Medical image processing apparatus, medical image processing method, and medical image processing program

Abstract

To accurately specify a dominant area of the arteries.SOLUTION: A medical image processing apparatus includes: an acquisition unit that acquires medical image data of a site including a first blood vessel that is an artery and a second blood vessel that is an artery or a vein; a specification unit that specifies a dominant area of the first blood vessel; and an output unit that outputs data for displaying the specified dominant area. The specification unit specifies the dominant area of the multiple arteries on the basis of the medical image data, a blood flow strength coefficient and a damping coefficient of the first blood vessel, and a blood flow strength coefficient and a damping coefficient of the second blood vessel.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The embodiments disclosed in this specification and the drawings relate to a medical image processing device, a medical image processing method, and a medical image processing program. [Background technology]

[0002] The area that is supplied with nutrients by blood diffusing from an artery is called the control area (or blood flow area), and is one of the important indicators in vascular treatment. For example, after treatment of coronary artery disease, the control area of ​​the treated coronary artery is identified, and the area that can be reperfused is determined from the identified control area. Therefore, the control area is an important indicator for estimating the effectiveness of treatment.

[0003] Conventionally, the Voronoi fractionation method has been known as a method for identifying a dominating region using medical images. The Voronoi fractionation method is a method for dividing a region into a plurality of seed points (generator points) arranged at any position in a certain metric space, based on which other points in the same metric space are closest to the seed point. For example, the dominating region of a selected coronary artery is identified by performing region expansion based on the shape of the selected coronary artery. The boundary between the dominating regions is part of the perpendicular bisector of the two seed points. However, in this method, the dominating region is identified by considering only the distance from the seed points in the spatial coordinates, making it difficult to accurately identify the dominating region for each patient. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2015-164560 A [Patent Document 2] JP 2019-114287 A [Patent Document 3] JP 2009-279290 A [Patent Document 4] JP 2019-181290 A [Patent Document 5] JP 2017-080043 A [Patent Document 6] JP 2018-102791 A Summary of the Invention [Problem to be solved by the invention]

[0005] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to accurately identify the governing area of ​​an artery. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems. [Means for solving the problem]

[0006] A medical image processing apparatus according to an embodiment includes an acquisition unit that acquires medical image data of a region including a first blood vessel that is an artery and a second blood vessel that is an artery or a vein, an identification unit that identifies a control region of the first blood vessel, and an output unit that outputs data for displaying the identified control region. The identification unit identifies the control region of the arteries based on the medical image data, a blood flow intensity coefficient and an attenuation coefficient associated with the first blood vessel, and a blood flow intensity coefficient and an attenuation coefficient associated with the second blood vessel. [Brief description of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram showing an example of the arrangement of a medical image processing apparatus according to a first embodiment. [Figure 2A] FIG. 13 is a diagram for explaining an example of factors that determine the attenuation coefficient of blood flow. [Figure 2B] FIG. 13 is a diagram for explaining an example of factors that determine the attenuation coefficient of blood flow. [Figure 2C] FIG. 13 is a diagram for explaining an example of factors that determine the attenuation coefficient of blood flow. [Diagram 3] 4 is a flowchart for explaining an example of a medical image processing method according to the first embodiment. [Figure 4]5 is a flowchart for explaining an example of a control region specifying method according to the first embodiment. [Diagram 5] FIG. 2 is a diagram showing an example of a vector field formed by arterial blood flow vectors. [Figure 6] FIG. 2 is a diagram for explaining a method for identifying a control region according to the first embodiment. [Figure 7] FIG. 13 is a diagram showing an example of a control region identified by a boundary when an artery is present on the surface of tissue. [Figure 8] 10 is a flowchart illustrating an example of a control region specifying method according to a modified example of the first embodiment. [Figure 9A] FIG. 11 is a diagram for explaining a method for identifying a control region according to a modified example of the first embodiment. [Figure 9B] FIG. 2 is a diagram showing an example of a vector field formed by blood flow vectors of a vein. [Figure 10] FIG. 13 is a diagram showing an example of a screen on which lines indicating blood flow are superimposed on a medical image. [Figure 11] FIG. 13 is a diagram showing an example of a screen on which a control region is displayed using gradation. [Figure 12] FIG. 13 is a diagram showing an example of a display image in which the surface of the heart is expanded into a two-dimensional image by an equal area projection method. [Figure 13] FIG. 13 is a diagram showing an example of a display image after a thrombus is removed by simulation. [Figure 14A] FIG. 13 is a diagram showing an example of an image in which a relatively thick boundary line is superimposed when the diameter of an artery is large. [Figure 14B] FIG. 13 is a diagram showing an example of an image in which a relatively thin boundary line is superimposed when the diameter of an artery is small. [Figure 15] FIG. 13 is a diagram showing an example of an image in which a boundary is displayed using a gradation according to the strength of blood flow toward the boundary. [Figure 16] FIG. 13 is a diagram showing an example of a medical image on which a pop-up message is displayed. [Figure 17] FIG. 13 is a diagram showing an example of a medical image on which a pop-up message is displayed. [Figure 18] 10 is a flowchart for explaining an example of a medical image processing method according to the second embodiment. [Figure 19] 10 is a flowchart illustrating a method for identifying a control region according to a second embodiment. [Figure 20] FIG. 11 is a diagram for explaining a method for identifying a control region according to the second embodiment. [Figure 21] FIG. 13 is a block diagram showing an example of the arrangement of a medical image processing apparatus according to a third embodiment. [Figure 22] 13 is a flowchart for explaining an example of a medical image processing method according to the third embodiment. [Diagram 23] FIG. 13 is a view showing an example of a screen according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] Hereinafter, medical image processing devices according to the first to third embodiments will be described with reference to the drawings. In the following description, components having substantially the same functions and configurations will be given the same reference numerals, and repeated explanations will be given only when necessary. In addition, terms indicating geometric conditions (parallel, perpendicular, etc.) used in this specification will be interpreted to include a range in which similar functions can be expected without being bound by strict meanings.

[0009] (First embodiment) FIG. 1 shows an example of the configuration of a medical image processing apparatus 1 according to the first embodiment.

[0010] As described in detail below, the medical image processing device 1 according to this embodiment is configured to acquire medical image data of a region including multiple arteries from an external medical image diagnostic device, a medical image storage server, etc. (not shown), identify the control area of ​​each artery taking into account the blood flow intensity coefficient (R) and attenuation coefficient (β) of each artery, and output data for displaying the identified control area.

[0011] 1, the medical image processing apparatus 1 includes a memory 11, a display 12, an input interface 13, a communication interface 14, and a processing circuit 15. Each component will be described in detail below.

[0012] The memory 11 is connected to the processing circuit 15 and stores various types of information used by the processing circuit 15. The memory 11 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, a hard disk, an optical disk, or the like. The memory 11 stores various programs required for the processing circuit 15 to execute each function, various types of data processed by the programs, and the like. Note that the various types of data handled in this specification are typically digital data.

[0013] The display 12 displays various images and information. For example, the display 12 displays medical images and a GUI (Graphical User Interface) that accepts user operations. In this embodiment, the display 12 is configured by, for example, a liquid crystal display or a CRT (Cathode Ray Tube) display.

[0014] The input interface 13 accepts various input operations, converts the accepted input operations into electrical signals, and outputs the electrical signals to the processing circuit 15. The input interface 13 is realized by, for example, a mouse, a keyboard, a touch panel, a trackball, a manual switch, a foot switch, a button, a joystick, or the like.

[0015] The communication interface 14 communicates with other devices (medical image diagnostic devices, medical image storage servers, etc.) via an in-hospital network or an external communication network such as the Internet, in accordance with various communication protocols.

[0016] The processing circuitry 15 is an arithmetic circuit that performs various calculations and controls the operation of the medical image processing device 1. As shown in Fig. 1, the processing circuitry 15 has an acquisition function 15a, a specification function 15b, and an output function 15c. The acquisition function 15a is an example of an acquisition section, the specification function 15b is an example of a specification section, and the output function 15c is an example of an output section.

[0017] In this embodiment, each processing function executed by the acquisition function 15a, the identification function 15b, and the output function 15c is stored in the memory 11 in the form of a program executable by a computer. That is, the processing circuit 15 is configured with a processor, and realizes the function corresponding to each program by reading and executing the program from the memory 11. In other words, the processing circuit 15 in a state in which each program has been read has each function shown in the processing circuit 15 of FIG.

[0018] 1 shows a case where the processing functions of the acquisition function 15a, the identification function 15b, and the output function 15c are realized by a single processing circuit 15, but the embodiment is not limited to this. For example, the processing circuit 15 may be configured as a combination of multiple independent processors, and each processor may execute a program to realize each processing function. Furthermore, each processing function of the processing circuit 15 may be appropriately distributed or integrated and realized in a single or multiple processing circuits.

[0019] Next, each processing function will be described in detail.

[0020] The acquisition function 15a acquires medical image data of a subject (patient, examinee, etc.) from an external device (electronic medical record system, etc.) or the memory 11. For example, the medical image data is volume data such as an MRI image or a CT image.

[0021] The medical image data is data of a medical image of a region including an artery (first blood vessel) and an artery or vein (second blood vessel). In this embodiment, the medical image data is data of a medical image of a region including a plurality of arteries. That is, both the first blood vessel and the second blood vessel are arteries.

[0022] The site is not particularly limited, but may be, for example, the heart, liver, brain, etc. When the site is the heart, the medical image data includes data on the coronary arteries running on the surface of the tissue (myocardium). When the site is the liver or brain, the medical image data includes data on the arteries inside the tissue.

[0023] The acquisition function 15a may acquire information other than medical image data, such as blood pressure of a subject.

[0024] The identification function 15b is configured to identify at least the dominated area of ​​a first blood vessel based on medical image data, a blood flow intensity coefficient and an attenuation coefficient associated with the first blood vessel, and a blood flow intensity coefficient and an attenuation coefficient associated with the second blood vessel.

[0025] In this embodiment, the identification function 15b is configured to identify the governing regions of the first and second arteries based on the medical image data, the blood flow intensity coefficient and attenuation coefficient of the first artery, and the blood flow intensity coefficient and attenuation coefficient of the second artery. The identification function 15b identifies the governing regions of the first and second arteries by defining a boundary between the governing region of the first artery and the governing region of the second artery. Here, the governing region of an artery is an area that is supplied with nutrients by an artery, and is also called a blood flow region. Note that the boundary is not limited to a boundary line, and may be a boundary surface.

[0026] The blood flow strength coefficient for an artery is a coefficient that represents the strength of the blood flow that diffuses from the inside to the outside of the artery, i.e., this blood flow strength coefficient is a coefficient that represents the force with which blood inside the artery diffuses through the blood vessel wall into the surrounding tissue.

[0027] Specifically, the blood flow intensity coefficient for an artery is determined based on the shape factor and the function factor of the artery. The shape factors include, for example, the arterial blood vessel diameter, the arterial blood vessel length, the arterial blood vessel position, and the thickness of the arterial wall. The function factors include, for example, the blood pressure and the blood flow rate. The blood flow intensity coefficient increases as the arterial blood vessel diameter increases. Also, the blood flow intensity coefficient increases as the arterial blood vessel length increases. The blood flow intensity coefficient also increases when the blood pressure and the blood flow rate are high. The arterial blood vessel position indicates, for example, the distance of the artery from the heart, and the closer the distance from the heart, the higher the blood flow intensity coefficient. The thicker the arterial wall is, the harder it is for blood to diffuse outside the blood vessel, so the blood flow intensity coefficient decreases. Thus, the arterial blood flow intensity coefficient according to this embodiment is a coefficient based on at least one of the arterial blood vessel diameter, the arterial blood vessel length, the arterial blood vessel position, the arterial blood vessel wall thickness, the blood pressure, and the blood flow rate. The identification function 15b determines the blood flow intensity coefficient based on these factors.

[0028] The information on the shape factors and the functional factors may be obtained from medical image data, or from an external device such as a blood pressure monitor. For example, the information on the shape factors is obtained from medical image data, and the information on the functional factors is obtained from an external device. Note that the information on the functional factors can also be obtained from medical image data. For example, the blood vessel shape may be obtained from a CT image, and the blood pressure and blood flow rate may be calculated by fluid calculation, or the blood flow rate may be calculated from an MRI image.

[0029] The attenuation coefficient for an artery is a coefficient that represents the attenuation characteristics of blood flow in tissues (such as the heart muscle) surrounding the artery. More specifically, the attenuation coefficient for an artery is determined based on the shape and function factors of the artery and the tissues surrounding the artery. Examples of the shape factors include the distance from the artery and the position of the thrombus in the artery. As shown in FIG. 2A, the value of the attenuation coefficient β decreases as the position becomes farther from the artery A (i.e., the attenuation of the blood flow becomes greater). As shown in FIG. 2B, when a thrombus T is present in the artery A, the attenuation coefficient β decreases in the direction of the thrombus T. Examples of the functional factors include the properties of the tissues surrounding the artery. For example, when a part of the tissue surrounding the artery A is necrotic and hardened due to a disease, blood becomes difficult to diffuse, and the attenuation coefficient β decreases. In FIG. 2C, in the tissue N that has hardened due to the progression of ischemia, blood becomes difficult to diffuse, and the attenuation coefficient β decreases. The attenuation coefficient β according to this embodiment is a coefficient based on at least one of the distance from the artery, the position of the thrombus in the artery, and the properties of the tissues surrounding the artery. The specification function 15b determines the attenuation coefficient based on these factors. Although the circles in FIGS. 2A to 2C indicate only representative points in the peripheral area of ​​the artery, the attenuation coefficient may be determined for each data point (voxel) of the medical image data.

[0030] The tissue properties may be tissue properties other than hardness (properties that affect blood diffusion). Parts with properties different from other parts, such as necrotic areas or the above-mentioned tissue N, can be detected by CT perfusion, which measures blood flow in tissue using a contrast agent. Alternatively, they may be detected by MRI perfusion. In addition, tissue function may be examined by strain analysis using ultrasound examination results to detect parts with different properties.

[0031] In addition, the identification function 15b may identify the control area based on the blood flow intensity coefficient and attenuation coefficient of the current (pre-treatment) artery, and may also identify the control area based on the blood flow intensity coefficient and attenuation coefficient of the future (post-treatment) artery. That is, the identification function 15b may identify the control area based on the blood flow intensity coefficient and attenuation coefficient of the artery from which the thrombus has been removed. In addition, at this time, the control area of ​​the artery after the virtual treatment may be simulated by using virtual values ​​as the blood flow intensity coefficient and attenuation coefficient.

[0032] The output function 15c outputs data (display data) for displaying the control areas identified by the identification function 15b. In this embodiment, the output function 15c outputs data for displaying the control areas of the first and second arteries identified by the identification function 15b. The output function 15c transmits the display data to the display 12. The display 12, which has received the display data, displays an image in which the borders dividing the control areas of each artery are superimposed on the medical image in which the first and second arteries are depicted. The output function 15c may transmit the display data to an external display device (not shown) connected to the medical image processing device 1 via the communication interface 14.

[0033] When the output function 15c identifies the control area of ​​the artery after the virtual treatment, it may output data for displaying the control area of ​​the artery before the treatment (first control area) and may output data for displaying the control area of ​​the artery after the virtual treatment (second control area). In this case, the output function 15c may output data for displaying the first control area and the second control area in a comparable manner. For example, the output function 15c outputs data for displaying an image including the first control area and an image including the second control area side by side on the same screen. Alternatively, the output function 15c may display the boundary defining the first control area and the boundary defining the second control area superimposed on the same medical image (see FIG. 13 described later).

[0034] <Medical Image Processing Method (First Embodiment)> Next, an example of a medical image processing method using the above-mentioned medical image processing apparatus 1 will be described with reference to the flowchart of FIG.

[0035] Step S1: The acquiring function 15a acquires medical image data of a region including the first and second arteries. In this step, the acquiring function 15a acquires medical image data of a subject from, for example, an image storage device (for example, a reconstruction server that reconstructs a diagnostic image from imaging data, or a PACS (Picture Archiving and Communication System)) communicably connected to the medical image processing device 1.

[0036] Step S2: The identification function 15b identifies the governing regions of the multiple arteries based on the medical image data acquired in step S1, the blood flow intensity coefficient and the attenuation coefficient of the first artery, and the blood flow intensity coefficient and the attenuation coefficient of the second artery. This step will be described in detail with reference to the flowchart of FIG.

[0037] Step S21: The identification function 15b determines a blood flow intensity coefficient and an attenuation coefficient for the first artery, and generates a first vector field related to the first artery. In this step, for example, one of the arteries included in the medical image data acquired in the previous step S1 is focused on, and a vector field of the artery is generated. First, the identification function 15b determines a blood flow intensity coefficient based on at least one of the diameter, length, position, wall thickness, blood pressure, and blood flow rate of the first artery. Furthermore, the identification function 15b determines an attenuation coefficient based on at least one of the distance from the first artery, the position of the thrombus, and the properties of the tissue surrounding the first artery. Then, the identification function 15b generates a first vector field (distance field) related to the first artery based on the determined blood flow intensity coefficient and attenuation coefficient.

[0038] The blood flow vectors constituting the first vector field have a direction of diffusion from the first artery and a magnitude according to the blood flow intensity coefficient and the attenuation coefficient associated with the first artery, for example, the blood flow vector has a magnitude proportional to the product of the blood flow intensity coefficient and the attenuation coefficient.

[0039] FIG. 5 shows an example of a vector field composed of arterial blood flow vectors. The artery A1 on the left side of FIG. 5 is an example of a first artery. A plurality of blood flow vectors bv1 that spread radially from the center C1 of the artery A1 compose the first vector field. Each blood flow vector bv1 has a direction of diffusion from the artery A1 and a magnitude according to the blood flow intensity coefficient and attenuation coefficient related to the artery A1. As described above, the value of the attenuation coefficient β decreases with increasing distance from the artery, so that the magnitude (length) of the blood flow vector bv1 decreases with increasing distance from the artery A1, as shown in FIG. 5.

[0040] Step S22: The identification function 15b determines a blood flow intensity coefficient and an attenuation coefficient for a second artery adjacent to the first artery, and generates a second vector field related to the second artery. In this step, for example, among the multiple arteries included in the medical image data acquired in the previous step S21, the identification function 15b focuses on the second artery adjacent to the first artery, and generates a vector field of the second artery. The specific method of generating the second vector field is the same as that of the first artery. That is, first, the identification function 15b determines a blood flow intensity coefficient based on at least one of the diameter, length, position, wall thickness, blood pressure, and blood flow rate of the second artery. Furthermore, the identification function 15b determines an attenuation coefficient based on at least one of the distance from the second artery, the position of the thrombus, and the properties of the tissue surrounding the second artery. Then, the identification function 15b generates a second vector field (distance field) related to the second artery based on the determined blood flow intensity coefficient and attenuation coefficient.

[0041] The artery A2 on the right side of FIG. 5 shows an example of a second artery. A plurality of blood flow vectors bv2 radially spreading from the center C2 of the artery A2 constitute a second vector field. Each blood flow vector bv2 has a direction of spreading from the artery A2 and a magnitude according to the blood flow intensity coefficient and the attenuation coefficient of the artery A2. The magnitude of the blood flow vector bv2 is proportional to, for example, the product of the blood flow intensity coefficient and the attenuation coefficient. As with the blood flow vector bv1, the blood flow vector bv2 becomes smaller as it moves away from the artery A2. Note that in the example of FIG. 5, since the artery A1 has a larger diameter than the artery A2, the blood flow intensity coefficient of the artery A1 is larger than the blood flow intensity coefficient of the artery A2. Therefore, when compared at positions at the same distance from the centers of the arteries A1 and A2, the magnitude of the blood flow vector bv1 is larger than the blood flow vector bv2.

[0042] Step S23: The identifying function 15b determines a boundary B between the control area D1 of the artery A1 and the control area D2 of the artery A2 based on the first vector field and the second vector field generated in steps S21 and S22. For example, the identifying function 15b obtains a plurality of points where the projections of the blood flow vectors of each vector field on a line parallel to the line passing through the first artery and the second artery cancel each other out, and connects the obtained plurality of points. More specifically, as shown in FIG. 6, a line L2 parallel to the line L1 passing through the center C1 of the artery A1 and the center C2 of the artery A2 is considered, and a point on the line L2 where the projection vector bv1p of the blood flow vector bv1 of the first vector field on the line L2 and the projection vector bv2p of the blood flow vector bv2 of the second vector field on the line L2 cancel each other out (i.e., a point where the directions of the projection vectors are opposite and the magnitudes are equal, and the sum of the projection vectors is 0). Next, the straight line L2 is translated, and a point P on the straight line L2 where the sum of the projection vectors is 0 is similarly found. By repeating this process, multiple points P are found. In FIG. 6, the sum of the projection vectors is 0 at each point P. The identifying function 15b defines the boundary B between the control area D1 of the artery A1 and the control area D2 of the artery A2 by connecting the multiple points P found in this manner. Note that FIG. 6 shows only representative points P.

[0043] The straight line L1 is not limited to a line passing through the centers of the first and second arteries, but may be a line passing through a representative point such as the center of gravity of the cross-sectional shape of each artery. Moreover, the straight line L1 may be a straight line passing through an arbitrary point in the first artery and an arbitrary point in the second artery.

[0044] Also, the method of finding the point P is not limited to the above method. For example, the identifying function 15b may generate a composite vector field by combining the first vector field and the second vector field. In this case, the identifying function 15b may determine a plurality of vectors in the composite vector field that are perpendicular to the straight line L1, and define the boundary B by connecting the base points of the plurality of vectors that have been found.

[0045] In addition, the target is not limited to arteries inside tissue, but may be arteries on the surface of tissue such as myocardium. Fig. 7 shows an example of control areas D1 and D2 of arteries specified by boundary B when arteries A1 and A2 exist on the surface of tissue (such as coronary arteries of myocardium).

[0046] For arteries other than arteries A1 and A2 included in the medical image, the control area is specified by executing steps S21 to S23. For example, in Fig. 6, if there is another artery adjacent to artery A2 on the right side of artery A2, a blood flow intensity coefficient and an attenuation coefficient are determined for the other artery, a vector field is generated, and then a boundary between the control area of ​​artery A2 and the control area of ​​the other artery is obtained based on the vector field and a second vector field related to artery A2.

[0047] Returning to the flowchart of FIG.

[0048] Step S3: The output function 15c outputs data (display data) for displaying the control areas of the first and second arteries identified in step S2. In this embodiment, the output function 15c transmits the display data to the display 12. The display 12 displays an image in which the boundary B dividing the control areas D1, D2 of the arteries A1, A2 is superimposed on the medical image in which the first and second arteries are depicted. That is, the output function 15c outputs data for superimposing the boundary on the medical image together with the first and second arteries.

[0049] The medical image displayed on the display 12 may be a tomographic image of a three-dimensional tissue such as the heart, or may be a two-dimensional image of the surface of the three-dimensional tissue expanded by an equal-area projection (equivalent area projection). An equal-area projection is a projection in which the ratio between the area on the earth and the area on the corresponding map (i.e., the area scale) is the same everywhere. As the equal-area projection, various projections such as the Mollweide projection, the Sanson projection, and the Lambert equal-area projection can be used.

[0050] Furthermore, the boundary B is not limited to being displayed as a boundary line as shown in FIG. 6, but may be shown by displaying the dominance area D1 and the dominance area D2 in different display forms (colors, brightness, etc.).

[0051] According to the first embodiment described above, the governing area of ​​each artery can be specified more accurately by considering the blood flow intensity coefficient and attenuation coefficient of each artery. Specifically, the governing area is specified taking into consideration the blood vessel characteristics unique to each patient, such as the blood flow rate, blood pressure, blood vessel shape, and position of each artery, so that the governing area of ​​the artery can be specified accurately.

[0052] <Modification> Next, a method for identifying a control area according to a modified example of the first embodiment will be described with reference to the flowchart in Fig. 8. In this modified example, the control area of ​​each artery is identified taking into consideration the influence on blood flow of veins surrounding the first and second arteries. Fig. 8 shows a detailed flow of the process in step S2.

[0053] Step S21a: The determination function 15b determines a blood flow intensity coefficient and an attenuation coefficient for the first artery, and generates a first vector field for the first artery. This step is the same as step S21 described above, so a detailed description is omitted.

[0054] Step S22a: The determining function 15b determines a blood flow intensity coefficient and an attenuation coefficient for a second artery adjacent to the first artery, and generates a second vector field for the second artery. This step is the same as the above-mentioned step S22, so a detailed description is omitted.

[0055] Step S23a: The determining function 15b determines a blood flow intensity coefficient and an attenuation coefficient for a vein included in the region of the medical image data, and generates a third vector field related to the vein. For example, the vein is a vein V between an artery A1 and an artery A2, as shown in FIG. 9A.

[0056] The blood flow vector constituting the third vector field related to the vein has a direction of converging on the vein and a magnitude according to the blood flow intensity coefficient and attenuation coefficient related to the vein. The blood flow intensity coefficient related to the vein is a coefficient representing the intensity of the blood flow of the blood converging from the outside to the inside of the vein, and the attenuation coefficient related to the vein is a coefficient representing the attenuation characteristics of the blood flow in the tissue (myocardium, etc.) surrounding the vein. The blood flow intensity coefficient and attenuation coefficient related to the vein are determined in the same manner as in the case of the artery. That is, the specific function 15b determines the blood flow intensity coefficient based on at least one of the vein's blood vessel diameter, blood vessel length, blood vessel position, vascular wall thickness, blood pressure, and blood flow rate, and determines the attenuation coefficient based on at least one of the distance from the vein, the position of the thrombus in the vein, and the properties of the tissue surrounding the vein.

[0057] 9B shows an example of a vector field formed by blood flow vectors of a vein. A plurality of blood flow vectors bv3 converging toward the center C3 of the vein V constitute a third vector field. Each blood flow vector bv3 has a direction converging on the vein V and a magnitude according to the blood flow intensity coefficient and attenuation coefficient associated with the vein V. As shown in FIG. 9B, the magnitude (length) of the blood flow vector bv3 decreases with increasing distance from the vein V.

[0058] Step S24a: The identification function 15b generates a first resultant vector field by combining the first vector field and the third vector field, and generates a second resultant vector field by combining the second vector field and the third vector field.

[0059] Step S25a: The identification function 15b determines a boundary between the region governed by the first artery and the region governed by the second artery based on the first resultant vector field and the second resultant vector field. The boundary can be determined in the same manner as in step S23 described above. For example, the identification function 15b determines a plurality of points at which the projections of the blood flow vectors of each resultant vector field on a line parallel to the line passing through the first artery and the second artery cancel each other out, and determines the boundary by connecting the determined plurality of points.

[0060] More specifically, as shown in FIG. 9A, a straight line L2 parallel to a straight line L1 passing through the center C1 of the artery A1 and the center C2 of the artery A2 is considered, and a point is obtained where a projection vector bv1cp of the blood flow vector bv1c of the first resultant vector field onto the straight line L2 and a projection vector bv2cp of the blood flow vector bv2c of the second resultant vector field onto the straight line L2 cancel each other out. In FIG. 9A, the sum of the projection vectors at each point Pc is 0. The specification function 15b defines a boundary Bc between the control area D1 of the artery A1 and the control area D2 of the artery A2 when the vein V exists by connecting the multiple points Pc obtained in this manner. Note that the boundary B in FIG. 9A shows the boundary when the vein V does not exist.

[0061] According to this modification, as described above, it is possible to specify the governing area of ​​the artery by taking into consideration the presence of the vein. In the example of Fig. 9A, since the vein V exists on the side of the artery A1, the boundary is shifted toward the artery A1 side compared to the case where the vein V does not exist.

[0062] The method of finding the point Pc is not limited to the above method. For example, the specification function 15b may generate a third resultant vector field by combining the first resultant vector field and the second resultant vector field, find a plurality of vectors perpendicular to the straight line L1 in the third resultant vector field, and define the boundary Bc by connecting the base points of the plurality of vectors found.

[0063] Also, as shown in FIG. 10, blood flows bf1 and bf2 based on blood flow vectors may be displayed in a medical image that displays the governing area of ​​each identified artery. The circles in FIG. 10 indicate only representative points in the peripheral area of ​​the artery (similarly in FIG. 11). The output function 15c outputs data for displaying the blood flow from the artery A1 to the vein V based on the first resultant vector field, and outputs data for displaying the blood flow from the artery A2 to the vein V based on the second resultant vector field. Thereby, the blood flow bf1 formed by connecting the blood flow vectors bv1c of the first resultant vector field is displayed, and the blood flow bf2 formed by connecting the blood flow vectors bv2c of the second resultant vector field is displayed. The blood flows bf1 and bf2 are discharged from the arteries A1 and A2 and absorbed into the vein V. It is also possible to display only one of the blood flows bf1 and bf2. The blood flow may be obtained by connecting the blood flow vectors for each data point (voxel) of the medical image data.

[0064] Also, the lines indicating the blood flows bf1 and bf2 may be displayed with a gradation. For example, the lines indicating the blood flows may be displayed with a gradation such that the arterial side is a first color (e.g., red) and the venous side is a second color (e.g., blue).

[0065] Also, as shown in Fig. 11, in a medical image showing the control area of ​​each identified artery, each control area may be displayed by gradation. In this case, the output function 15c outputs data for displaying the control area of ​​the first artery and the control area of ​​the second artery by gradation so that the arterial side is a first color and the venous side is a second color. As a result, as shown in Fig. 11, the control area D1 of the artery A1 and the control area D2 of the artery A2 are displayed by gradation so that the arterial side is a first color (e.g., red) and the venous side is a second color (e.g., blue).

[0066] 10 and 11, the blood flow vectors bv1c and bv2c do not have to be displayed. Whether or not to display the blood flow vectors and which artery the blood flow is to be displayed from may be specified by the user via the input interface 13 of the medical image processing device 1.

[0067] <Application Examples> Next, as a specific application example of the above-mentioned medical image processing apparatus and method, application to identifying the region controlled by the coronary arteries of the heart will be described.

[0068] FIG. 12 shows an example of a display image in which the surface of the heart is expanded into a two-dimensional image by the equal area projection method. In the figure, a plurality of arrows pointing to the boundary B1 indicate blood flow vectors. These arrows may not be displayed. As shown in FIG. 12, in this example, the coronary artery CA branches into the coronary artery CA1 and the coronary artery CA2, and the coronary artery CA1 is thicker than the coronary artery CA2. The coronary artery CA1 is constricted by a thrombus TA, so that the blood flow rate is reduced compared to a normal state. In addition, a necrotic area NA of the myocardium exists between the coronary artery CA1 and the coronary artery CA2. The boundary B1 indicates a boundary obtained by the method for identifying the control area according to the above-mentioned embodiment, and is a boundary between the control area DA1 of the coronary artery CA1 and the control area DA2 of the coronary artery CA2. As shown in FIG. 12, the boundary B1 straddles the necrotic area NA. The boundary B1 can be used as a resection line with less bleeding when performing a resection operation of the necrotic area NA.

[0069] FIG. 13 shows an example of a display image in which the thrombus TA is virtually removed in the simulation. In the figure, multiple arrows pointing to the boundary B2 indicate blood flow vectors. These arrows do not have to be displayed. In this example, it is assumed that the thrombus TA has been removed, and the control area is identified based on the blood flow intensity coefficient and attenuation coefficient in the normal state of the coronary artery CA1. In FIG. 13, the boundary B2 between the identified control areas is superimposed on the image of the myocardium. The boundary B2 shifts to the coronary artery CA2 side, and the necrotic area NA is included in the control area DA1 of the coronary artery CA1. From this result, a user such as a doctor can predict that the necrotic area NA will all belong to the control area of ​​the coronary artery CA1 by removing the thrombus TA. In addition, when there are multiple thrombi in an artery, a user such as a doctor can investigate what kind of vascular treatment is effective by performing multiple simulations while changing the thrombi to be removed.

[0070] 13, the boundary B1 before the treatment may be displayed so as to be distinguishable from the boundary B2, thereby allowing the change in the boundary due to the treatment to be easily understood.

[0071] Furthermore, this is not limited to cases where a thrombus is removed, but it is also possible to simulate changes in the control area of ​​an artery adjacent to a blood vessel before performing treatment such as tying off or cutting the blood vessel.

[0072] In order to compare the control area before treatment with the control area according to the simulation result (control area after virtual treatment), the images in Fig. 12 and Fig. 13 may be displayed simultaneously on the display 12. This allows users such as doctors to easily grasp the predicted treatment effect in advance.

[0073] As shown in Figures 14A and 14B, the display mode of the boundary between the control regions may be changed according to the strength of the blood flow that hits the boundary. For example, when both the coronary artery CA1 and the coronary artery CA2 are thick and the blood flow rate is large, a relatively thick boundary B may be displayed as shown in Figure 14A. On the other hand, when the coronary artery CA1 and the coronary artery CA2 are thin, a thin boundary B may be displayed as shown in Figure 14B. Note that the display mode to be changed is not limited to the thickness of the boundary B, and may also be the color, line type, etc. of the boundary B.

[0074] In this way, the output function 15c may change the display form of the boundary according to the magnitude of the blood flow toward the boundary. This allows a user such as a doctor to easily understand the strength of the blood flow from the display form of the boundary. For example, to avoid a cumbersome screen display, the blood flow vector (the arrow toward the boundary B) may be hidden in Figures 14A and 14B, and even in this case, the strength of the blood flow can be easily understood from the display form of the boundary.

[0075] As shown in FIG. 15, the boundary may be displayed with a gradation according to the strength of the blood flow. That is, the boundary B may be displayed with a gradation according to the magnitude of the blood flow toward the boundary along the boundary B. For example, the boundary B is displayed with a gradation such that the part with the strongest blood flow is a first color (for example, dark red) and the part with the weakest blood flow is a second color (for example, light red). This allows a user such as a doctor to easily understand the part with the strongest (or weakest) blood flow from the gradation of the boundary. For example, the blood flow vector (the arrow toward the boundary B) may be hidden in FIG. 15 to avoid a cumbersome screen display, and even in this case, the strength of the blood flow at each part of the boundary can be easily understood from the gradation of the boundary.

[0076] The output function 15c may output data for indicating which of the control regions identified by the identification function 15b a tissue whose characteristics are different from normal, such as tissue that has hardened due to ischemia, a necrotic area, or a lesion, belongs to. In the example of FIG. 16, a pop-up display indicates that the necrotic area NA belongs to the control region DA1. This allows a user such as a doctor to easily understand which artery's control region the tissue whose characteristics are different from normal belongs to. The display format is not limited to the pop-up format.

[0077] Furthermore, the output function 15c may output data for indicating that the size of the control area identified by the identification function 15b is different from the standard size by a predetermined value or more. In the example of FIG. 17, a pop-up display indicates that the size of the control area DA1 is 18% smaller than the standard size due to a thrombus TA in the coronary artery CA1. This allows a user such as a doctor to easily grasp the control area that is different from the standard size by a predetermined value or more. Note that the display format is not limited to the pop-up format.

[0078] As described above, in the first embodiment, the governing area of ​​a plurality of arteries is specified by taking into consideration the blood flow intensity coefficient and attenuation coefficient of the plurality of arteries, so that the governing area of ​​each artery can be specified more accurately. This makes it possible to perform an accurate simulation of reperfusion, and to determine a resection line with less bleeding when performing a resection operation on a necrotic part of the myocardium.

[0079] Second embodiment In the first embodiment, when a first artery and a second artery exist, the governing area of ​​each artery is specified. In the second embodiment, when an artery and a vein exist, the governing area of ​​the artery is specified. The configuration of the medical image processing device according to the second embodiment is the same as that of the medical image processing device 1 described in the first embodiment, and therefore the description will be omitted.

[0080] <Medical image processing method (second embodiment)> An example of a medical image processing method according to the second embodiment will be described with reference to the flowchart of FIG.

[0081] Step S1A: The acquisition function 15a acquires medical image data of a region including an artery and a vein adjacent to the artery. The details of the method of acquiring the medical image data are the same as those of step S1 described above.

[0082] Step S2A: The identification function 15b identifies the control area of ​​the artery based on the medical image data acquired in step S1A, the blood flow intensity coefficient and attenuation coefficient related to the artery, and the blood flow intensity coefficient and attenuation coefficient related to the vein. Details of this step will be described in detail with reference to the flowchart in FIG.

[0083] Step S21b: The determination function 15b determines a blood flow intensity coefficient and an attenuation coefficient for the artery, and generates a first vector field for the artery. The details of this step are the same as those of step S21 described above.

[0084] Step S22b: The determination function 15b determines a blood flow intensity coefficient and an attenuation coefficient for the vein, and generates a second vector field for the vein. The specific method for generating the second vector field is the same as that of the above-mentioned step S23a.

[0085] Step S23b: The identifying function 15b determines the boundary of the governing region of the artery based on the first vector field and the second vector field generated in steps S21b and S22b. For example, the identifying function 15b obtains a plurality of points where the projections of the blood flow vectors of each vector field on a line parallel to the line passing through the artery and the vein cancel each other out, and connects the obtained plurality of points. More specifically, as shown in FIG. 20, a line L2 parallel to a line L1 passing through the center C1 of the artery A and the center C3 of the vein V is considered, and a point P on the line L2 where the projection vector bv1p of the blood flow vector bv1 of the first vector field on the line L2 and the projection vector bv3p of the blood flow vector bv3 of the second vector field on the line L2 cancel each other out is obtained. Next, the line L2 is translated, and a point on the line L2 where the sum of the projection vectors is 0 is obtained in the same manner. This is repeated to obtain a plurality of points. The identification function 15b defines the boundary B of the control area D1 of the artery A by connecting the multiple points thus obtained.

[0086] Returning to the flowchart of FIG.

[0087] Step S3A: The output function 15c outputs data (display data) for displaying the governing area of ​​the artery identified in step S2 A. The details of this step are the same as those of step S3 described above.

[0088] The output function 15c may output data for displaying the blood flow from the artery to the vein based on the first and second vector fields. This allows a screen display similar to that of the modified example of the first embodiment. The lines indicating the blood flow may be displayed using gradation. The output function 15c may output data for displaying the governed area of ​​the artery using gradation such that the arterial side is a first color and the venous side is a second color.

[0089] As described above, in the second embodiment, the arterial governing area is identified by taking into account the blood flow intensity coefficient and attenuation coefficient related to the artery and the blood flow intensity coefficient and attenuation coefficient related to the vein, so that the arterial governing area can be identified more accurately.

[0090] (Third embodiment) Next, a medical image processing apparatus according to a third embodiment will be described. Fig. 21 is a block diagram showing an example of the configuration of a medical image processing apparatus 1A according to this embodiment. In Fig. 21, components having the same functions as those in Fig. 1 are given the same reference numerals.

[0091] The medical image processing device 1A includes a Voronoi specifying function 15d and a determining function 15e in addition to the functions (acquiring function 15a, specifying function 15b, and output function 15c) of the processing circuit 15 described in the first embodiment. The Voronoi specifying function 15d is an example of a Voronoi specifying unit, and the determining function 15e is an example of a determining unit.

[0092] In this embodiment, each processing function executed by the acquisition function 15a, the identification function 15b, the output function 15c, the Voronoi identification function 15d, and the determination function 15e is stored in the memory 11 in the form of a program executable by a computer. That is, the processing circuit 15 is configured by a processor, and realizes the function corresponding to each program by reading and executing the program from the memory 11. In other words, the processing circuit 15 in the state where each program is read has each function shown in the processing circuit 15 of FIG.

[0093] The Voronoi identification function 15d identifies the governing area of ​​the blood vessel by the Voronoi fractionation method. More specifically, the Voronoi identification function 15d identifies the governing area of ​​the first blood vessel and the governing area of ​​the second blood vessel by the Voronoi fractionation method based on the shape information of the first blood vessel and the shape information of the second blood vessel included in the medical image data.

[0094] The decision function 15e decides whether to use the identification function 15b or the Voronoi identification function 15d to identify the dominant region based on a predetermined condition. The predetermined condition is a required identification accuracy, a machine specification (processing speed, etc.) of the medical image processing device, an urgency of the surgery or examination, etc.

[0095] <Medical image processing method (third embodiment)> An example of a medical image processing method using the above-mentioned medical image processing apparatus 1A will be described with reference to a flowchart in FIG.

[0096] Step S1B: The acquisition function 15a acquires medical image data of a region including a plurality of blood vessels. The details of the method of acquiring the medical image data are the same as those of step S1 described above.

[0097] Step S2B: The acquiring function 15a acquires a predetermined condition for determining the identification method. For example, the acquiring function 15a acquires a required identification accuracy, urgency, and the like input by the user via the input interface 13 as the predetermined condition. The acquiring function 15a may acquire information on the machine specifications of the medical image processing device 1A from the operating system of the medical image processing device 1A or the like as the predetermined condition. Alternatively, the acquiring function 15a may acquire information indicating urgency from the electronic medical record of the patient or the like as the predetermined condition.

[0098] Step S3B: The determination function 15e determines a method for identifying the control region based on the predetermined conditions acquired in step S2B. For example, the determination function 15e determines to perform identification using the Voronoi identification function 15d when the accuracy required for defining the control region (identification accuracy) is low, when the machine specifications of the medical image processing device 1A are low, or when the urgency is high.

[0099] Step S4B: According to the method determined in step S3B, the determination function 15b or the Voronoi determination function 15d determines the dominating region. That is, if the determination function 15e determines to perform the determination using the determination function 15b, the above-mentioned step S2 or step S2A is performed in this step. On the other hand, if the determination function 15e determines to perform the determination using the Voronoi determination function 15d, the Voronoi determination function 15d determines the dominating region by the Voronoi fractionation method.

[0100] Step S5B: The output function 15c outputs data for displaying the control area identified in step S4B. Based on the data, the display 12 displays an image in which the boundary of the control area of ​​the artery is superimposed on the medical image in which the artery is drawn.

[0101] According to the third embodiment, it is possible to appropriately use a method for specifying a dominant region using the Voronoi fractionation method and a method for specifying a dominant region taking into account blood vessel characteristics specific to a patient, depending on conditions such as required specification accuracy.

[0102] It is also possible to perform both the identification of the dominance region by the identification function 15b and the identification of the dominance region by the Voronoi identification function 15d. In this case, the output function 15c may output data for displaying the dominance region identified by the Voronoi identification function 15d in addition to data for displaying the dominance region identified by the identification function 15b. FIG. 23 is an example of a screen displaying both the boundary B defined by the identification function 15b and the boundary Bvo defined by the Voronoi identification function 15d. The boundary B and the boundary Bvo may be distinguished from each other by changing the display form such as the color or type of the line.

[0103] Furthermore, the above-described medical image processing method is merely an example, and various modifications are possible. For example, steps S2B and S3B may be performed before step S1B.

[0104] The term "processor" used in the above description means a circuit such as a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)). The processor realizes its function by reading and executing a program stored in the memory 11. Instead of storing the program in the memory 11, the processor may be configured to directly incorporate the program in its circuit. In this case, the processor realizes its function by reading and executing the program incorporated in its circuit. The processor is not limited to being configured as a single processor circuit, and may be configured as a single processor by combining multiple independent circuits to realize its function. Furthermore, the multiple components in FIG. 1 may be integrated into a single processor to realize its function.

[0105] The medical image processing method described in Figures 3, 4, 8, 18, 19, and 22 can be realized by executing a prepared medical image processing program on a computer such as a personal computer or a workstation. This medical image processing program can be distributed via a network such as the Internet. This medical image processing program can also be recorded on a non-transitory recording medium readable by a computer such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, or a DVD, and executed by being read from the recording medium by a computer.

[0106] Although several embodiments have been described above, these embodiments are presented only as examples and are not intended to limit the scope of the invention. The novel device and method described in this specification can be implemented in various other forms. In addition, various omissions, substitutions, and modifications can be made to the forms of the device and method described in this specification without departing from the spirit of the invention. The appended claims and their equivalents are intended to include such forms and modifications that fall within the scope and spirit of the invention. [Explanation of symbols]

[0107] 1 Medical image processing device 11. Memory 12 Display 13 Input Interface 14 Communication Interface 15 Processing circuit 15a Acquisition Function 15b Specific functions 15c Output Function 15d Voronoi specific function 15e Decision Function A,A1,A2 arteries bf1,bf2 blood flow bv,bv1,bv2,bv1c,bv2c Blood flow vector bv1p,bv2p,bv1cp,bv2cp Projection vectors B,Bc,B1,B2 boundary CA, CA1, CA2 coronary arteries C1,C2 center D1,D2,DA1,DA2 Control area L1,L2 straight line N organization NA Necrotic area P,Pc points M1,M2 Message T,TA Thrombus V vein

Claims

1. an acquisition unit that acquires medical image data of a region including a first blood vessel that is an artery and a second blood vessel that is an artery or a vein; an identification unit that identifies a governing region of the first blood vessel based on the medical image data, a blood flow intensity coefficient and an attenuation coefficient of the first blood vessel, and a blood flow intensity coefficient and an attenuation coefficient of the second blood vessel; an output unit that outputs data for displaying the identified control region; A medical image processing device comprising:

2. the blood flow intensity coefficient for the first blood vessel is a coefficient based on at least one of a blood vessel diameter, a blood vessel length, a blood vessel position, a blood vessel wall thickness, a blood pressure, and a blood flow rate of the first blood vessel, and the attenuation coefficient for the first blood vessel is a coefficient based on at least one of a distance from the first blood vessel, a position of a thrombus in the first blood vessel, and a property of a tissue surrounding the first blood vessel; 2. The medical image processing device according to claim 1, wherein the blood flow intensity coefficient for the second blood vessel is a coefficient based on at least one of the blood vessel diameter, blood vessel length, blood vessel position, blood vessel wall thickness, blood pressure, and blood flow rate of the second blood vessel, and the attenuation coefficient for the second blood vessel is a coefficient based on at least one of the distance from the second blood vessel, the position of a thrombus in the second blood vessel, and the properties of the tissue surrounding the second blood vessel.

3. the second blood vessel is an artery adjacent to the first blood vessel; A blood flow intensity coefficient of the first blood vessel represents the intensity of blood flow of blood diffusing from the inside to the outside of the first blood vessel, and an attenuation coefficient of the first blood vessel represents the attenuation characteristics of the blood flow in tissue surrounding the first blood vessel; a blood flow intensity coefficient of the second blood vessel represents the intensity of blood flow of blood diffusing from the inside to the outside of the second blood vessel, and an attenuation coefficient of the second blood vessel represents the attenuation characteristics of the blood flow in tissue surrounding the second blood vessel; The identification unit identifies governing regions of the first blood vessel and the second blood vessel, the output unit outputs data for displaying governing regions of the first blood vessel and the second blood vessel. The medical image processing device according to claim 1 .

4. The identification unit is generating a first vector field for the first blood vessel, the blood flow vector constituting the first vector field having a direction of diffusion from the first blood vessel and a magnitude according to a blood flow intensity coefficient and an attenuation coefficient related to the first blood vessel; generating a second vector field for the second blood vessel, the blood flow vector constituting the second vector field having a direction of diffusion from the second blood vessel and a magnitude according to a blood flow intensity coefficient and an attenuation coefficient related to the second blood vessel; defining a boundary between a region dominated by the first vessel and a region dominated by the second vessel based on the first vector field and the second vector field; The medical image processing device according to claim 3 .

5. the region of the medical image data includes a third blood vessel that is a vein; The blood flow intensity coefficient of the third blood vessel represents the intensity of the blood flow of blood converging from the outside to the inside of the third blood vessel, and the attenuation coefficient of the third blood vessel represents the attenuation characteristics of the blood flow in tissue surrounding the third blood vessel; the identifying unit identifies governing regions of the first blood vessel and the second blood vessel based on the medical image data and blood flow intensity coefficients and attenuation coefficients related to the first to third blood vessels; the output unit outputs data for displaying governing regions of the first blood vessel and the second blood vessel. The medical image processing device according to claim 3 .

6. The identification unit is generating a first vector field for the first blood vessel, the blood flow vector constituting the first vector field having a direction of diffusion from the first blood vessel and a magnitude according to a blood flow intensity coefficient and an attenuation coefficient related to the first blood vessel; generating a second vector field for the second blood vessel, the blood flow vector constituting the second vector field having a direction of diffusion from the second blood vessel and a magnitude according to a blood flow intensity coefficient and an attenuation coefficient related to the second blood vessel; generating a third vector field for the third blood vessel, the blood flow vector constituting the third vector field having a direction converging on the third blood vessel and a magnitude according to a blood flow intensity coefficient and an attenuation coefficient related to the third blood vessel; combining the first vector field and the third vector field to generate a first resultant vector field, and combining the second vector field and the third vector field to generate a second resultant vector field; defining a boundary between a region dominated by the first blood vessel and a region dominated by the second blood vessel based on the first resultant vector field and the second resultant vector field; The medical image processing device according to claim 5 .

7. 7. The medical image processing device according to claim 6, wherein the output unit outputs data for displaying blood flow from the first blood vessel to the third blood vessel based on the first resultant vector field, and / or outputs data for displaying blood flow from the second blood vessel to the third blood vessel based on the second resultant vector field.

8. The medical image processing apparatus according to claim 7 , wherein the line indicating the blood flow is displayed in a gradation such that the arterial side is in a first color and the venous side is in a second color.

9. 7. The medical image processing device according to claim 6, wherein the output unit outputs data for displaying the governed area of ​​the first blood vessel and the governed area of ​​the second blood vessel using a gradation such that an arterial side is a first color and a venous side is a second color.

10. the second blood vessel is a vein adjacent to the first blood vessel; A blood flow intensity coefficient of the first blood vessel represents the intensity of blood flow of blood diffusing from the inside to the outside of the first blood vessel, and an attenuation coefficient of the first blood vessel represents the attenuation characteristics of the blood flow in tissue surrounding the first blood vessel; A blood flow intensity coefficient of the second blood vessel represents the intensity of blood flow converging from the outside to the inside of the second blood vessel, and an attenuation coefficient of the second blood vessel represents the attenuation characteristics of the blood flow in tissue surrounding the second blood vessel; The identification unit identifies a control region of the first blood vessel, The output unit outputs data for displaying a control region of the first blood vessel. The medical image processing device according to claim 1 .

11. The identification unit is generating a first vector field for the first blood vessel, the blood flow vector constituting the first vector field having a direction of diffusion from the first blood vessel and a magnitude according to a blood flow intensity coefficient and an attenuation coefficient related to the first blood vessel; generating a second vector field for the second blood vessel, the blood flow vector constituting the second vector field having a direction converging on the second blood vessel and a magnitude according to a blood flow intensity coefficient and an attenuation coefficient related to the second blood vessel; determining a boundary of a control region of the first vessel based on the first vector field and the second vector field; The medical image processing device according to claim 10.

12. The medical image processing device according to claim 1 , wherein the output unit outputs data for displaying a boundary of the control region together with the first and second blood vessels, and a display form of the boundary changes depending on a magnitude of blood flow toward the boundary.

13. 2. The medical image processing device according to claim 1, wherein the output unit outputs data for displaying a boundary of the control region together with the first and second blood vessels, and the boundary is displayed with a gradation according to a magnitude of blood flow toward the boundary along the boundary.

14. the identification unit identifies a first control region of the first blood vessel based on a blood flow intensity coefficient and an attenuation coefficient of the first blood vessel before treatment, and identifies a second control region of the first blood vessel based on a blood flow intensity coefficient and an attenuation coefficient of the first blood vessel after virtual treatment; The medical image processing apparatus according to claim 1 , wherein the output unit outputs data for displaying the first and second control regions in a comparable manner.

15. The medical image processing apparatus according to claim 1 , wherein the output unit outputs data indicating to which of the identified control regions a tissue having an abnormal property belongs.

16. The medical image processing apparatus according to claim 1 , wherein the output unit outputs data indicating that the size of the specified control region differs from a standard size by a predetermined value or more.

17. the second blood vessel is an artery adjacent to the first blood vessel; a Voronoi identification unit that identifies a governing region of the first blood vessel and a governing region of the second blood vessel by a Voronoi fractionation method based on shape information of the first blood vessel and shape information of the second blood vessel; a determination unit that determines whether the identification unit or the Voronoi identification unit is to identify a dominating region based on a predetermined condition; Further equipped with 2. The medical image processing device according to claim 1, wherein when the determination unit determines to perform identification of the dominance region by the Voronoi identification unit, the Voronoi identification unit identifies the dominance regions of the first and second blood vessels, and the output unit outputs data for displaying the dominance region identified by the Voronoi identification unit instead of data for displaying the dominance region identified by the identification unit.

18. the second blood vessel is an artery adjacent to the first blood vessel; a Voronoi identification unit that identifies a governing region of the first blood vessel and a governing region of the second blood vessel by a Voronoi fractionation method based on shape information of the first blood vessel and shape information of the second blood vessel, The medical image processing apparatus according to claim 1 , wherein the output unit outputs data for displaying the dominance region identified by the Voronoi identifying unit, in addition to data for displaying the dominance region identified by the identifying unit.

19. acquiring medical image data of a site including a first blood vessel which is an artery and a second blood vessel which is an artery or a vein; identifying a governing region of the first blood vessel based on the medical image data, a blood flow intensity coefficient and an attenuation coefficient related to the first blood vessel, and a blood flow intensity coefficient and an attenuation coefficient related to the second blood vessel; outputting data for displaying the identified control region; Medical image processing method.

20. acquiring medical image data of a site including a first blood vessel which is an artery and a second blood vessel which is an artery or a vein; identifying a governing region of the first blood vessel based on the medical image data, a blood flow intensity coefficient and an attenuation coefficient related to the first blood vessel, and a blood flow intensity coefficient and an attenuation coefficient related to the second blood vessel; A medical image processing program for causing a computer to execute the steps of: outputting data for displaying the identified control region.

Images