Information processing device, information processing method, and recording medium

Abstract

A blood flow distribution determination unit (111) analyzes first three-dimensional time-series images including an analysis target part of a subject which are captured by an MRI (Magnetic Resonance Imaging) device employing a phase contrast method to determine a blood flow velocity distribution in the analysis target part. A shape determination unit (112) analyzes second three-dimensional time-series images that are captured by a different imaging method from that employed in the phase contrast method and show the anatomy of the subject to determine the shape of the analysis target part. An image generation unit (113) generates a fusion image produced by superposing the first three-dimensional time-series images and the second three-dimensional time-series images on each other. An index generation unit (114) generates an index associated with the blood flow flowing in the shape, on the basis of the blood flow velocity distribution and the shape in the fusion image. An output unit (115) outputs the shape and the index while associating the shape and the index with each other. As a result, a burden on the subject during the measurement of a blood flow is reduced.

Description

Information processing device, information processing method, and recording medium

[0001] The present invention relates to an information processing device, an information processing method, and a recording medium, and more particularly to a technique for generating an index relating to blood flow from an MRI (Magnetic Resonance Imaging) image.

[0002] 2. Description of the Related Art There is known a technique for visualizing the distribution of blood flow within a blood vessel as vectors from images obtained by an ultrasound diagnostic device, MRI phase images, or the like (see, for example, Patent Document 1).

[0003] International Publication No. 2013 / 077013

[0004] Itatani K, Sekine T, Yamagishi M, Maeda Y, Higashitani N, Miyazaki S, Matsuda J, Takehara Y. Hemodynamic Parameters for Cardiovascular System in 4D Flow MRI: Mathematical Definition and Clinical Applications. Magn Reson Med Sci. 2022; 21(2):380-399.

[0005] Ultrasound has the problem that it is difficult to reach certain areas, such as the distal ascending aorta and the aortic arch, making imaging of these areas difficult. While MRI images can visualize these areas, contrast agents are used to increase the contrast of the images for more accurate measurements. However, the use of contrast agents places a burden on the subject, and it is desirable to reduce the burden on the subject.

[0006] The present invention has been made in consideration of these points, and aims to provide a technique for reducing the burden on a subject when measuring blood flow.

[0007] A first aspect of the present invention is an information processing device comprising: a blood flow distribution specifying unit that specifies a blood flow velocity distribution in a region to be analyzed of a subject by analyzing first three-dimensional time-series images including the region to be analyzed of the subject, the first three-dimensional time-series images being imaged by an MRI imaging device using a phase contrast method; a shape specifying unit that specifies a shape of the region to be analyzed by analyzing second three-dimensional time-series images showing the anatomy of the subject, the second three-dimensional time-series images being imaged by a method different from the imaging using the phase contrast method; an image generating unit that generates a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; an index generating unit that generates an index related to the blood flow through the shape based on the blood flow velocity distribution in the fusion image and the shape; and an output unit that outputs the shape and the index in association with each other.

[0008] In other words, an information processing device according to a first aspect of the present invention is as follows: That is, the information processing device includes: a blood flow distribution specifying unit that analyzes first three-dimensional time-series images including an analysis target region of a subject imaged by an MRI imaging device using a phase contrast method to specify a blood flow velocity distribution in the analysis target region, a shape specifying unit that analyzes second three-dimensional time-series images that are images captured by a method different from the imaging using the phase contrast method and show the anatomy of the subject to specify a shape of the analysis target region, an image generating unit that generates a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images, an index generating unit that generates an index related to blood flow flowing inside the shape based on the blood flow velocity distribution in the fusion image and the shape, and an output unit that outputs the shape and the index in association with each other.

[0009] The analysis target area may be the heart and great cardiac vessels, and the shape identification unit may include: a region division unit that divides a reference image, which is one time-series image among a plurality of time-series images that constitute the second three-dimensional time-series image, into a plurality of regions including the region of the heart; a feature point extraction unit that extracts one or more feature points in the reference image; a tracking unit that tracks transitions of the feature points in the second three-dimensional time-series image starting from the feature points; and a region modification unit that changes the shapes of the plurality of regions over time based on the tracking results of the feature points.

[0010] In the information processing device of the first aspect of the present invention described above, the analysis target area may be the heart and cardiac great vessels, and the shape identification unit may include: a region division unit that divides a reference image, which is one time-series image among a plurality of time-series images that constitute the second three-dimensional time-series image, into a plurality of regions including the region of the heart; a feature point extraction unit that extracts one or more feature points in the reference image; a tracking unit that tracks the transition of the feature points in the second three-dimensional time-series image starting from the feature points; and a region change unit that changes the shapes of the plurality of regions in a time-series manner based on the tracking results of the feature points.

[0011] The index generating unit may generate an index related to blood flow flowing inside the region of the heart identified by the shape identifying unit.

[0012] In the information processing device according to the first aspect of the present invention, the index generating unit may generate an index relating to blood flow within the region of the heart identified by the shape identifying unit.

[0013] The shape identification unit may further include a grid point management unit that generates a grid in the reference image and deforms the grid based on the tracking results of the feature points, and the image generation unit may generate an anatomical image in which the deformed grid is superimposed on at least the second three-dimensional time-series image.

[0014] In the information processing device of the first aspect of the present invention described above, the shape identification unit may further include a grid point management unit that generates a grid in the reference image and deforms the grid based on the tracking results of the feature points, and the image generation unit may generate an anatomical image in which the deformed grid is superimposed on at least the second three-dimensional time-series image.

[0015] The information processing device may further include an image acquisition unit that acquires a set of images in which the difference between the image capture times of the first three-dimensional time-series image and the second three-dimensional time-series image is within a predetermined time.

[0016] In the information processing device that is the first aspect of the present invention described above, the information processing device may further include an image acquisition unit that acquires a set of images in which the difference between the imaging time of the first three-dimensional time series image and the imaging time of the second three-dimensional time series image is within a predetermined time.

[0017] The image acquisition unit may acquire the second three-dimensional time-series images without contrast, which are captured without using a contrast agent.

[0018] In the information processing device that is the first aspect of the present invention described above, the image acquisition unit may further acquire the second three-dimensional time-series images that are non-contrast and are captured without using a contrast agent.

[0019] A second aspect of the present invention is an information processing system. This information processing system may include: a blood flow distribution identification unit that analyzes first three-dimensional time-series images including a region to be analyzed of a subject, the first three-dimensional time-series images being imaged using a phase contrast method by an MRI (Magnetic Resonance Imaging) device, to identify a blood flow velocity distribution in the region to be analyzed; a shape identification unit that analyzes second three-dimensional time-series images showing the anatomy of the subject, the second three-dimensional time-series images being imaged using a method other than the phase contrast method, to identify a shape of the region to be analyzed; an image generation unit that generates a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; an index generation unit that generates an index related to the blood flow through the shape based on the blood flow velocity distribution and the shape in the fusion image; and an output unit that outputs the shape and the index in association with each other. Note that the information processing system described here is different from the information processing system S described later in the detailed description of the invention.

[0020] The information processing system according to a second aspect of the present invention can be described as follows: That is, the information processing system includes: a blood flow distribution identifying means for analyzing first three-dimensional time-series images including a region to be analyzed of a subject, the first three-dimensional time-series images including the region to be analyzed and imaged by a magnetic resonance imaging (MRI) device using a phase contrast method, and identifying a blood flow velocity distribution in the region to be analyzed; a shape identifying means for analyzing second three-dimensional time-series images showing the anatomy of the subject, the images being imaged by a method different from the phase contrast method, and identifying a shape of the region to be analyzed; an image generating means for generating a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; an index generating means for generating an index related to the blood flow through the shape based on the blood flow velocity distribution and the shape in the fusion image; and an output means for outputting the shape and the index in association with each other. Note that the information processing system described here is different from the information processing system S described later in the detailed description of the invention.

[0021] A third aspect of the present invention is an information processing method, in which a processor executes the steps of: analyzing first three-dimensional time-series images including a region to be analyzed of a subject imaged using a phase contrast method by an MRI imaging device, and identifying a blood flow velocity distribution in the region to be analyzed; analyzing second three-dimensional time-series images showing the anatomy of the subject, which are images imaged using a method different from the phase contrast method, and identifying a shape of the region to be analyzed; generating a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; generating an index related to blood flow through the shape based on the blood flow velocity distribution and the shape in the fusion image; and outputting the shape and the index in association with each other.

[0022] The information processing method according to the third aspect of the present invention can be restated as follows: That is, a computer-executed method including the steps of: analyzing first three-dimensional time-series images including a region to be analyzed of a subject imaged using a phase contrast method by an MRI imaging device, and identifying a blood flow velocity distribution in the region to be analyzed; analyzing second three-dimensional time-series images showing the anatomy of the subject, which are images imaged using a method different from the imaging using the phase contrast method, and identifying a shape of the region to be analyzed; generating a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; generating an index related to blood flow flowing inside the shape based on the blood flow velocity distribution and the shape in the fusion image; and outputting the shape and the index in association with each other.

[0023] The information processing method according to the third aspect of the present invention can be further restated as follows: That is, a computer-implemented method including the steps of: analyzing, using a processor, first three-dimensional time-series images including a region to be analyzed of a subject imaged using a phase contrast method by an MRI imaging device, and identifying a blood flow velocity distribution in the region to be analyzed; analyzing second three-dimensional time-series images showing the anatomy of the subject, which are images imaged using a method different from the phase contrast method, and identifying a shape of the region to be analyzed; generating a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; generating an index related to blood flow within the shape based on the blood flow velocity distribution and the shape in the fusion image; and outputting the shape and the index in association with each other.

[0024] A fourth aspect of the present invention is a computer-readable recording medium having recorded thereon a program that causes a computer to perform the following functions: analyze first three-dimensional time-series images including a region to be analyzed of a subject imaged by an MRI imaging device using a phase contrast method to identify a blood flow velocity distribution in the region to be analyzed; analyze second three-dimensional time-series images that are images of the subject's anatomy and are imaged by a method different from the phase contrast method to identify a shape of the region to be analyzed; generate a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; generate an index related to blood flow through the shape based on the blood flow velocity distribution and the shape in the fusion image; and output the shape and the index in association with each other.

[0025] The fourth aspect of the present invention can be described as follows: A computer-readable recording medium having recorded thereon a program that, when executed by a computer, causes the computer to perform the following steps: analyzing first three-dimensional time-series images including a region to be analyzed of a subject imaged using a phase contrast method by an MRI imaging device, and identifying a blood flow velocity distribution in the region to be analyzed; analyzing second three-dimensional time-series images, which are images captured using a method different from the phase contrast method and show the anatomy of the subject, and identifying a shape of the region to be analyzed; generating a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; generating an index related to blood flow within the shape based on the blood flow velocity distribution and the shape in the fusion image; and outputting the shape and the index in association with each other.

[0026] The recording medium according to a fourth aspect of the present invention can be further described as follows: That is, a non-transitory computer-readable storage medium storing a program for causing a computer to execute the following processes, including the steps of: analyzing first three-dimensional time-series images including a region to be analyzed of a subject imaged by an MRI imaging device using a phase contrast method to identify a blood flow velocity distribution in the region to be analyzed; analyzing second three-dimensional time-series images showing the anatomy of the subject, which are images imaged by a method different from the imaging using the phase contrast method, to identify a shape of the region to be analyzed; generating a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; generating an index related to blood flow through the shape based on the blood flow velocity distribution and the shape in the fusion image; and outputting the shape and the index in association with each other.

[0027] A fifth aspect of the present invention is a program that causes a computer to perform the following functions: analyzing first three-dimensional time-series images including a region to be analyzed of a subject imaged by an MRI imaging device using a phase contrast method to identify a blood flow velocity distribution in the region to be analyzed; analyzing second three-dimensional time-series images that are images of the subject's anatomy and are imaged by a method different from the phase contrast method to identify a shape of the region to be analyzed; generating a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; generating an index related to blood flow through the shape based on the blood flow velocity distribution and the shape in the fusion image; and outputting the shape and the index in association with each other.

[0028] The program according to the fifth aspect of the present invention can be rephrased as follows: That is, a computer-executable program product that, when executed by a computer, causes the computer to perform the following steps: analyzing first three-dimensional time-series images including a region to be analyzed of a subject imaged by an MRI imaging device using a phase contrast method to identify a blood flow velocity distribution in the region to be analyzed, analyzing second three-dimensional time-series images that are images captured by a method different from the phase contrast method and show the anatomy of the subject to identify a shape of the region to be analyzed, generating a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images, and generating an index related to the blood flow flowing inside the shape based on the blood flow velocity distribution and the shape in the fusion image, and outputting the shape and the index in association with each other.

[0029] In order to provide this program or to update a part of the program, a computer-readable recording medium on which this program is recorded may be provided, or this program may be transmitted over a communication line.

[0030] Any combination of the above components, and any transformation of the present invention into a method, device, system, computer program, data structure, recording medium, etc., are also valid aspects of the present invention.

[0031] The information processing device and information processing system according to the present disclosure may also be considered as a diagnostic support device and system, respectively, based on the presentation of blood flow-related indices. Similarly, the information processing method and program according to the present disclosure may also be considered as a diagnostic support method and program, respectively, based on the presentation of blood flow-related indices.

[0032] According to the present invention, the burden on the subject during blood flow measurement can be reduced.

[0033] FIG. 1 is a diagram for explaining an overview of an information processing system according to an embodiment. FIG. 2 is a diagram for explaining an example of the overall configuration of an information processing device according to an embodiment. FIG. 3 is a diagram for schematically showing an example of the functional configuration of an information processing device according to an embodiment. FIG. 4 is a diagram for explaining an example of the functional configuration of a shape specification unit according to an embodiment. FIG. 5 is a diagram for explaining feature point tracking by a shape specification unit according to an embodiment. FIG. 6 is a diagram for explaining lattice deformation performed by a shape specification unit according to an embodiment. FIG. 7 is a flowchart for explaining the flow of information processing performed by an information processing device according to an embodiment.

[0034] <Outline of the embodiment> Fig. 1 is a diagram for explaining an outline of an information processing system S according to an embodiment. Below, an outline of the embodiment will be described with reference to Fig. 1 .

[0035] An information processing system S according to an embodiment may include an information processing device 1 and an MRI imaging device 2. In the information processing system S according to an embodiment, a medical professional such as a doctor or a radiologist may be able to capture two different image sets with a subject P as a subject p in a single imaging sequence. One of the two different image sets may be an image set that reflects the blood flow velocity distribution of blood flowing through an analysis target region of the subject P, and the other may be an image set that shows the anatomy of the subject P. The information processing device 1 may be intended to output an index related to the blood flow flowing inside the body of the subject P by analyzing the two different image sets captured by the MRI imaging device 2.

[0036] In the example shown in FIG. 1 , a medical professional may use an MRI imaging device 2 to generate three-dimensional time-series images of 4D Flow MRI with a subject P as the subject p and three-dimensional time-series images called SSFP (Steady State Free Processing, or true FIESTA) in a single imaging sequence.

[0037] Since this is a known technology, detailed description will be omitted. 4D Flow MRI, also known as 3D cine phase contrast imaging, is an MRI imaging method that non-invasively images blood flow within the body of a subject P. The phase contrast imaging method utilizes the fact that the spin precession of protons is proportional to the movement speed of water molecules by applying a gradient magnetic field during three-dimensional time-series MRI data acquisition to obtain blood flow velocity distribution in the direction of the gradient magnetic field. By slicing and layering the blood flow velocity distribution in the anterior-posterior, lateral-lateral, and posterior directions and imaging the target area of ​​analysis, such as the heart, in three dimensions, it is possible to visualize three-dimensional blood flow within the target area of ​​analysis. This can be captured as a pulsating image during the cardiac cycle, which is why it is called 4D Flow MRI. Therefore, the three-dimensional time-series images of 4D Flow MRI are a set of images that reflect the blood flow velocity distribution.

[0038] Furthermore, SSFP is an image set showing the anatomy of subject P. SSFP is often used for measuring cardiac function in conventional cardiac MRI. Note that, as the image set showing the anatomy of subject P, in addition to SSFP, an image set captured using an imaging method such as the fast gradient echo method, the gradient echo method, or the black blood method can also be used. Any of these image sets can be captured by the MRI imaging device 2, and can be captured together with three-dimensional time-series images of 4D flow MRI in a single imaging sequence.

[0039] Below, an overview of the processing flow from imaging the subject P to outputting indices related to blood flow in the information processing system S according to the embodiment will be explained in the order of (1) to (6), where the numbers correspond to (1) to (6) in Figure 1.

[0040] (1) A medical professional may image the subject P using a phase contrast method to generate a first three-dimensional time series image that reflects the blood flow velocity distribution of blood flowing through the area of ​​the subject P that is to be analyzed. (2) A medical professional may image the subject P using a technique different from the phase contrast method in the same imaging sequence as the first three-dimensional time series image to generate a second three-dimensional time series image that shows the anatomy of the subject P.

[0041] (3) The information processing device 1 may analyze the first three-dimensional time-series images generated by the MRI imaging device 2 to identify the blood flow velocity distribution of the analysis target region. In the schematic diagram shown in Fig. 1, regions indicated by different hatching patterns, such as a grid, diagonal lines, horizontal lines, or vertical lines, may indicate regions with different blood flow velocities. Because the first three-dimensional time-series images indicate the blood flow velocity distribution, the structure of the analysis target region may not necessarily be clearly imaged.

[0042] (4) The information processing device 1 may analyze the second three-dimensional time-series images generated by the MRI imaging device 2 to identify the shape of the region to be analyzed. As schematically shown in FIG. 1 , the second three-dimensional time-series images are images showing the anatomy of the region to be analyzed, and may include images of tissue boundaries, etc. However, information regarding the blood flow velocity distribution in the tissue may not be included.

[0043] (5) The information processing device 1 may generate a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image, thereby enabling the information processing device 1 to visualize the blood flow distribution of blood flowing within the analysis target region.

[0044] (6) The information processing device 1 may generate an index related to the blood flow within the shape based on the blood flow velocity distribution within the area to be analyzed in the fusion image and the shape of the area to be analyzed (see, for example, Itatani K, Sekine T, Yamagishi M, Maeda Y, Higashitani N, Miyazaki S, Matsuda J, Takehara Y. Hemodynamic Parameters for Cardiovascular System in 4D Flow MRI: Mathematical Definition and Clinical Applications. Magn Reson Med Sci. 2022; 21(2):380-399.). Examples of "blood flow indexes" include ventricular volume, ejection fraction, wall motion abnormalities, cardiac output, presence or absence of accelerated blood flow, quantification of regurgitant volume at cardiac valves, quantification of intracardiac shunt rate, quantification of local blood flow, flow through valves such as the aortic valve, mitral valve, pulmonary valve, and tricuspid valve, shear stress on the vascular wall (WSS), index values ​​for time variation of WSS, aortic flow rate and energy loss, deformation of blood vessels and the heart (changes in longitudinal expansion and contraction, aortic arch curvature, torsion, etc., changes in ventricular volume, ejection fraction), etc.

[0045] In this way, the information processing system S according to the embodiment may track the movement of the analysis target region without using a contrast agent by combining an image set such as SSFP, which is an image showing the anatomy of the subject P, with a 4D Flow MRI image set showing the blood flow velocity distribution. Furthermore, the information processing system S may be able to shorten the time required for imaging because it captures two different image sets in a single imaging sequence. As a result, the information processing system S may be able to reduce the burden on the subject P during blood flow measurement.

[0046] <Functional Configuration of Information Processing Device 1 According to the Embodiment> FIG. 2 is a diagram illustrating an example of the overall configuration of the information processing device 1. As illustrated in this diagram, the overall configuration of the information processing device 1 may include a CPU 20 capable of performing arithmetic processing, a ROM 21 capable of storing a BIOS, etc., a RAM 22 which may serve as a working area, and a storage 23 capable of storing programs, etc. The overall configuration of the information processing device 1 may further include an input unit 25, an output unit 26, and a storage medium 27 via an input / output interface 24. The input unit 25 may include an input device such as a keyboard. The output unit 26 may include an output device such as a display. Data transmission and reception between the MRI imaging device 2 and the information processing device 1 may be performed via the input unit 25 and the output unit 26. The functional configuration of the information processing device 1 illustrated in FIG. 3 may be included in the overall configuration illustrated in FIG. 2. In the configuration of FIG. 3, storage devices such as the ROM 21, RAM 22, and storage 23 may be integrated into the storage unit 10.

[0047] FIG. 3 is a diagram schematically illustrating an example of the functional configuration of an information processing device 1 according to an embodiment. The information processing device 1 may be, for example, a medical workstation and may include a storage unit 10 and a control unit 11. In FIG. 3, arrows indicate main data flows, and data flows not shown in FIG. 3 may also exist. In FIG. 3, each functional block may represent a functional unit configuration rather than a hardware (device) unit configuration. Therefore, the functional blocks shown in FIG. 3 may be implemented in a single device, or may be implemented separately in multiple devices. Data may be exchanged between functional blocks via any means, such as a data bus, a network, or a portable storage medium.

[0048] The storage unit 10 may be a large-capacity storage device such as a ROM (Read Only Memory) that stores the BIOS (Basic Input Output System) of the computer that realizes the information processing device 1, a RAM (Random Access Memory) that serves as the working area of ​​the information processing device 1, an OS (Operating System), an application program, or an HDD (Hard Disk Drive) or SSD (Solid State Drive) that stores various information referenced when the application program is executed.

[0049] The control unit 11 may be a processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) of the information processing device 1, and may function as an image acquisition unit 110, a blood flow distribution identification unit 111, a shape identification unit 112, an image generation unit 113, an index generation unit 114, and an output unit 115 by executing a program stored in the memory unit 10.

[0050] 3 shows an example in which the information processing device 1 is configured as a single device. However, the information processing device 1 may be realized by multiple processors, memories, and other computing resources, such as a cloud computing system. In this case, each unit constituting the control unit 11 may be realized by at least one of multiple different processors executing a program.

[0051] The image acquisition unit 110 may acquire first three-dimensional time-series images including an analysis target region of the subject p imaged using the phase contrast method by the MRI imaging device 2. The image acquisition unit 110 may also acquire second three-dimensional time-series images showing the anatomy of the subject p. Here, the second three-dimensional time-series images may be image data acquired using a method (e.g., SSFP) different from imaging using the phase contrast method.

[0052] The blood flow distribution identification unit 111 may identify the blood flow velocity distribution of the analysis target region by analyzing the first three-dimensional time-series images using a known blood flow visualization technique. Furthermore, the blood flow distribution identification unit 111 may identify the blood flow velocity distribution of the analysis target region by analyzing the first three-dimensional time-series images including the analysis target region of the subject that have been imaged using a phase contrast method with an MRI (Magnetic Resonance Imaging) imaging device. The shape identification unit 112 may identify the shape of the analysis target region by analyzing the second three-dimensional time-series images. Furthermore, the shape identification unit 112 may identify the shape of the analysis target region by analyzing the second three-dimensional time-series images that show the anatomy of the subject and that have been imaged using a method other than imaging using the phase contrast method.

[0053] The image generator 113 may generate a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image using a known medical image synthesis technique. That is, the image generator 113 may generate a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image. This allows the image generator 113 to visualize the relationship between the shape of the analysis target region and the blood flow velocity distribution.

[0054] The index generating unit 114 may generate an index related to the blood flow flowing inside the shape based on the blood flow velocity distribution and the shape in the fusion image. The index generating unit 114 may generate an index related to the blood flow flowing inside the region of the heart identified by the shape identifying unit 112. More specifically, the index generating unit 114 may generate an index related to the blood flow flowing inside the region of the heart identified by the shape identifying unit 112. Based on the relationship between the internal structure of the heart and the velocity of blood flowing through the heart, the index generating unit 114 may be able to accurately calculate the above-mentioned ventricular volume, ejection fraction, wall motion abnormality, cardiac output, presence or absence of accelerated blood flow, quantitative determination of regurgitant flow at cardiac valves, quantitative determination of intracardiac shunt rate, quantitative determination of local blood flow, flow through valves such as the aortic valve, mitral valve, pulmonary valve, and tricuspid valve, shear stress on the vascular wall (WSS), an index value of time variation of WSS, aortic flow rate and energy loss, deformation of the blood vessels and the heart (changes in longitudinal expansion and contraction, aortic arch curvature, torsion, etc., change in ventricular volume, ejection fraction), etc. The output unit 115 may associate the shape with the index and output it to a display unit (not shown) of the information processing device 1 or a terminal (not shown) capable of communicating with the information processing device 1.

[0055] An information processing device (hereinafter referred to as "information processing device no. 1") comprising: a blood flow distribution identification unit that analyzes first three-dimensional time-series images including an area to be analyzed of a subject imaged using a phase contrast method by an MRI imaging device, and identifies the blood flow velocity distribution of the area to be analyzed; a shape identification unit that analyzes second three-dimensional time-series images that are images captured using a method different from imaging using the phase contrast method and show the anatomy of the subject, and identifies the shape of the area to be analyzed; an image generation unit that generates a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image; an index generation unit that generates an index related to the blood flow flowing inside the shape based on the blood flow velocity distribution in the fusion image and the shape; and an output unit that outputs the shape and the index in association with each other, can reduce the burden on a subject when measuring blood flow.

[0056] That is, as described above, the blood flow distribution determination unit may be configured to analyze the first three-dimensional time-series images to determine the blood flow velocity distribution for the analysis target region of the subject, and the shape determination unit may be configured to analyze the second three-dimensional time-series images to determine the shape of the analysis target region. Furthermore, the image generation unit may be configured to generate a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images. Furthermore, the index generation unit may generate an index related to the blood flow flowing within the shape, and the output unit may be capable of outputting the shape and the index in association with each other. Therefore, in order to obtain an output in which the shape and the index are associated with each other, it is sufficient to acquire the first three-dimensional time-series images and the second three-dimensional time-series images, thereby reducing the burden on the subject.

[0057] <Functional Configuration of Shape Identification Unit 112> FIG. 4, which explains this configuration, is a diagram schematically illustrating an example of the functional configuration of the shape identification unit 112 according to the embodiment. The shape identification unit 112 according to the embodiment may include a region division unit 1120, a feature point extraction unit 1121, a tracking unit 1122, a region modification unit 1123, and a lattice point management unit 1124. The functional configuration of the shape identification unit 112 will be described below, assuming that the analysis target region to be analyzed by the information processing device 1 according to the embodiment is the heart and cardiac great blood vessels of the subject P. However, it will be understood by those skilled in the art that the analysis target region is not limited to the heart and cardiac great blood vessels, and may be any other region as long as it is an organ through which blood flows.

[0058] It is known that cardiac beat tracking is effective in improving the accuracy of 4D Flow MRI when applied to diagnostic support for cardiovascular diseases such as those of the heart. Conventionally, in order to more accurately track the beat of the heart and the cardiac great vessels, a blood pool contrast agent or the like is administered to the subject P to perform imaging and increase contrast. However, from the viewpoint of reducing the burden on the subject P who may have impaired cardiac function, there is a demand for the use of contrast agents and for shortening the imaging time.

[0059] Therefore, the shape identification unit 112 according to the embodiment may be capable of performing pulsation tracking using, for example, a tracking method based on the known Lucas-Kanade method, with an image set showing anatomy such as SSFP, rather than 4D Flow MRI, as the analysis target. First, the region division unit 1120 may divide a reference image, which is one time-series image among a plurality of time-series images constituting the second three-dimensional time-series image, into a plurality of regions including the region of the heart.

[0060] The feature point extraction unit 1121 may extract one or more feature points in the reference image. The feature points extracted by the feature point extraction unit 1121 may be, for example, edges of regions of the heart or the cardiac great vessels. The tracking unit 1122 may track transitions of feature points in the second three-dimensional time-series image, starting from the feature point extracted by the feature point extraction unit 1121. This allows the tracking unit 1122 to track pulsation, which is the temporal movement of the region to be analyzed. The region change unit 1123 may change the shapes of multiple regions in a time series based on the tracking results of the feature points, and may further display the results on a display unit.

[0061] In the above-mentioned information processing device No. 1, the analysis target area is the heart and cardiac great vessels, and the shape identification unit 112 includes an area division unit 1120 that divides a reference image, which is one of the multiple time-series images that make up the second three-dimensional time-series image, into multiple areas including the heart area; a feature point extraction unit 1121 that extracts one or more feature points in the reference image; a tracking unit 1122 that tracks the transition of the feature points in the second three-dimensional time-series image starting from the feature points; an area change unit 1123 that changes the shapes of the multiple areas in time series based on the tracking results of the feature points; and an area change unit 1124 that changes the shapes of the above-mentioned multiple areas in time series based on the tracking results of the feature points.This information processing device may be capable of grasping the temporal fluctuations of the analysis target area in blood flow measurement.

[0062] 5( a) to 5(d) described later, the operation is as follows: That is, the region dividing unit 1120 divides a reference image, which is one of the time-series images constituting the second three-dimensional time-series image, into a plurality of regions including a cardiac region, the feature point extracting unit 1121 extracts one or more feature points in the reference image, the tracking unit 1122 tracks transitions of the feature points in the second three-dimensional time-series image starting from the feature points, the region changing unit 1123 changes the shapes of the plurality of regions in time series based on the tracking results of the feature points, and the region changing unit 1124 changes the shapes of the plurality of regions in time series based on the tracking results of the feature points, and after processing by the image generating unit 113 and the index generating unit 114, the output unit 115 may output the shapes and the indices in association with each other.

[0063] Furthermore, the index generating unit 114 may be configured to generate an index related to the blood flow inside the region of the heart identified by the shape identifying unit 112, thereby generating an index particularly related to the blood flow inside the heart, and the output unit may output the aforementioned shape and the aforementioned index in association with each other.

[0064] 5(a) to 5(d) are diagrams for explaining feature point tracking by the shape identification unit 112 according to the embodiment. In FIGS. 5(a) to 5(d), black circles marked with the symbol 1 indicate lattice points of a square lattice set in the reference image. To avoid complexity, not all lattice points are marked with symbols, but black circles similar to the black circles marked with the symbol 1 in FIGS. 5(a) to 5(d) indicate lattice points. The lattice formed from the lattice points shown in FIG. 5(a) is a lattice generated in the reference image by the lattice point management unit 1124 of the shape identification unit 112.

[0065] As shown in Figure 5(a), the lattice forms a quadrangular region with four lattice points 1 as vertices. In Figures 5(a) to 5(d), the crosses marked with the symbol c indicate the centers of gravity of the quadrangular regions with four lattice points 1 as vertices. As with the lattice point 1, not all centers of gravity are marked with a symbol to avoid complexity, but in Figures 5(a) to 5(d), crosses similar to the crosses marked with the symbol c indicate the centers of gravity of the quadrangular regions.

[0066] 5(a) to 5(d), the open circles marked with the symbol f indicate feature points extracted by the feature point extraction unit 1121. To avoid complication, not all feature points are marked with symbols, but the open circles similar to the open circles marked with the symbol f in FIGS.

[0067] 5A, the arrow starting from feature point f is the movement vector of feature point f, and shows the tracking result of feature point f by the tracking unit 1122. Fig. 5A shows the position to which feature point f in the reference image has moved in the image adjacent to the reference image in time series (i.e., the frame image adjacent to the reference image).

[0068] The area modification unit 1123 may calculate a center-of-gravity movement vector, which is a weighted average of the movement vectors of feature points f included in each rectangular area based on the distance from the center of gravity of that rectangular area. In FIG. 5( b), an arrow starting from the center of gravity c may indicate a center-of-gravity movement vector related to that center of gravity c. To avoid complexity, not all center-of-gravity movement vectors are labeled, but arrows similar to the arrow labeled v in FIG. 5( b) indicate center-of-gravity movement vectors. This may enable the area modification unit 1123 to express temporal fluctuations of each rectangular area as a vector.

[0069] Fig. 5(c) shows the relationship between lattice point l in the reference image and the center of gravity c of each rectangular region after movement. The region modification unit 1123 may modify the position of lattice point l so that the center of gravity c of the moved rectangular region coincides with the center of gravity c of the rectangular region. Fig. 5(d) shows new lattice point l modified by the region modification unit 1123 based on the movement of the center of gravity c of the rectangular region. In the example shown in Fig. 5(d), the rectangular region having four lattice points l as vertices expands, which corresponds to the expansion due to heartbeat.

[0070] Returning to the explanation of FIG. 4, the grid point management unit 1124 may deform the grid generated on the reference image based on the tracking result of the feature point f by the tracking unit 1122.

[0071] 6(a) to 6(c) are diagrams for explaining the grid deformation performed by the shape identification unit 112 according to the embodiment. Specifically, Fig. 6(a) shows the grid in the reference image, and Fig. 6(b) shows the grid after deformation by the grid point management unit 1124. Fig. 6(c) shows an image in which the deformed grid and an image showing the anatomy of the analysis target region are superimposed.

[0072] As shown in FIG. 6( a), a square grid is set in the reference image. However, the grid point management unit 1124 may deform the grid as shown in FIG. 6( b) after the region modification unit 1123 moves the center of gravity c of the rectangular region based on the movement of the feature point f. FIG. 6( b) can be considered information reflecting the temporal change in the shape of the analysis target region. The image generation unit 113 may generate an anatomical image by superimposing a grid on at least an image showing the anatomy of the analysis target region (i.e., the second three-dimensional time-series image). That is, the image generation unit 113 may generate an anatomical image by superimposing the deformed grid on at least the second three-dimensional time-series image. This allows medical professionals to grasp the temporal change of the analysis target region at a glance in the second three-dimensional time-series image, which is an image set showing the anatomy of subject P.

[0073] <Imaging Sequence> In the information processing system S according to the embodiment, the first three-dimensional time series images and the second three-dimensional time series images may both be generated by the MRI imaging device 2 imaging the subject P. Therefore, medical personnel do not need to change imaging equipment to capture the first three-dimensional time series images and the second three-dimensional time series images of the subject P. The first three-dimensional time series images and the second three-dimensional time series images can be captured consecutively in order, and from the perspective of the subject P, the subject P may simply lie on a bed provided by the MRI imaging device 2 to complete the imaging of the first three-dimensional time series images and the second three-dimensional time series images. Note that when the first three-dimensional time series images and the second three-dimensional time series images are captured consecutively, either one may be captured first.

[0074] Although it depends on the size of the area to be analyzed (and further, the number of captured images), when the first three-dimensional time series image and the second three-dimensional time series image are captured in sequence, the difference between the capture time of the first three-dimensional time series image and the capture time of the second three-dimensional time series image may be within a predetermined time (e.g., within 10 minutes, within 5 minutes, within 3 minutes, or within 1 minute). In other words, the image acquisition unit 110 may be capable of determining whether the first three-dimensional time series image and the second three-dimensional time series image were captured using the same imaging sequence by determining whether the difference between the capture time of the first three-dimensional time series image and the capture time of the second three-dimensional time series image is within a predetermined time.

[0075] The image acquisition unit 110 may be capable of acquiring a set of images captured in the same imaging sequence by acquiring a set of images in which the difference between the imaging times of the first three-dimensional time-series images and the second three-dimensional time-series images is within a predetermined time period. This allows the image acquisition unit 110 to ensure that the imaging times of the images showing the anatomy of the analysis target region and the images showing the blood flow distribution within the analysis target region are within a predetermined time period, thereby suppressing discrepancies between the first three-dimensional time-series images and the second three-dimensional time-series images due to changes in the imaged region over time.

[0076] Furthermore, the information processing device 1 may be capable of calculating an index related to blood flow by incorporating anatomical knowledge of the target region, without increasing the contrast of the second three-dimensional time-series images using a contrast agent, etc., by using the first three-dimensional time-series images in combination, which are images showing the anatomy of the region to be analyzed. This allows the image acquisition unit 110 to acquire non-contrast second three-dimensional time-series images captured without using a contrast agent, thereby reducing the burden on the subject P caused by the use of a contrast agent.

[0077] 7 is an example of a flowchart for explaining the flow of information processing performed by the information processing device 1 according to the embodiment. The processing in this flowchart may be started, for example, when the information processing device 1 is started.

[0078] The image acquisition unit 110 can acquire (S2) first three-dimensional time-series images including a region to be analyzed of the subject p imaged using the phase contrast method by the MRI imaging device 2. The image acquisition unit 110 can also acquire (S4) second three-dimensional time-series images showing the anatomy of the subject p.

[0079] The blood flow distribution specifying unit 111 may specify the blood flow velocity distribution of the analysis target region by analyzing the first three-dimensional time-series images using a known blood flow visualization technique (S6). The shape specifying unit 112 may specify the shape of the analysis target region by analyzing the second three-dimensional time-series images (S8).

[0080] The image generator 113 may generate a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image using a known medical image synthesis technique (S10). The index generator 114 may generate an index related to the blood flow flowing inside the shape based on the blood flow velocity distribution and the shape in the fusion image (S12).

[0081] The output unit 115 may be a unit that associates the shape of the analysis target region with the index related to blood flow and outputs the associated data (S14) to the display unit of the information processing device 1 or to a terminal that can communicate with the information processing device 1. In other words, the output unit 115 may be a unit that outputs the shape of the analysis target region with the index related to blood flow and associates the associated data. When the output unit outputs the index, the processing in this flowchart may end.

[0082] The present invention can be implemented as an information processing device, an information processing system that performs the functions described for the information processing device 1 according to the embodiment, an information processing method that performs the functions, a computer-readable recording medium that stores a program that causes a computer to perform the functions, and a program that causes a computer to perform the functions. These embodiments have the same effects as the functions described for the information processing device 1 according to the embodiment.

[0083] An embodiment of the present invention will now be described in further detail, in which the information processing system functions as described above for the information processing device 1 according to the embodiment. This information processing system may be the information processing system previously described as the second aspect of the present invention. That is, this information processing system may include: a blood flow distribution identification unit that analyzes first three-dimensional time-series images including a region to be analyzed of a subject, the first three-dimensional time-series images being imaged using a phase contrast method by an MRI (Magnetic Resonance Imaging) device, to identify a blood flow velocity distribution in the region to be analyzed; a shape identification unit that analyzes second three-dimensional time-series images showing the anatomy of the subject, the second three-dimensional time-series images being imaged using a method different from the phase contrast method, to identify a shape of the region to be analyzed; an image generation unit that generates a fusion image by superimposing the first three-dimensional time-series images and the second three-dimensional time-series images; an index generation unit that generates an index related to the blood flow through the shape based on the blood flow velocity distribution in the fusion image and the shape; and an output unit that outputs the shape and the index in association with each other.

[0084] The information processing system described here may correspond to the information processing device 1 in the information processing system S described above. The blood flow distribution specifying means may correspond to the blood flow distribution specifying unit 111 described above. The shape specifying means may correspond to the shape specifying unit 112 described above. The image generating means may correspond to the image generating unit 113 described above. The index generating means may correspond to the index generating unit 114 described above. The output means may correspond to the output unit 115 described above.

[0085] <Effects of Information Processing Device 1 According to the Embodiment> As described above, the information processing device 1 according to the embodiment can reduce the burden on the subject during blood flow measurement.

[0086] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope of the above embodiments, and various modifications and alterations are possible within the spirit and scope of the present invention. For example, all or part of the device can be configured by functionally or physically distributing or integrating any unit. Furthermore, new embodiments resulting from any combination of multiple embodiments are also included in the embodiments of the present invention. The effects of the new embodiments resulting from the combination will also have the effects of the original embodiments. The contents of all publications, including patents and patent applications referenced in this specification, should be construed as being incorporated by reference as if they were expressly set forth in this specification.

[0087] 1... Information processing device 10... Memory unit 11... Control unit 110... Image acquisition unit 111... Blood flow distribution identification unit 112... Shape identification unit 1120... Area division unit 1121... Feature point extraction unit 1122... Tracking unit 1123... Area change unit 1124... Lattice point management unit 113... Image generation unit 114... Index generation unit 115... Output unit 2... MRI imaging device S... Information processing system

Claims

1. a blood flow distribution specifying unit that specifies a blood flow velocity distribution of an analysis target portion by analyzing a first three-dimensional time-series image including the analysis target portion of a subject imaged by a magnetic resonance imaging (MRI) imaging device using a phase contrast method; a shape identification unit that identifies a shape of the analysis target region by analyzing a second three-dimensional time-series image that is captured by a method other than the imaging using the phase contrast method and shows the anatomy of the subject; and an image generating unit that generates a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image; an index generating unit that generates an index related to a blood flow flowing inside the shape based on the blood flow velocity distribution in the fusion image and the shape; an output unit that outputs the shape and the index in association with each other, The analysis target site is the heart and the cardiac great vessels, The shape specifying unit is a region dividing unit that divides a reference image, which is one of a plurality of time-series images constituting the second three-dimensional time-series image, into a plurality of regions including the region of the heart; a feature point extraction unit that extracts one or more feature points in the reference image; a tracking unit that tracks a transition of the feature point in the second three-dimensional time-series image, starting from the feature point; and a region changing unit that changes shapes of the plurality of regions in a time series manner based on a center-of-gravity movement vector of the plurality of regions calculated based on a tracking result of the feature points. Information processing device.

2. the index generating unit generates an index related to blood flow flowing inside the region of the heart identified by the shape identifying unit. The information processing device according to claim 1 .

3. the shape specifying unit further includes a lattice point management unit that generates a lattice in the reference image and deforms the lattice based on a tracking result of the feature points; The image generating unit generates an anatomical image by superimposing the deformed grid on at least the second three-dimensional time-series image.

3. The information processing device according to claim 1 or 2.

4. The information processing device includes: an image acquisition unit that acquires a set of images in which the difference between an imaging time of the first three-dimensional time-series image and an imaging time of the second three-dimensional time-series image is within a predetermined time; 3. The information processing device according to claim 1 or 2.

5. The information processing device according to claim 4 , wherein the predetermined time is within 10 minutes.

6. The image acquisition unit acquires the second non-contrast three-dimensional time-series images captured without using a contrast agent. The information processing device according to claim 4.

7. The information processing device according to claim 1 , wherein the technique different from the imaging using the phase contrast method is selected from the group consisting of SSFP and a Black blood method.

8. 3. The information processing device of claim 1 or 2, wherein the indicators related to blood flow are selected from the group consisting of ventricular volume, ejection fraction, wall motion abnormalities, cardiac output, presence or absence of accelerated blood flow, quantification of regurgitant volume at cardiac valves, quantification of intracardiac shunt rate, quantification of local blood flow, flow through valves such as the aortic valve, mitral valve, pulmonary valve, tricuspid valve, etc., aortic flow or energy loss, deformation of blood vessels or the heart, longitudinal expansion and contraction of blood vessels or the heart, change in curvature or torsion of the aortic arch, change in ventricular volume, and change in ejection fraction.

9. a blood flow distribution specifying unit that specifies a blood flow velocity distribution of an analysis target portion by analyzing a first three-dimensional time-series image including the analysis target portion of a subject imaged by an MRI imaging device using a phase contrast method; a shape identification unit that identifies a shape of the analysis target region by analyzing a second three-dimensional time-series image that is captured by a method other than the imaging using the phase contrast method and shows the anatomy of the subject; and an image generating unit that generates a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image; an index generating unit that generates an index related to a blood flow flowing inside the shape based on the blood flow velocity distribution in the fusion image and the shape; an output unit that outputs the shape and the index in association with each other, The analysis target site is the heart and the cardiac great vessels, The technique other than imaging using the phase contrast method is selected from the group consisting of SSFP and Black blood method; The index relating to the blood flow is selected from the group consisting of ventricular volume, ejection fraction, wall motion abnormality, cardiac output, presence or absence of accelerated blood flow, quantitative determination of regurgitant volume at a cardiac valve, quantitative determination of intracardiac shunt rate, quantitative determination of local blood flow, flow through valves such as aortic valve, mitral valve, pulmonary valve, tricuspid valve, flow rate or energy loss in the aorta, deformation amount of blood vessel or heart, expansion and contraction in the long axis direction of blood vessel or heart, change in curvature or torsion of the aortic arch, change in ventricular volume, and change in ejection fraction; The shape specifying unit is a region dividing unit that divides a reference image, which is one of a plurality of time-series images constituting the second three-dimensional time-series image, into a plurality of regions including the region of the heart; a feature point extraction unit that extracts one or more feature points in the reference image; a tracking unit that tracks a transition of the feature point in the second three-dimensional time-series image, starting from the feature point; a region changing unit that changes shapes of the plurality of regions in a time series manner based on a center-of-gravity movement vector of the plurality of regions calculated based on a tracking result of the feature points, the index generating unit generates an index related to a blood flow flowing inside the region of the heart identified by the shape identifying unit; the shape specifying unit further includes a lattice point management unit that generates a lattice in the reference image and deforms the lattice based on a tracking result of the feature points; The image generation unit generates an anatomical image by superimposing a deformed grid on at least the second three-dimensional time-series image. The information processing device includes: an image acquisition unit that acquires a set of images in which the difference between an imaging time of the first three-dimensional time-series image and an imaging time of the second three-dimensional time-series image is within 10 minutes; The image acquisition unit acquires the second non-contrast three-dimensional time-series images captured without using a contrast agent. The information processing device according to claim 1 .

10. a blood flow distribution specifying means for specifying a blood flow velocity distribution of an analysis target portion by analyzing a first three-dimensional time-series image including the analysis target portion of a subject imaged by a magnetic resonance imaging (MRI) imaging device using a phase contrast method; a shape identification means for analyzing a second three-dimensional time-series image showing the anatomy of the subject, the second three-dimensional time-series image being captured by a method other than the imaging using the phase contrast method, and identifying a shape of the portion to be analyzed; an image generating means for generating a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image; an index generating means for generating an index related to a blood flow flowing inside the shape based on the blood flow velocity distribution in the fusion image and the shape; and an output means for outputting the shape and the index in association with each other, The analysis target site is the heart and the cardiac great vessels, The shape specifying means is a region dividing means for dividing a reference image, which is one of a plurality of time-series images constituting the second three-dimensional time-series image, into a plurality of regions including the region of the heart; A feature point extracting means for extracting one or more feature points in the reference image; a tracking means for tracking a transition of the feature point in the second three-dimensional time-series image, starting from the feature point; and an area changing means for changing shapes of the plurality of areas in a time series manner based on a center-of-gravity movement vector of the plurality of areas calculated based on a tracking result of the feature points. Information processing system.

11. The processor: analyzing a first three-dimensional time-series image including an analysis target region of a subject imaged by an MRI imaging device using a phase contrast method to identify a blood flow velocity distribution of the analysis target region; analyzing a second three-dimensional time-series image showing the anatomy of the subject, the second three-dimensional time-series image being captured by a method other than the imaging using the phase contrast method, to identify the shape of the region to be analyzed; generating a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image; generating an index related to blood flow flowing inside the shape based on the blood flow velocity distribution in the fusion image and the shape; and outputting the shape and the index in association with each other; The analysis target site is the heart and the cardiac great vessels, The step of identifying the shape includes: Dividing a reference image, which is one of a plurality of time-series images constituting the second three-dimensional time-series image, into a plurality of regions including the region of the heart; extracting one or more feature points in the reference image; tracking a transition of the feature point in the second three-dimensional time-series images starting from the feature point; changing the shapes of the plurality of regions in a time series manner based on a center-of-gravity movement vector of the plurality of regions calculated based on the tracking result of the feature points; Information processing methods.

12. On the computer, a function of analyzing a first three-dimensional time-series image including an analysis target region of a subject imaged by an MRI imaging device using a phase contrast method, and identifying a blood flow velocity distribution of the analysis target region; a function of analyzing a second three-dimensional time-series image showing the anatomy of the subject, the second three-dimensional time-series image being captured by a method other than the imaging using the phase contrast method, to identify the shape of the portion to be analyzed; a function of generating a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image; a function of generating an index related to a blood flow flowing inside the shape based on the blood flow velocity distribution in the fusion image and the shape; and a function of outputting the shape and the index in association with each other, The analysis target site is the heart and the cardiac great vessels, The function of specifying the shape is a function of dividing a reference image, which is one of a plurality of time-series images constituting the second three-dimensional time-series image, into a plurality of regions including the region of the heart; extracting one or more feature points from the reference image; a function of tracking a transition of the feature point in the second three-dimensional time-series image starting from the feature point; and changing the shapes of the plurality of regions in a time series manner based on a center-of-gravity movement vector of the plurality of regions calculated based on the tracking result of the feature points. A computer-readable recording medium on which a program is recorded.

13. On the computer, a function of analyzing a first three-dimensional time-series image including an analysis target region of a subject imaged by an MRI imaging device using a phase contrast method, and identifying a blood flow velocity distribution of the analysis target region; a function of analyzing a second three-dimensional time-series image showing the anatomy of the subject, the second three-dimensional time-series image being captured by a method other than the imaging using the phase contrast method, to identify the shape of the portion to be analyzed; a function of generating a fusion image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image; a function of generating an index related to a blood flow flowing inside the shape based on the blood flow velocity distribution in the fusion image and the shape; and a function of outputting the shape and the index in association with each other, The analysis target site is the heart and the cardiac great vessels, The function of specifying the shape is a function of dividing a reference image, which is one of a plurality of time-series images constituting the second three-dimensional time-series image, into a plurality of regions including the region of the heart; extracting one or more feature points from the reference image; a function of tracking a transition of the feature point in the second three-dimensional time-series image starting from the feature point; and changing the shapes of the plurality of regions in a time series manner based on a center-of-gravity movement vector of the plurality of regions calculated based on the tracking result of the feature points. program.