image. Attach and display in superimposition. Further, the output function 24f may superimpose and display only the measurement points on the medical image, for example, as shown in FIG. 8C. FIG. 8C is a diagram showing a display example according to the first embodiment. Further, the output function 24f may superimpose and display only the evaluation points constituting the specified closed curve on the medical image.

Further, the output function 24f may project the specified closed curve onto an arbitrary cross section and display it. For example, the output function 24f first generates a two-dimensional image of an arbitrary cross section passing through the mitral valve from a three-dimensional image including the mitral valve. Further, the output function 24f superimposes and displays the measurement points located on the arbitrary cross section with respect to the two-dimensional image. Further, the output function 24f projects and displays the evaluation points constituting the specified closed curve on the two-dimensional image. That is, the output function 24f projects each evaluation point in a direction perpendicular to the arbitrary cross section regardless of whether or not each evaluation point constituting the specified closed curve is located on the arbitrary cross section. It is superimposed and displayed on the two-dimensional image. As a result, the output function 24f can display the closed curve specified in the three-dimensional space on the two-dimensional image. Note that FIG. 8D is a diagram showing a display example according to the first embodiment.

The output function 24f may switch various displays such as FIGS. 7B, 8A, 8B, 8C, and 8D according to an instruction from the user. Further, although the case of displaying the specified closed curve has been described, the output function 24f may display the area surrounded by the specified closed curve. For example, the output function 24f may display a plane or a curved surface surrounded by the specified closed curve instead of the evaluation points constituting the specified closed curve.

That is, the output function 24f displays the closed curve or region specified by the specific function 24e. For example, as shown in FIG. 8B or the like, the output function 24f may display the closed curve or region specified by the specific function 24e in association with the medical image. Further, for example, as shown in FIG. 7B or the like, the output function 24f associates the closed curve or region specified by the specific function 24e with a plurality of axes or measurement points set by the axis setting function 24c. It may be displayed. Here, as shown in FIG. 7B or the like, the output function 24f may display the evaluation points and the measurement points constituting the specified closed curve in different display forms.

By displaying the closed curve identified in step S5, the medical image processing apparatus 20 can provide information about the mitral valve. For example, if a closed curve is specified under the closed curve condition of "minimum area", the user can refer to the display of the closed curve to see the shape and size of the bottleneck in the mitral valve. And so on.

Further, the output function 24f may calculate and display the measured value for the closed curve specified in step 5 or the region surrounded by the closed curve (step S6) (step S7). For example, the output function 24f can calculate measured values such as the perimeter of the specified closed curve, the area of the area surrounded by the closed curve, and the circularity of the closed curve. Further, the output function 24f may calculate a measured value regarding a two-dimensional closed curve obtained by projecting the specified closed curve in an arbitrary direction. Further, the output function 24f may calculate the measured value after approximating the specified closed curve to another shape. For example, the output function 24f may approximate the specified closed curve to an ellipse and calculate measured values such as a major axis and a minor axis for the ellipse.

Some of the measured values related to the closed curve may have already been calculated in step S5. For example, when the closed curve condition is "minimum area", the specific function 24e calculates the area of the closed curve in the process for specifying the closed curve satisfying the closed curve condition. The specific function 24e may record the measured value calculated in step S5 in the memory 21, and the output function 24f may use the measured value recorded in the memory 21 to display the step S7.

For example, the output function 24f displays a list of measured values calculated for a plurality of items on the display 22. When displaying the closed curve specified in step S5, the output function 24f may display the measured value side by side or overlapped with the closed curve. For example, as shown in FIG. 9, the output function 24f superimposes and displays the measurement points and the evaluation points constituting the specified closed curve on the medical image, and further, “area” and “perimeter”. The measured values calculated for the measurement items such as "length" and "circularity" are superimposed and displayed. Note that FIG. 9 is a diagram showing a display example according to the first embodiment.

By calculating and displaying the measured values, the medical image processing apparatus 20 can provide information about the mitral valve. For example, if a closed curve is specified under the closed curve condition of "minimum area", the user can refer to the display of the measured value related to the closed curve to use the area of the bottleneck in the mitral valve. , Perimeter, circularity, etc. can be grasped as numerical values.

In addition, various modifications can be made to the display form. For example, the output function 24f may change the display form (color, shape, etc.) of the closed curve or the measured value to be displayed based on the size of the measured value. Further, the output function 24f may change the display form based on the relationship between the calculated core phase and the magnitude of the measured value, or may display a screen calling attention. For example, when the closed curve is specified with the closed curve condition as "minimum area", if the area of the closed curve in systole is large or the area in diastole is small, the existence of a disease related to the mitral valve is suspected. In such a case, the output function 24f can display a warning or highlight a measured value such as an area.

Further, the output function 24f may display the specified closed curve or region and display a cross section at an angle different from the closed curve or region. For example, the output function 24f generates and displays a cross-sectional image substantially parallel to the specified closed curve from a three-dimensional medical image, and displays the specified closed curve on the cross-sectional image. Further, the output function 24f generates and displays, for example, an orthogonal cross section orthogonal to the cross section image.

Further, for example, the output function 24f may further display various analysis images. For example, the output function 24f performs fluid analysis based on a plurality of medical images collected in time series, and calculates the properties of the fluid such as the flow direction and the flow velocity of the blood flow in the vicinity of the mitral valve. Further, the output function 24f displays the calculated properties of the fluid, for example, in a color map. Further, the output function 24f can also display a closed curve or a region specified by the specific function 24e on such a color map.

So far, the mitral valve has been described as the target organ, but it can be applied to valves other than the mitral valve as well. Further, it can be similarly applied not only to valves but also to various biological organs having a tubular structure such as blood vessels, esophagus, trachea, ureters, and intestines. That is, the above-described embodiment can be applied to any living organ in which a fluid such as blood or gas, or a solid flows inside.

As an example, the acquisition function 24b acquires a medical image including blood vessels such as coronary arteries and cerebral arteries. Further, the axis setting function 24c sets a plurality of axes based on the blood vessels. For example, the axis setting function 24c sets a first closed curve at one end of a blood vessel included in a medical image, sets a second closed curve at the other end, and sets a plurality of each of the first closed curve and the second closed curve. Set the endpoint of. Then, the axis setting function 24c sets a plurality of axes based on the set plurality of end points. For example, the axis setting function 24c sets a plurality of axes by connecting end points along a blood vessel shape.

Here, the blood vessel may have a stenotic site. For example, as shown in FIG. 10, stenosis may occur in blood vessels such as coronary arteries and cerebral arteries due to intravascular structures such as plaque H1 and plaque H2. In such a case, the axis setting function 24c sets a plurality of axes along the shape of the blood vessel and the shape of the structure in the blood vessel. That is, the axis setting function 24c sets a plurality of axes by connecting the end points set on the first closed curve and the end points set on the second closed curve along the blood vessel or the intravascular structure. Note that FIG. 10 is a diagram showing an example of an intravascular stenosis site according to the first embodiment.

Further, the condition setting function 24d sets a closed curve condition related to the closed curve corresponding to the blood vessel. Further, the specific function 24e specifies a closed curve based on a plurality of set axes based on the closed curve condition. For example, when the closed curve condition is "minimum area", the specific function 24e specifies a closed curve that passes through all the set plurality of axes and has the minimum area. Here, the closed curves that pass through all of the plurality of axes are set at a plurality of positions in the blood vessel shown in FIG. 10, for example. For example, a closed curve that passes through all the axes of numbers is set in a region having a diameter G1 as a major diameter, a region having a diameter G2 as a major diameter, a region having a diameter G3 as a major diameter, and the like. Here, the specifying function 24e can specify a closed curve set in a region having a diameter G3 as a major diameter as a closed curve having a minimum area. That is, the specific function 24e can specify a region having a diameter G3 as a major diameter as a bottleneck region.

As shown in FIG. 10, the shape inside the blood vessel may be complicated due to the presence of plaque or the like. Here, for example, when evaluating the orthogonal cross-sectional area of each position along the core wire of a blood vessel, there is a possibility that a region having a diameter G1 or a diameter G2 as a major diameter may be erroneously determined as a bottleneck region. On the other hand, the medical image processing apparatus 20 evaluates a closed curve inclined with respect to the core line of a blood vessel, for example, a region having a diameter G3 as a major diameter by setting a plurality of axes, and creates a bottleneck region. Can be properly identified.

As described above, according to the first embodiment, the acquisition function 24b acquires a medical image including a biological organ or a valve having a tubular structure. Further, the axis setting function 24c sets a plurality of axes based on a biological organ or a valve having a tubular structure. Further, the condition setting function 24d sets a closed curve condition for a closed curve corresponding to a living organ or a valve having a tubular structure. Further, the specific function 24e specifies a closed curve based on a plurality of axes set by the axis setting function 24c or a region surrounded by the closed curve based on the closed curve condition. Therefore, the medical image processing apparatus 20 according to the first embodiment can provide information about a biological organ or a valve having a tubular structure.

For example, in the case of a mitral valve, if the area of the tip of the valve is the smallest, it is easy to identify the bottleneck, but the shape of the mitral valve varies, and the area between the tip and the annulus becomes the bottleneck. In some cases. That is, the closed curve with the smallest area may be located on the surface of the valve leaflet rather than the tip. Alternatively, the closed curve with the smallest area may be partly located at the tip of the leaflet and the other part above the surface of the leaflet. As described above, although it was possible to obtain information on the shape of the mitral valve based on the medical image, it was not easy to obtain information on the area of the bottleneck and the like. On the other hand, the medical image processing apparatus 20 can appropriately specify the closed curve even for an organ having a complicated shape and provide the information.

The mitral valve is composed of two leaflets, an anterior leaflet and a posterior leaflet. As described above, a biological organ such as a blood vessel or a valve may be divided into a plurality of regions. The medical image processing apparatus 20 may process a biological organ as one region, or may separately process a characteristic region or a region having different characteristics in a region of interest.

For example, in step S2 of FIG. 2, the axis setting function 24c may divide a biological organ such as a blood vessel or a valve into a plurality of regions and acquire a region of interest for each region. For example, the axis setting function 24c acquires the two leaflets of the anterior leaflet and the posterior leaflet of the mitral valve separately as separate regions. That is, the axis setting function 24c performs division based on the anatomical features or structures of biological organs such as blood vessels and valves. Here, the output function 24f may display the acquired plurality of areas of interest on the display 22. Further, the output function 24f may be controlled to display a plurality of attention areas under different display conditions, for example, changing the color between the attention area based on the anterior leaflet and the attention area based on the posterior leaflet. Further, the output function 24f may be controlled so as to display only a part of the plurality of areas of interest according to the instruction of the user.

Further, for example, in step S3, the axis setting function 24c may divide a biological organ such as a blood vessel or a valve into a plurality of regions and set a plurality of axes based on different criteria for each region. That is, the axis setting function 24c may set the number of axes to be set, the spacing, and the like for each region such as the anterior leaflet and the posterior leaflet. For example, the axis setting function 24c can control so that six axes are set for the anterior leaflet and four axes are set for the posterior leaflet.

Further, for example, in step S4, the condition setting function 24d may divide a biological organ such as a blood vessel or a valve into a plurality of regions and set a closed curve condition for each region. For example, the condition setting function 24d may set the curvature of each line segment by approximating the curve. Alternatively, for example, the condition setting function 24d may divide the region surrounded by the closed curve into two regions, a region on the anterior leaflet side and a region on the posterior leaflet side, and set each area as a closed curve condition.

Further, for example, in step S5, the specific function 24e may divide a biological organ such as a blood vessel or a valve into a plurality of regions, and specify a closed curve or a region surrounded by the closed curve with different criteria for each region. .. For example, in the specific function 24e, the condition for determining the position for resetting the evaluation point may be different between the evaluation point on the anterior leaflet side axis and the evaluation point on the posterior leaflet side axis. For example, it may be controlled to reset only the posterior leaflet side without resetting the anterior leaflet side. Further, for example, when the repetitive processing is stopped after a certain number of times, the specific function 24e may control the number of resets on the posterior leaflet side to be larger than the number of times on the anterior leaflet side.

Further, for example, in step S6 and step S7, the output function 24f may divide a biological organ such as a blood vessel or a valve into a plurality of regions and calculate a measured value for each region. For example, as shown in FIG. 11, the output function 24f may calculate and display each of the anterior apex perimeter and the posterior apex perimeter. Further, the output function 24f may display the closed curve or the area specified by the specific function 24e in a display mode different for each area. For example, as shown in FIG. 11, the output function 24f may display a closed curve so that the shape of the evaluation point on the anterior leaflet side axis and the evaluation point on the posterior leaflet side axis are different. In FIG. 11, the evaluation points on the anterior leaflet side of the specified closed curve are indicated by black dots of a quadrangle, and the evaluation points on the posterior leaflet side are indicated by black dots of a triangle. FIG. 11 is a diagram showing a display example according to the first embodiment.

The method for treating a biological organ such as a blood vessel or a valve by dividing it into a plurality of regions may be applied to only one of steps S2 to S7 in FIG. 2, or may be applied to a plurality or all of them. ..

Further, in the above-described embodiment, a case where a plurality of axes are set is described according to the flowchart of FIG. 4A. That is, a first closed curve is set at one end of the mitral valve or the like, a second closed curve is set at the other end, a plurality of endpoints are set for each of the first closed curve and the second closed curve, and a plurality of endpoints are set. The case of setting a plurality of axes based on the endpoints has been described. However, the embodiments are not limited to this.

For example, the axis setting function 24c may set a plurality of axes by using a plurality of predetermined cross sections. For example, the axis setting function 24c sets a plurality of axes using the UI shown in FIG. Note that FIG. 12 shows a case where a plurality of predetermined cross sections are defined radially. That is, the axis setting function 24c defines a radial cross section such as cross sections P1 to P4, and sets a plurality of axes based on the position where the cross section and the region of interest intersect. The cross sections P1 to P4 are two-dimensional planes having lengths in the depth direction, respectively. The center position of the radial cross section may be set manually by the user or may be set based on a predetermined standard. For example, the center position of the radial cross section may be the center of the display screen, or may be the center of gravity of the region of interest or the center of gravity or the center of the tip closed curve or the annulus closed curve. However, since it is desirable to set the center position of the radial cross section inside the region of interest, the axis setting function 24c may be controlled so that it cannot be set outside the region of interest. Note that FIG. 12 is a diagram showing an example of an axis setting method according to the first embodiment.

Further, the axis setting function 24c determines the direction in which the cross section is set. For example, the direction for setting the cross section may be the direction from the front side to the back side of the display screen, or the direction from the center of gravity or the center of the tip closed curve toward the center of gravity or the center of the annulus closed curve.

Further, the axis setting function 24c sets information regarding the number of cross sections to be set. The number of cross sections may be predetermined, or may be appropriately set by using, for example, the UI shown in FIG. Note that FIG. 12 shows a case where four cross sections P1 to P4 are set as the number of cross sections. Alternatively, the angle between the cross sections may be set instead of the number of cross sections. Then, the axis setting function 24c sets a set number of cross sections or a number of cross sections that can be set closest to the angle between the set cross sections and at equal intervals. That is, when the angle between the cross sections is set, the number obtained by dividing "180 degrees" by the set angle and rounding down to the nearest whole number is the number of cross sections. For example, when "45 degrees" is set as the angle between the cross sections, four cross sections are set as shown in FIG. That is, in the case shown in FIG. 12, the axis setting function 24c can define a plurality of predetermined cross sections by receiving an input of the number of cross sections or the angle between the cross sections.

Further, the axis setting function 24c may control the cross section so that the user can move, delete, or add the cross section after setting the cross section. For example, the output function 24f displays the set cross section on the display 22, and the axis setting function 24c accepts a user operation on the cross section based on, for example, an operation of the mouse pointer M. The axis setting function 24c may be controlled so as not to move beyond the adjacent cross sections.

Then, after the positions and numbers of the radial cross sections are determined, the axis setting function 24c sets a plurality of axes based on the intersection positions of these cross sections and the region of interest. That is, the axis setting function 24c sets a plurality of axes by using a plurality of cross sections defined radially. For example, the axis setting function 24c uses the intersection of each cross section and the tip closed curve or the annulus closed curve as an end point, and sets a plurality of axes based on these end points. For example, the axis setting function 24c sets a plurality of axes by connecting the end points on the tip closed curve and the end points on the annulus closed curve along the shape of the region of interest.

Further, in FIGS. 6A and 6B, a case where the closed curve condition is set by the user directly inputting the closed curve condition has been described. For example, in FIG. 6A, the closed curve condition is selected from “perimeter”, “area”, “circularity”, and the like. However, the user may not be able to grasp the correspondence between these closed curve conditions and the clinical meaning.

Therefore, the condition setting function 24d may set the closed curve condition by presenting the clinical meaning of each closed curve condition to the user and accepting the selection of the clinical meaning from the user. For example, as shown in FIG. 13A, the output function 24f has a clinical meaning of "minimum area" and "size of a region that becomes a bottleneck of blood flow" and a clinical meaning of "maximum circularity". The table displays "easiness of blood flow" and the clinical meaning of "maximum circumference" "how wide the valve opening is". Further, for example, as shown in FIG. 13B, the output function 24f causes a plurality of clinical meanings to be pulled down and displayed based on the user operation received via the mouse pointer M. Then, the user selects a plurality of clinical meanings of interest, and the condition setting function 24d sets a closed curve condition corresponding to the selected clinical meaning. That is, in the case shown in FIG. 13A, the output function 24f displays a plurality of combinations of clinical meanings and the above conditions, and the condition setting function 24d sets closed curve conditions based on user operations for the displayed plurality of combinations. be able to. Further, in the case shown in FIG. 13B, the output function 24f displays a plurality of clinical meanings in a pull-down manner, and the condition setting function 24d can set a closed curve condition based on a user operation for the pull-down display. 13A and 13B are diagrams showing an example of a method for setting a closed curve condition according to the first embodiment.

(Second embodiment)
In the second embodiment, when a plurality of time-series medical images are acquired, a closed curve or a region surrounded by the closed curve is specified based on the plurality of medical images. That is, in the second embodiment, a case of specifying a closed curve or a region surrounded by the closed curve will be described based on the information of a plurality of images captured at a plurality of different time points. The medical image processing system 1 according to the second embodiment has the same configuration as the medical image processing system 1 shown in FIG. 1, and has an axis setting function 24c, a condition setting function 24d, a specific function 24e, and an output function 24f. Some of the processing is different. Hereinafter, the points described in the above-described embodiment are designated by the same reference numerals as those in FIG. 1, and the description thereof will be omitted.

For example, in step S1 shown in FIG. 2, the acquisition function 24b acquires a plurality of time-series medical images. For example, the acquisition function 24b acquires a plurality of medical images including a mitral valve and having different heart phases. Further, in step S2, the axis setting function 24c acquires a region of interest for each of the plurality of medical images. Further, in step S3, the axis setting function 24c sets a plurality of axes for each of the plurality of medical images. It is desirable that the conditions such as the number of axes set for each medical image are the same.

Further, in step S4, the condition setting function 24d sets a condition based on a plurality of medical images as a closed curve condition. Examples of such conditions include "minimum (or maximum) variation in closed curve between medical images", "minimum (or maximum) change in area between medical images", and "area in multiple medical images". The average value of is the minimum (or maximum). "

Further, in step S5, the specific function 24e associates the evaluation points in each axis between the medical images. For example, the specific function 24e sets the same number of measurement points under the same conditions for all medical images, and associates the corresponding measurement points between the medical images. To give another example, the specific function 24e sets a measurement point on the reference medical image and aligns the measurement point between the reference medical image and another medical image to obtain the measurement point of the reference medical image. The corresponding position may be used as a measurement point for another medical image. Since the shape of the mitral valve changes for each medical image, the distance and positional relationship between the measurement points will change for each medical image. Then, the specific function 24e calculates the value of the item related to the closed curve condition based on the plurality of medical images based on the corresponding closed curve in each medical image. Further, the specific function 24e specifies a closed curve or a region surrounded by the closed curve by repeating the process of resetting the evaluation point and calculating the value of the item related to the closed curve condition.

Further, the output function 24f calculates the measured value in step S6 and displays the measured value in step S7. Here, the measured value calculated by the output function 24f may be calculated based on a plurality of medical images such as "amount of variation of the closed curve between medical images", or may be calculated based on a plurality of medical images, for example, "area of the closed curve". It may be calculated based on one medical image such as ".

(Third embodiment)
Living organs such as blood vessels and valves may contain characteristic points or structures. In the third embodiment, a case where the processing in consideration of such a characteristic point or structure will be described will be described. The medical image processing system 1 according to the third embodiment has the same configuration as the medical image processing system 1 shown in FIG. 1, and has an axis setting function 24c, a condition setting function 24d, a specific function 24e, and an output function 24f. Some of the processing is different. Hereinafter, the points described in the above-described embodiment are designated by the same reference numerals as those in FIG. 1, and the description thereof will be omitted.

For example, in step S2 shown in FIG. 2, the axis setting function 24c acquires a region of interest and identifies a characteristic point or structure. Here, the characteristic point or structure is, for example, the position of the commissure of the anterior and posterior leaflets of the mitral valve, the position of the trigone, which is the position related to the mitral valve, and the like. Or the apex of the heart or the central position of the aortic valve. For example, the axis setting function 24c can identify a characteristic point or structure by the above-mentioned known region extraction technique. The axis setting function 24c may simultaneously perform the acquisition of the region of interest and the identification of the characteristic point or structure by the same method, or may be performed separately by using different methods.

For example, the axis setting function 24c can utilize a characteristic point or structure when setting an axis in step S3. That is, the axis setting function 24c can set a plurality of axes based on a characteristic point or structure. Hereinafter, a case where the axis is set according to the flowchart of FIG. 4 will be described. For example, as an example of step S31, a case where the pixel located at the lower end or the upper end in each pixel row in a predetermined direction is specified as the tip shape D1 and the annulus shape D2 has been described. Here, the axis setting function 24c can specify the predetermined direction based on a characteristic point or structure. Further, as an example of step S32, a case where a starting point is set based on a reference point and a plurality of endpoints are set from the starting point has been described. Here, the axis setting function 24c can set a reference point or a starting point based on a characteristic point or structure.

Further, the specific function 24e can utilize a characteristic point or structure when specifying a closed curve or a region surrounded by the closed curve in step S5. That is, the specific function 24e can specify a closed curve or a region surrounded by the closed curve based on a characteristic point or structure. For example, first, in step S4, the condition setting function 24d sets whether or not the position of a characteristic point or structure is used as a closed curve condition. For example, the condition setting function 24d can set whether or not to use a characteristic point or a position of a structure by accepting a user operation via a UI such as a check box. Then, the specific function 24e specifies a closed curve passing through a characteristic point or structure or a region surrounded by the closed curve based on the closed curve condition. For example, the specific function 24e specifies a closed curve that passes through all the axes set by the axis setting function 24c, passes through two commissures, and has the minimum perimeter. Further, for example, the specific function 24e may set a search range of evaluation points to be moved on each axis based on a characteristic point or a position (coordinates) of a structure when specifying a closed curve. For example, the specific function 24e may be controlled to move the evaluation point only in the region surrounded by the four points of the two commissures and the two fiber triangles.

Further, the output function 24f may display the characteristic points or structures so that the user can recognize them. For example, when displaying a region of interest, an axis, an evaluation point, a closed curve specified by the specific function 24e or a region surrounded by the closed curve, a measured value related to the closed curve or the region, and the like, the position of a characteristic point or structure. Can also be displayed. For example, the output function 24f can display a characteristic point or structure by using a display form (color, shape) different from other evaluation points, areas, and the like.

(Fourth Embodiment)
By the way, although the first to third embodiments have been described so far, various different embodiments may be implemented in addition to the above-described embodiments.

For example, in the above-described embodiment, a case where a region of interest is acquired and an axis is set on the region of interest has been described. However, the embodiments are not limited to this. For example, the axis setting function 24c may omit the acquisition of the region of interest and set a plurality of axes directly from the medical image acquired by the acquisition function 24b.

For example, the axis setting function 24c can set a plurality of axes by a machine learning technique such as deep learning without acquiring a region of interest. As an example, the axis setting function 24c first acquires a region of interest from a medical image and sets the plurality of axes based on the region of interest, as described in the first embodiment. Further, the axis setting function 24c collects a large number of combinations of the medical image and the set plurality of axes as learning data. Further, the axis setting function 24c executes machine learning using the medical image as input side data and the set plurality of axes as output side data to generate a trained model. The trained model is functionalized to receive input of a medical image and set multiple axes. Then, when the acquisition function 24b newly acquires the medical image, the axis setting function 24c sets a plurality of axes by inputting the medical image to the trained model without acquiring the region of interest. be able to. That is, step S2 shown in FIG. 2 can be omitted. Similarly, the above-mentioned measurement points can be set without acquiring the region of interest.

For example, in the above-described embodiment, a case where a plurality of axes are generated each time has been described. However, the embodiment is not limited to this, and the axis setting function 24c may set a plurality of axes by deforming a plurality of predetermined axes.

For example, the axis setting function 24c acquires the cylindrical model shown in FIG. 14 in advance and stores it in the memory 21. A plurality of axes are set in the cylindrical model based on arbitrary conditions. That is, the cylindrical model is an example of a plurality of predetermined axes. In the case shown in FIG. 14, ten linear axes are set along the height direction in the cylindrical model. Note that FIG. 14 is a diagram for explaining a method of setting the axis according to the fourth embodiment.

For example, when the acquisition function 24b newly acquires a medical image, the axis setting function 24c reads a cylindrical model from the memory 21 and deforms it according to the structure of a biological organ such as a mitral valve. For example, the axis setting function 24c sets a plurality of axes by aligning the read tubular model with a medical image including a biological organ such as a mitral valve. That is, the axis setting function 24c performs deformation based on the alignment result between a plurality of predetermined axes and a biological organ such as a mitral valve. For example, the axis setting function 24c acquires a region of interest from a medical image and aligns a cylindrical model so as to fit the shape of the region of interest. As the alignment method, a known deformation alignment method can be used. For example, the axis setting function 24c can align the cylindrical model with the medical image by a method of aligning grid points such as ICP (Iterative Closest Point). Further, the axis setting function 24c can also set the axis by aligning between the images using the image for which the axis has already been set. In this case, a known method such as an FFD (Free-Form Deformation) method or an LDDMM (Large Deformation Diffeomorphic Metric Mapping) method can be used for the alignment between images.

Further, in the above-described embodiment, the case where the display 22 is displayed based on the closed curve or the region specified by the specific function 24e has been described. However, the embodiments are not limited to this. For example, the output function 24f may transmit the closed curve or region specified by the specific function 24e to an external device. In this case, the external device can display a closed curve or a region, and can calculate and display various measured values.

The term "processor" used in the above description refers to, for example, a CPU, a GPU (Graphics Processing Unit), an integrated circuit for a specific application (Application Specific Integrated Circuit: ASIC), and a programmable logic device (for example, a simple programmable logic device (Simple Program)). It means a circuit such as a Logic Device (SPLD), a composite programmable logic device (Complex Program Logic Device: CPLD), and a field programmable gate array (Field Programmable Gate Array: FPGA). When the processor is, for example, a CPU, the processor realizes a function by reading and executing a program stored in a storage circuit. On the other hand, when the processor is, for example, an ASIC, the function is directly incorporated as a logic circuit in the circuit of the processor instead of storing the program in the storage circuit. It should be noted that each processor of the embodiment is not limited to the case where each processor is configured as a single circuit, and a plurality of independent circuits may be combined to form one processor to realize its function. .. Further, a plurality of components in each figure may be integrated into one processor to realize the function.

Further, in FIG. 1, a single memory 21 has been described as storing a program corresponding to each processing function of the processing circuit 24. However, the embodiments are not limited to this. For example, a plurality of memories 21 may be distributed and arranged, and the processing circuit 24 may be configured to read a corresponding program from the individual memories 21. Further, instead of storing the program in the memory 21, the program may be directly incorporated in the circuit of the processor. In this case, the processor realizes the function by reading and executing the program embedded in the circuit.

Each component of each device according to the above-described embodiment is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of them may be functionally or physically distributed / physically in arbitrary units according to various loads and usage conditions. Can be integrated and configured. Further, each processing function performed by each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware by wired logic.

Further, the medical image processing method described in the above-described embodiment can be realized 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. Further, this program is recorded on a non-transient recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, or a DVD that can be read by a computer, and is executed by being read from the recording medium by the computer. You can also do it.

According to at least one embodiment described above, it is possible to provide information about a biological organ or valve having a tubular structure.

Although some embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other embodiments, and various omissions, replacements, changes, and combinations of embodiments can be made without departing from the gist of the invention. These embodiments and variations thereof are included in the scope of the invention described in the claims and the equivalent scope thereof, as are included in the scope and gist of the invention.

Regarding the above embodiments, the following appendices are disclosed as one aspect and selective features of the invention.
(Appendix 1)
An acquisition unit that acquires medical images including blood vessels or valves,
An axis setting unit that sets a plurality of axes based on the blood vessel or valve,
A condition setting unit that sets conditions related to the closed curve corresponding to the blood vessel or valve, and
A medical image processing apparatus comprising a closed curve based on the plurality of axes or a specific portion for specifying a region surrounded by the closed curve based on the above conditions.
(Appendix 2)
The axis setting unit may acquire a region of interest from the medical image based on the blood vessel or valve and set the plurality of axes based on the region of interest.
(Appendix 3)
The axis setting unit may divide the blood vessel or valve into a plurality of regions and acquire the region of interest for each region.
(Appendix 4)
The axis setting unit sets a first closed curve at one end of the blood vessel or valve, a second closed curve at one end of the other end, and a plurality of each of the first closed curve and the second closed curve. The endpoints may be set and the plurality of axes may be set based on the plurality of endpoints.
(Appendix 5)
The plurality of axes may be set along the shape of the blood vessel or valve.
(Appendix 6)
The medical image contains blood vessels and
The axis setting unit sets the plurality of axes by connecting the end points set on the first closed curve and the end points set on the second closed curve along the blood vessel or the intravascular structure. You may.
(Appendix 7)
The axis setting unit may set a different number of the end points on the first closed curve and the second closed curve.
(Appendix 8)
The axis setting unit receives input of a starting point for setting a plurality of the end points in order and a condition for setting a plurality of the end points, so that each of the first closed curve and the second closed curve May be set to a plurality of the endpoints.
(Appendix 9)
The axis setting unit may accept a user operation for displaying the first closed curve and the second closed curve as input of the starting point.
(Appendix 10)
The axis setting unit may set the plurality of axes based on the characteristic points or structures of the blood vessel or valve.
(Appendix 11)
The axis setting unit may set the plurality of axes by using a plurality of predetermined cross sections.
(Appendix 12)
The predetermined plurality of cross sections may be defined radially.
(Appendix 13)
The axis setting unit may define a plurality of predetermined cross sections by receiving an input of the number of cross sections or the angle between the cross sections.
(Appendix 14)
The axis setting unit may set the plurality of axes using a trained model functionalized to receive input of a medical image and set a plurality of axes.
(Appendix 15)
The axis setting unit may set the plurality of axes by deforming the plurality of predetermined axes.
(Appendix 16)
The shaft setting unit may be deformed according to the structure of the blood vessel or valve.
(Appendix 17)
The axis setting unit may perform the deformation based on the alignment result of the predetermined axis and the blood vessel or valve.
(Appendix 18)
The plurality of predetermined axes may be a cylindrical model.
(Appendix 19)
The specific unit acquires a plurality of closed curve candidates that pass through all of the plurality of axes, calculates the value of the item related to the condition for each of the acquired plurality of closed curve candidates, and is based on the plurality of axes. A closed curve or a region surrounded by the closed curve may be specified.
(Appendix 20)
The specific unit may set evaluation points for each of the plurality of axes and connect the evaluation points to obtain the closed curve candidate.
(Appendix 21)
The specific unit may acquire the plurality of closed curve candidates by repeating the resetting of the evaluation points according to the value.
(Appendix 22)
The specific unit may acquire the plurality of closed curve candidates by moving the evaluation points so that the value satisfies the condition or the value approaches the condition.
(Appendix 23)
The specific part may specify a closed curve based on the plurality of axes or a region surrounded by the closed curve based on a characteristic point or structure in the blood vessel or valve.
(Appendix 24)
The acquisition unit acquires a plurality of the medical images in a time series and obtains them.
The condition setting unit sets the condition based on the plurality of medical images, and sets the condition.
Based on the above conditions, the specific unit may specify a closed curve based on the plurality of axes or a region surrounded by the closed curve.
(Appendix 25)
Further, an output unit that outputs a closed curve or a region specified by the specific unit may be provided.
(Appendix 26)
The output unit may display the closed curve or region specified by the specific unit.
(Appendix 27)
The output unit may display the closed curve or region specified by the specific unit in association with the medical image.
(Appendix 28)
The output unit may display the closed curve or region specified by the specific unit in association with the plurality of axes or measurement points.
(Appendix 29)
The output unit may display the evaluation points constituting the closed curve specified by the specific unit and the measurement points in different display forms.
(Appendix 30)
The output unit may divide the blood vessel or valve into a plurality of regions and display the closed curve or region specified by the specific unit in a display mode different for each region.
(Appendix 31)
The output unit may display a measured value regarding a closed curve or a region specified by the specific unit.
(Appendix 32)
The output unit may divide the blood vessel or valve into a plurality of regions, and calculate and display the measured value for each region.
(Appendix 33)
The axis setting unit may divide the blood vessel or valve into a plurality of regions and set the plurality of axes based on different criteria for each region.
(Appendix 34)
The axis setting unit may divide the blood vessel or valve into a plurality of regions and set the conditions for each region.
(Appendix 35)
The specific portion may divide the blood vessel or valve into a plurality of regions and specify a closed curve based on the plurality of axes or a region surrounded by the closed curve based on different criteria for each region.
(Appendix 36)
The condition setting unit may accept the selection of the clinical meaning from the user and set the condition corresponding to the selected clinical meaning.
(Appendix 37)
It is equipped with an output unit that displays a plurality of combinations of the clinical meaning and the conditions.
The condition setting unit may set the condition based on the user operation for the combination.
(Appendix 38)
Equipped with an output unit that pulls down multiple clinical meanings
The condition setting unit may set the condition based on the user operation for the pull-down display.
(Appendix 39)
The condition setting unit may display a plurality of items and contents of the condition, accept selection from the user for the item and the content, and set the condition based on the accepted item and content.
(Appendix 40)
The condition setting unit may set the condition by displaying a plurality of the item of the condition, accepting a selection from the user, and further accepting an input of the content in the accepted item.
(Appendix 41)
The degradation may be characterized by being based on the anatomical features or structure of the early blood vessels or valves.
(Appendix 42)
As the condition, the condition setting unit may set at least one of the perimeter of the closed curve, the area of the area surrounded by the closed curve, the circularity of the closed curve, and the diameter of the sphere inscribed in the closed curve.
(Appendix 43)
The medical image processing apparatus according to claim 1 to 15, wherein the specific unit specifies a closed curve passing through all of the plurality of axes or a region surrounded by the closed curve based on the above conditions.
(Appendix 44)
An acquisition unit that acquires a medical image including a biological organ or valve having a tubular structure,
An axis setting unit that sets a plurality of axes based on the biological organ or valve,
A condition setting unit that sets conditions related to the closed curve corresponding to the biological organ or valve, and
A medical image processing apparatus comprising a closed curve based on the plurality of axes or a specific portion for specifying a region surrounded by the closed curve based on the above conditions.
(Appendix 45)
Obtain medical images including blood vessels or valves,
Set multiple axes based on the blood vessel or valve
Conditions related to the closed curve corresponding to the blood vessel or valve are set.
A medical image processing method comprising identifying a closed curve based on the plurality of axes or a region surrounded by the closed curve based on the above conditions.
(Appendix 46)
A program that causes a computer to execute each configuration of the above medical image processing device.

1 Medical image processing system 10 Medical image diagnostic device 20 Medical image processing device 21 Memory 22 Display 23 Input interface 24 Processing circuit 24a Control function 24b Acquisition function 24c Axis setting function 24d Condition setting function 24e Specific function 24f Output function 30 Image storage device

Claims (19)

An acquisition unit that acquires medical images including blood vessels or valves,
An axis setting unit that sets a plurality of axes based on the blood vessel or valve,
A condition setting unit that sets conditions related to the closed curve corresponding to the blood vessel or valve, and
A medical image processing apparatus comprising a closed curve based on the plurality of axes or a specific portion for specifying a region surrounded by the closed curve based on the above conditions. The axis setting unit divides the blood vessel or valve into a plurality of regions, acquires a region of interest from the medical image for each region, and sets the plurality of axes based on the region of interest. The medical image processing apparatus described in. The axis setting unit sets a first closed curve at one end of the blood vessel or valve, a second closed curve at one end of the other end, and a plurality of each of the first closed curve and the second closed curve. The medical image processing apparatus according to claim 1 or 2, wherein the endpoints are set and the plurality of axes are set based on the plurality of endpoints. The medical image processing apparatus according to claim 3, wherein the plurality of axes are set along the shape of the blood vessel or valve. The medical image contains blood vessels and
The axis setting unit sets the plurality of axes by connecting the end points set on the first closed curve and the end points set on the second closed curve along the blood vessel or the intravascular structure. , The medical image processing apparatus according to claim 3 or 4. The medical image processing apparatus according to any one of claims 1 to 5, wherein the axis setting unit sets the plurality of axes based on a characteristic point or structure of the blood vessel or valve. The medical image processing apparatus according to claim 1, wherein the axis setting unit sets the plurality of axes by using a plurality of predetermined cross sections. The medical image processing apparatus according to claim 1, wherein the axis setting unit sets the plurality of axes by using a trained model functionalized to receive input of a medical image and set a plurality of axes. .. The medical image processing apparatus according to claim 1, wherein the axis setting unit sets the plurality of axes by deforming a plurality of predetermined axes. The specific unit acquires a plurality of closed curve candidates that pass through all of the plurality of axes, calculates the value of the item related to the condition for each of the acquired plurality of closed curve candidates, and is based on the plurality of axes. The medical image processing apparatus according to any one of claims 1 to 9, which specifies a closed curve or a region surrounded by the closed curve. The medical image processing apparatus according to claim 10, wherein the specific unit sets evaluation points on each of the plurality of axes and acquires the closed curve candidate by connecting the evaluation points. The acquisition unit acquires a plurality of the medical images in a time series and obtains them.
The condition setting unit sets the condition based on the plurality of medical images, and sets the condition.
The medical image processing apparatus according to any one of claims 1 to 11, wherein the specific unit specifies a closed curve based on the plurality of axes or a region surrounded by the closed curve based on the above conditions. The medical image processing apparatus according to any one of claims 1 to 12, further comprising an output unit that outputs a closed curve or a region specified by the specific unit. The medical image processing apparatus according to any one of claims 1 to 13, further comprising an output unit for displaying a closed curve or a region specified by the specific unit. The condition setting unit sets at least one of the perimeter of the closed curve, the area of the area surrounded by the closed curve, the circularity of the closed curve, and the diameter of the sphere inscribed in the closed curve as the conditions. 14. The medical image processing apparatus according to any one of 14. The medical image processing apparatus according to any one of claims 1 to 15, wherein the specific unit specifies a closed curve passing through all of the plurality of axes or a region surrounded by the closed curve based on the above conditions. An acquisition unit that acquires a medical image including a biological organ or valve having a tubular structure,
An axis setting unit that sets a plurality of axes based on the biological organ or valve,
A condition setting unit that sets conditions related to the closed curve corresponding to the biological organ or valve, and
A medical image processing apparatus comprising a closed curve based on the plurality of axes or a specific portion for specifying a region surrounded by the closed curve based on the above conditions. Obtain medical images including blood vessels or valves,
Set multiple axes based on the blood vessel or valve
Set the conditions for the closed curve corresponding to the blood vessel or valve, and set the conditions.
A medical image processing method comprising identifying a closed curve based on the plurality of axes or a region surrounded by the closed curve based on the above conditions. Obtain medical images including blood vessels or valves,
Set multiple axes based on the blood vessel or valve
Set the conditions for the closed curve corresponding to the blood vessel or valve, and set the conditions.
A program that causes a computer to execute each process for specifying a closed curve based on the plurality of axes or a region surrounded by the closed curve based on the above conditions.

Images