WO2023203722A1 - 情報処理装置、情報処理方法、及び記録媒体 - Google Patents
情報処理装置、情報処理方法、及び記録媒体 Download PDFInfo
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Definitions
- the present invention relates to an information processing device, an information processing method, and a recording medium, and particularly relates to a technique for generating an index related to blood flow from an MRI (Magnetic Resonance Imaging) image.
- MRI Magnetic Resonance Imaging
- a technique is known that visualizes the distribution of blood flow in a blood vessel as a vector from an image obtained from an ultrasonic diagnostic device, an MRI phase image, etc. (see, for example, Patent Document 1).
- the problem with ultrasound is that there are areas that are difficult to reach, such as the distal ascending aorta and the aortic arch, and imaging in these areas is difficult. Although visualization of these areas is possible with MRI images, contrast agents are used to increase the contrast of the images for more accurate measurements. However, since the use of contrast media places a burden on the subject, it is desired to reduce the burden on the subject.
- the present invention has been made in view of these points, and it is an object of the present invention to provide a technique that reduces the burden on a subject in blood flow measurement.
- a first aspect of the present invention is an information processing device. This device analyzes a first three-dimensional time-series image including an analysis target region of a subject imaged using a phase contrast method by an MRI imaging device, and identifies a blood flow velocity distribution in the analysis target region.
- the present invention includes an index generation unit that generates an index related to blood flow flowing inside the shape based on the shape, and an output unit that outputs the shape and the index in association with each other.
- the information processing device that is the first aspect of the present invention is as follows. That is, the information processing device analyzes 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 determine the blood flow velocity distribution of the analysis target region.
- a blood flow distribution identifying unit to identify and analyze a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured by a method different from the imaging using the phase contrast method, to determine the analysis target region.
- An information processing device including: an index generation unit that generates an index related to blood flow flowing inside the shape based on the distribution and the shape; and an output unit that outputs the shape and the index in association with each other.
- the analysis target region may be a heart and a large cardiac blood vessel
- the shape identification unit may select a reference image that is one of a plurality of time-series images constituting the second three-dimensional time-series image.
- a region dividing unit that divides the image into a plurality of regions including the heart region; a feature point extraction unit that extracts one or more feature points in the reference image; and a feature point extraction unit that extracts one or more feature points in the reference image;
- the image forming apparatus may include a tracking unit that tracks transitions of the feature points in time-series images, and a region changing unit that changes the shapes of the plurality of regions in time series based on the tracking results of the feature points.
- the analysis target region may be a heart and a large cardiac blood vessel
- the shape identification unit may be configured to identify a plurality of parts forming the second three-dimensional time-series image.
- a region dividing unit that divides a reference image, which is one of the time-series images of the time-series images, into a plurality of regions including the heart region; and a feature point that extracts one or more feature points in the reference image.
- an extraction unit a tracking unit configured to track transitions of the feature points in the second three-dimensional time-series image using the feature points as a starting point
- an area changing unit that changes the area.
- the index generation unit may generate an index related to blood flow flowing inside the region of the heart identified by the shape identification unit.
- the index generating section may generate an index regarding blood flow flowing inside the region of the heart specified by the shape specifying section.
- the shape specifying unit may further include a lattice point management unit that generates a lattice in the reference image and deforms the lattice based on the tracking result of the feature points, and the image generation unit An anatomical image may be generated by superimposing the deformed lattice on a two-dimensional time-series image.
- the shape specifying unit generates a lattice in the reference image and also includes a lattice point management unit that deforms the lattice based on the tracking result of the feature points.
- the image generation unit may generate an anatomical image in which a deformed grid is superimposed on at least the second three-dimensional time-series image.
- the information processing device further includes 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. You may prepare.
- the information processing device further comprises: a 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; may include an image acquisition unit that acquires a set of images within a predetermined time period.
- the image acquisition unit may acquire the second non-contrast three-dimensional time-series image captured without using a contrast agent.
- the information processing device further includes: the image acquisition unit configured to capture the non-contrast second three-dimensional image captured without using a contrast agent; A series of images may also be acquired.
- the second aspect of the present invention is an information processing system.
- This information processing system analyzes a first three-dimensional time-series image including an analysis target region of a subject imaged using a phase contrast method by an MRI (Magnetic Resonance Imaging) imaging device, and determines the blood flow velocity of the analysis target region.
- blood flow distribution identifying means for identifying the blood flow distribution, and analyzing a second three-dimensional time series image showing the anatomy of the subject, which is an image captured by a method different from the imaging using the phase contrast method, and performing the analysis.
- a shape specifying means for specifying the shape of the target region; an image generating means for generating a fused image in which the first three-dimensional time series image and the second three-dimensional time series image are superimposed; and the blood in the fused image.
- Information processing comprising: an index generation means for generating an index regarding blood flow flowing inside the shape based on the flow velocity distribution and the shape; and an output means for outputting the shape and the index in association with each other. It may be a system. Note that the information processing system described here is different from the information processing system S described later in the detailed description.
- the information processing system that is the second aspect of the present invention is as follows. That is, the information processing system analyzes a first three-dimensional time-series image including the analysis target part of a subject imaged using a phase contrast method by an MRI (Magnetic Resonance Imaging) imaging device, and calculates the analysis target part.
- shape identifying means for identifying the shape of the analysis target region; image generating means for generating a fused image in which the first three-dimensional time-series image and the second three-dimensional time-series image are superimposed; and the fused image.
- an index generation means for generating an index regarding the blood flow flowing inside the shape based on the blood flow velocity distribution and the shape; and an output means for outputting the shape and the index in association with each other.
- the third aspect of the present invention is an information processing method.
- a processor analyzes 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 identifies a blood flow velocity distribution in the analysis target region. and analyzing a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured by a method different from the imaging using the phase contrast method, to identify the shape of the analysis target region.
- a step of generating an index related to blood flow flowing inside the shape, and a step of correlating and outputting the shape and the index are executed.
- the information processing method that is the third aspect of the present invention is as follows. That is, it is a method executed by a computer, which analyzes a first three-dimensional time-series image including an analysis target region of a subject imaged using a phase contrast method by an MRI imaging device, and determines the blood flow in the analysis target region. identifying the velocity distribution, and analyzing a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured using a method different from the imaging method using the phase contrast method, to determine the area to be analyzed. identifying the shape; generating a fused image by superimposing the first three-dimensional time series image and the second three-dimensional time series image; and identifying the blood flow velocity distribution and the shape in the fused image.
- a computer-implemented method comprising the steps of: generating an index regarding blood flow flowing inside the shape based on the shape; and outputting the shape and the index in association with each other.
- the information processing method which is the third aspect of the present invention, can be further stated as follows. That is, the method is implemented in a computer, and the analysis is performed by using a processor to analyze 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. identifying the blood flow velocity distribution of the target region, and analyzing a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured by a method different from the imaging using the phase contrast method. identifying the shape of the analysis target region; generating a fused image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image; and determining the blood flow velocity in the fused image.
- a computer-implemented method comprising the steps of: generating an index regarding blood flow flowing inside the shape based on the distribution and the shape; and outputting the shape and the index in association with each other.
- the fourth aspect of the present invention is a recording medium.
- This recording medium causes a computer to analyze 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 identify the blood flow velocity distribution of the analysis target region. and identifying the shape of the analysis target region by analyzing a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured by a method different from the imaging method using the phase contrast method.
- the present invention is a computer-readable recording medium on which a program is recorded, which realizes a function of generating an index related to blood flow flowing inside the shape, and a function of outputting the shape and the index in association with each other.
- the recording medium which is the fourth aspect of the present invention is as follows. That is, when executed by the computer, the computer performs the following steps: analyzing the first three-dimensional time-series image including the analysis target region of the subject imaged by the MRI imaging device using the phase contrast method; identifying the blood flow velocity distribution of the analysis target region, and analyzing a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured by a method different from the imaging using the phase contrast method. identifying the shape of the analysis target region; generating a fused image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image; and determining the shape of the blood flow in the fused image.
- a computer storing a program that executes the steps of: generating an index regarding blood flow flowing inside the shape based on the velocity distribution and the shape; and outputting the shape in association with the index.
- the recording medium which is the fourth aspect of the present invention can be further stated as follows. That is, the computer performs processing including the following: Analyzing a first three-dimensional time-series image including the analysis target region of the subject imaged by an MRI imaging device using the phase contrast method, and determining the blood flow velocity of the analysis target region. identifying the distribution, and analyzing a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured by a method different from the imaging method using the phase contrast method, to determine the shape of the analysis target region. identifying the first three-dimensional time-series image and the second three-dimensional time-series image to generate a fused image; and determining the blood flow velocity distribution and the shape in the fused image.
- a non-temporary computer storing a program for executing processing including the steps of: generating an index regarding blood flow flowing inside the shape based on the shape; and outputting the shape in association with the index.
- Computer-readable storage medium Computer-readable storage medium.
- the fifth aspect of the present invention is a program.
- This program causes a computer to analyze 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 the blood flow velocity distribution of the analysis target region. and a function of identifying the shape of the analysis target region by analyzing a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured by a method different from the imaging method using the phase contrast method.
- a function of generating an index regarding blood flow flowing inside a shape, and a function of correlating and outputting the shape and the index are realized.
- the program that is the fifth aspect of the present invention is as follows. That is, when the program is executed by a computer, the computer performs the following steps: A program product executed by the computer, in which a target region of a subject imaged using a phase contrast method by an MRI imaging device is analyzed. analyzing a first three-dimensional time-series image containing a first three-dimensional time-series image to identify the blood flow velocity distribution of the analysis target region; analyzing a second three-dimensional time-series image showing the anatomy of the body to identify the shape of the analysis target region; and fusion of the first three-dimensional time-series image and the second three-dimensional time-series image by superimposing them.
- a program product executed on a computer that outputs steps and causes execution.
- a computer-readable recording medium recording this program may be provided, and this program may be transmitted over a communication line.
- the information processing device and information processing system according to the present disclosure can also be regarded as a diagnosis support device and a diagnosis support system, or a diagnosis support device and a diagnosis support system, respectively, based on the presentation of indicators related to blood flow.
- the information processing method and program according to the present disclosure can also be regarded as a diagnosis support method and a diagnosis support program, or a diagnosis support method and a diagnosis support program, respectively, based on presentation of indicators related to blood flow.
- the burden on the subject during blood flow measurement can be reduced.
- FIG. 1 is a diagram for explaining an overview of an information processing system according to an embodiment.
- FIG. 1 is a diagram for explaining an example of the overall configuration of an information processing device according to an embodiment.
- FIG. 1 is a diagram schematically showing an example of a functional configuration of an information processing device according to an embodiment.
- FIG. 2 is a diagram schematically showing an example of a functional configuration of a shape identifying section according to an embodiment.
- FIG. 3 is a diagram for explaining feature point tracking by the shape specifying unit according to the embodiment.
- FIG. 1 is a diagram for explaining an overview of an information processing system S according to an embodiment. An overview of the embodiment will be described below with reference to FIG.
- the information processing system S may include an information processing device 1 and an MRI imaging device 2.
- a medical worker such as a doctor or a radiologic technologist may be able to capture two different image sets in which the subject P is the subject p in one imaging sequence.
- One of the two different image sets may be an image set reflecting the blood flow velocity distribution of blood flowing through the analysis target site of the subject P, and the other may be an image set showing the anatomy of the subject P.
- the information processing device 1 may have the purpose of outputting an index related to blood flow in the body of the subject P by analyzing two different image sets captured by the MRI imaging device 2.
- a medical worker uses an MRI imaging device 2 to obtain a 4D Flow MRI three-dimensional time-series image of a subject P as a subject p, and an SSFP (Steady State Free Procession, or true FIESTA) image. It is sufficient to generate a so-called three-dimensional time-series image in one imaging sequence.
- MRI imaging device 2 to obtain a 4D Flow MRI three-dimensional time-series image of a subject P as a subject p, and an SSFP (Steady State Free Procession, or true FIESTA) image. It is sufficient to generate a so-called three-dimensional time-series image in one imaging sequence.
- SSFP Steady State Free Procession, or true FIESTA
- 4D Flow MRI is also called 3D cine phase contrast method, and is an MRI imaging method that non-invasively images the blood flow inside the body of subject P.
- the phase contrast method uses the fact that the spin precession of protons is proportional to the moving speed of water molecules by applying a gradient magnetic field during three-dimensional time-series data imaging with MRI, and obtains the blood flow velocity distribution in the direction of the gradient magnetic field.
- the imaging method by layering slices of the blood flow velocity distribution in the front-back, left-right, and up-down directions and three-dimensionally imaging the target area such as the heart, it is possible to obtain three-dimensional blood flow within the target area. It can be visualized.
- This is called 4D Flow MRI because it can be captured as a pulsating image in the cardiac cycle. Therefore, the three-dimensional time-series images of 4D Flow MRI are an image set that reflects the blood flow velocity distribution.
- SSFP is an image set showing the anatomy of subject P.
- SSFP is often used in conventional cardiac MRI to measure cardiac function.
- 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 image set can be imaged by the MRI imaging device 2, and can be imaged together with the three-dimensional time-series images of 4D Flow MRI in one imaging sequence.
- a medical worker can generate a first three-dimensional time-series image that reflects the blood flow velocity distribution of blood flowing through the analysis target region of the subject P by imaging the subject P using a phase contrast method.
- the medical worker obtains a second three-dimensional time-series image showing the anatomy of the subject P by imaging the subject P using a method different from the phase contrast method in the same imaging sequence as the first three-dimensional time-series image. can be generated.
- 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.
- regions indicated by different hatching patterns such as grids, diagonal lines, horizontal lines, vertical lines, etc. may indicate regions where blood flow speeds are different. Since the first three-dimensional time-series image is an image showing the blood flow velocity distribution, the structure of the analysis target site is not necessarily clearly imaged.
- 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.
- the second three-dimensional time-series image is an image showing the anatomy of the analysis target site, and may include tissue boundaries and the like. However, information regarding the blood flow velocity distribution within the tissue may not be included.
- the information processing device 1 may generate a fused image in which the first three-dimensional time-series image and the second three-dimensional time-series image are superimposed. Thereby, the information processing device 1 may be one that can image the blood flow distribution of blood flowing within the analysis target site.
- the information processing device 1 may generate an index regarding the blood flow flowing inside the shape based on the blood flow velocity distribution within the analysis target region in the fused image and the shape of the analysis target region (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 “indicators related to blood flow” include ventricular volume, ejection fraction, abnormal wall motion, cardiac output, presence or absence of accelerated blood flow, quantification of regurgitation flow at heart valves, and quantification of intracardiac shunt rate. , Quantification of local blood flow, flow rate passing through valves such as the aortic valve, mitral valve, pulmonary valve, tricuspid valve, etc., wall shear stress (WSS) on the blood vessel wall, index value of time fluctuation of WSS, aorta These include flow rate and energy loss, deformation of blood vessels and the heart (changes in longitudinal expansion and contraction, curvature of the aortic arch, torsion, etc., changes in ventricular volume, and ejection fraction).
- valves such as the aortic valve, mitral valve, pulmonary valve, tricuspid valve, etc.
- WSS wall shear stress
- the information processing system S uses contrast agent It is sufficient to track the movement of the part to be analyzed without using. Further, since the information processing system S images two different image sets in one imaging sequence, the time related to imaging may be shortened. As a result, the information processing system S may be able to reduce the burden on the subject P in blood flow measurement.
- FIG. 2 is a diagram showing an example of the overall configuration of the information processing device 1.
- the overall configuration of the information processing device 1 includes a CPU 20 that can perform arithmetic processing, etc., a ROM 21 that can store BIOS, etc., a RAM 22 that can be a work area, and a storage 23 that can store programs, etc. Good luck.
- the overall configuration of the information processing device 1 can include an input section 25 , an output section 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 section 25 and the output section 26.
- the functional configuration of the information processing device 1 shown in FIG. 3 may be included in the overall configuration shown in FIG. 2.
- storage devices such as the ROM 21, RAM 22, and storage 23 may be combined in the storage unit 10.
- FIG. 3 is a diagram schematically showing an example of the functional configuration of the information processing device 1 according to the embodiment.
- the information processing device 1 is, for example, a medical workstation, and may include a storage section 10 and a control section 11.
- arrows indicate main data flows, and there may be data flows that are not shown in FIG.
- each functional block may represent a configuration of a functional unit rather than a configuration of a hardware (device) unit. Therefore, the functional blocks shown in FIG. 3 may be implemented within a single device, or may be implemented separately within multiple devices. Data may be exchanged between functional blocks via any means such as a data bus, a network, or a portable storage medium.
- the storage unit 10 includes a ROM (Read Only Memory) that stores the BIOS (Basic Input Output System) of the computer that implements the information processing device 1, a RAM (Random Access Memory) that serves as a work area for the information processing device 1, and an OS (OS).
- the storage device may be a large-capacity storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive) that stores a variety of information that is referenced during execution of the application program (Operating System), application program, and the application program.
- the control unit 11 is a processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) of the information processing device 1, and controls the image acquisition unit 110 and blood flow distribution by executing a program stored in the storage unit 10. It may function as the specifying section 111, the shape specifying section 112, the image generating section 113, the index generating section 114, and the output section 115.
- a processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) of the information processing device 1
- It may function as the specifying section 111, the shape specifying section 112, the image generating section 113, the index generating section 114, and the output section 115.
- FIG. 3 shows an example in which the information processing device 1 is composed of a single device.
- the information processing device 1 may be realized by calculation resources such as a plurality of processors and memories, such as a cloud computing system, for example.
- each unit constituting the control unit 11 may be realized by executing a program by at least one of a plurality of different processors.
- the image acquisition unit 110 may acquire a first three-dimensional time-series image including the analysis target region of the subject p imaged by the MRI imaging device 2 using a phase contrast method. Further, the image acquisition unit 110 may acquire a second three-dimensional time-series image showing the anatomy of the subject p.
- the second three-dimensional time-series image may be image data captured using a method different from imaging using a phase contrast method (for example, SSFP).
- the blood flow distribution identifying unit 111 may identify the blood flow velocity distribution of the analysis target site by analyzing the first three-dimensional time-series image using a known blood flow visualization technique. Furthermore, the blood flow distribution identification unit 111 analyzes a first three-dimensional time series image including the analysis target region of the subject imaged using the phase contrast method by an MRI (Magnetic Resonance Imaging) imaging device, and determines the analysis target region. It may be something that specifies blood flow velocity distribution.
- the shape identifying unit 112 may analyze the second three-dimensional time-series image and identify the shape of the region to be analyzed.
- the shape identifying unit 112 analyzes a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured using a method different from imaging using the phase contrast method, and identifies the shape of the analysis target region. Anything you do is fine.
- the image generation unit 113 may generate a fused image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image by using a known image synthesis technique for medical images. That is, the image generation unit 113 may generate a fused image in which the first three-dimensional time-series image and the second three-dimensional time-series image are superimposed. Thereby, the image generation unit 113 may be capable of visualizing the relationship between the shape of the analysis target site and the blood flow velocity distribution.
- the index generation unit 114 may generate an index regarding the blood flow flowing inside the shape based on the blood flow velocity distribution and the shape in the fused image.
- the index generation unit 114 may generate an index related to blood flow flowing inside the region of the heart identified by the shape identification unit 112. More specifically, the index generation unit 114 may generate an index related to blood flow flowing inside the region of the heart identified by the shape identification unit 112. Based on the relationship between the internal structure of the heart and the velocity of blood flowing through the heart, the index generation unit 114 calculates the above-mentioned ventricular volume, ejection fraction, wall motion abnormality, cardiac output, presence or absence of accelerated blood flow, and heart valves.
- the output unit 115 may output the shape and the index in correspondence to a display unit (not shown) of the information processing device 1 or a terminal (not shown) that can communicate with the information processing device 1.
- a blood flow distribution identifying unit that analyzes a first three-dimensional time-series image including the analysis target region of the subject imaged by the MRI imaging device using the phase contrast method to identify the blood flow velocity distribution of the analysis target region; a shape identifying unit that identifies the shape of the analysis target region by analyzing a second three-dimensional time-series image showing the anatomy of the subject, which is an image captured by a method different from imaging using a contrast method; an image generation unit that generates a fused image in which a three-dimensional time-series image and the second three-dimensional time-series image are superimposed; and a blood flow flowing inside the shape based on the blood flow velocity distribution in the fused image and the shape.
- An information processing device (hereinafter referred to as “information processing device No. 1”) includes an index generation unit that generates an index related to blood flow, and an output unit that outputs the shape and the index in association with each other. The burden on the subject during blood flow measurement can be reduced.
- the blood flow distribution specifying section can analyze the first three-dimensional time series image to specify the blood flow velocity distribution for the analysis target region of the subject, and the shape specifying section can specify the blood flow velocity distribution for the analysis target region of the subject. It may be configured to analyze three-dimensional time-series images and identify the shape of the analysis target site. Further, the image generation unit may be configured to generate a fused image in which the first three-dimensional time-series image and the second three-dimensional time-series image are superimposed. Furthermore, the index generation section may be able to generate an index regarding the blood flow flowing inside the above-described shape, and the output section may be able to output the above-described shape and the above-mentioned index in association with each other.
- FIG. 4 which describes this configuration, is a diagram schematically showing an example of the functional configuration of the shape identifying section 112 according to the embodiment.
- the shape identifying section 112 according to the embodiment may include a region dividing section 1120, a feature point extracting section 1121, a tracking section 1122, a region changing section 1123, and a grid point managing section 1124.
- the functional configuration of the shape identification unit 112 will be described on the premise that the analysis target parts to be analyzed by the information processing apparatus 1 according to the embodiment are the heart and large cardiac vessels of the subject P.
- the analysis target site is not limited to the heart and large cardiac vessels, but may be any other site as long as it is an organ through which blood flows.
- Heartbeat tracking is effective in applying 4D Flow MRI to support the diagnosis of cardiovascular diseases such as the heart and improving its accuracy.
- a Blood Pool contrast agent or the like has been administered to the subject P and imaged to increase the contrast.
- a contrast agent for shortening the imaging time.
- the shape identifying unit 112 uses, for example, a tracking method based on the known Lucas-Kanade method to analyze an image set showing anatomy such as SSFP instead of 4D Flow MRI. It may be possible to perform dynamic tracking.
- the region dividing unit 1120 divides the reference image, which is one of the plurality of time-series images constituting the second three-dimensional time-series image, into a plurality of regions including the heart region. good.
- 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 the heart or large cardiac blood vessels.
- the tracking unit 1122 may track the transition of the feature points in the second three-dimensional time-series image, starting from the feature points extracted by the feature point extraction unit 1121. Accordingly, the tracking unit 1122 may be capable of tracking the pulsation, which is the temporal movement of the analysis target region.
- the area changing unit 1123 may change the shape of a plurality of areas in time series based on the tracking results of feature points, and may also display the shapes on a display unit.
- the analysis target region is the heart and large cardiac blood vessels
- the shape identification unit 112 selects one time-series image from among the plurality of time-series images constituting the second three-dimensional time-series image.
- a region dividing unit 1120 that divides a reference image into a plurality of regions including the heart region;
- a feature point extraction unit 1121 that extracts one or more feature points in the reference image; 2.
- a tracking unit 1122 that tracks the transition of feature points in a three-dimensional time-series image; a region changing unit 1123 that changes the shape of the plurality of regions in time series based on the tracking results of feature points;
- the information processing device including the region changing unit 1124 that changes the shapes of the plurality of regions in time series based on the results is capable of grasping temporal fluctuations of the analysis target region in blood flow measurement. good.
- the region dividing unit 1120 divides the reference image, which is one of the plurality of time-series images constituting the second three-dimensional time-series image, into a plurality of regions including the heart region, and
- the point extraction unit 1121 extracts one or more feature points in the reference image, and the tracking unit 1122 tracks the transition of the feature points in the second three-dimensional time-series image using the feature points as a starting point.
- 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.
- the above-mentioned shape and the above-mentioned index may be output in association with each other by the output section 115 through processing by the image generation section 113 and the index generation section 114.
- the index generating section 114 is configured to generate an index regarding the blood flow flowing inside the region of the heart specified by the shape specifying section 112, thereby generating an index regarding the blood flow flowing inside the heart in particular.
- the output unit may be able to output the above-mentioned shape and the above-mentioned index in association with each other.
- FIGS. 5(a) to 5(d) are diagrams for explaining feature point tracking by the shape specifying unit 112 according to the embodiment.
- black circles marked with l indicate lattice points of a square lattice set in the reference image. In order to avoid complication, not all grid points are labeled, but black circles similar to the ones labeled l in Figures 5(a) to (d) indicate grid points.
- the lattice made up of lattice points shown in FIG. 5A is a lattice generated in the reference image by the lattice point management unit 1124 of the shape identification unit 112.
- the lattice constitutes a rectangular area with four lattice points l as vertices.
- a cross marked with c indicates the center of gravity of a rectangular region whose vertices are four grid points l.
- grid point l not all centroids are labeled with symbols to avoid complication, but crosses similar to the ones labeled with c in Figures 5(a) to (d) are squares. It shows the center of gravity of the area.
- the white circles marked with the symbol f indicate the feature points extracted by the feature point extraction unit 1121.
- the white circles similar to the white circles marked with the symbol f in Figures 5(a) to (d) are Shows feature points.
- FIG. 5(a) the arrow starting from the feature point f is a movement vector of the feature point f, and indicates the tracking result of the feature point f by the tracking unit 1122.
- FIG. 5A shows the position to which the feature point f in the reference image has moved in the image next to the reference image (that is, the frame image next to the reference image) in time series.
- the area changing unit 1123 may calculate a center-of-gravity movement vector, which is a weighted average based on the distance from the center of gravity of the rectangular area, for the movement vector of the feature point f included in each rectangular area.
- a center-of-gravity movement vector which is a weighted average based on the distance from the center of gravity of the rectangular area, for the movement vector of the feature point f included in each rectangular area.
- the arrow starting from the center of gravity c may indicate the center of gravity movement vector regarding the center of gravity c.
- arrows similar to the arrows with the symbol v in FIG. 5(b) indicate the center of gravity movement vectors.
- the area changing unit 1123 may be able to express temporal changes in each rectangular area as a vector.
- FIG. 5(c) shows the relationship between the grid point l in the reference image and the center of gravity c of each rectangular area after movement.
- the area changing unit 1123 may change the position of the lattice point l so that the center of gravity c of the rectangular area after the movement becomes the center of gravity c of the rectangular area.
- FIG. 5D shows a new grid point l changed by the area changing unit 1123 based on the movement of the center of gravity c of the rectangular area.
- the rectangular area having the four grid points l as vertices is expanded, and this corresponds to the expansion caused by the heartbeat.
- the lattice point management unit 1124 may transform the lattice generated in the reference image based on the tracking result of the feature point f by the tracking unit 1122.
- FIGS. 6(a) to 6(c) are diagrams for explaining the deformation of the lattice executed by the shape specifying unit 112 according to the embodiment. Specifically, FIG. 6(a) shows a lattice in the reference image, and FIG. 6(b) shows a lattice after transformation by the lattice point management unit 1124. Further, FIG. 6(c) shows an image in which the deformed lattice and an image showing the anatomy of the analysis target region are superimposed.
- FIG. 6A a square lattice is set in the reference image, and as a result of moving the center of gravity c of the square area based on the movement of the feature point f by the area changing unit 1123, the grid point management unit 1124
- the grid may be modified as shown in FIG. 6(b).
- FIG. 6(b) can be said to be information that reflects temporal changes in the shape of the analysis target region.
- the image generation unit 113 may generate an anatomical image in which a grid is superimposed on at least an image (ie, a second three-dimensional time-series image) showing the anatomy of the region to be analyzed.
- the image generation unit 113 may generate an anatomical image in which the deformed grid is superimposed on at least the second three-dimensional time-series image. Thereby, the medical worker can grasp the temporal fluctuation of the analysis target region at a glance in the second three-dimensional time-series images that are the image set showing the anatomy of the subject P.
- both the first three-dimensional time-series image and the second three-dimensional time-series image may be generated by the MRI imaging device 2 imaging the subject P. Therefore, the medical worker does not need to change the imaging device to capture the first three-dimensional time-series image and the second three-dimensional time-series image of the subject P.
- the first three-dimensional time-series image and the second three-dimensional time-series image can be sequentially captured, and from the viewpoint of the subject P, the subject P is simply lying on the bed provided in the MRI imaging device 2.
- the imaging of the first three-dimensional time-series image and the second three-dimensional time-series image may be completed at this point. Note that when the first three-dimensional time-series image and the second three-dimensional time-series image are sequentially captured, the order in which the two images are captured may be taken first.
- the first three-dimensional time series image and the second three-dimensional time series image are captured in order, the first three-dimensional time series image
- the difference between the imaging time of the image and the imaging time of the second three-dimensional time-series image is within a predetermined time (for example, within 10 minutes, within 5 minutes, within 3 minutes, or within 1 minute).
- the image acquisition unit 110 determines whether 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. It may also be possible to determine whether the three-dimensional time-series image and the second three-dimensional time-series image are captured in the same imaging sequence.
- the image acquisition unit 110 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, thereby obtaining the same imaging sequence. Any device that can obtain a set of images captured by the camera may be used. Thereby, the image acquisition unit 110 can guarantee that the imaging time of the image showing the anatomy of the analysis target region and the imaging time of the image showing the blood flow distribution in the analysis target region are within a predetermined time. It may be possible to suppress the deviation between the first three-dimensional time-series image and the second three-dimensional time-series image due to changes over time in the imaged region.
- the information processing device 1 also uses a second three-dimensional time-series image and a first three-dimensional time-series image, which are images showing the anatomy of the region to be analyzed, to obtain a second three-dimensional image using a contrast agent or the like. It may be possible to calculate an index related to blood flow by introducing anatomical knowledge of the target region without increasing the contrast of time-series images, that is, without using a contrast agent or the like. Thereby, the image acquisition unit 110 only needs to acquire a non-contrast second three-dimensional time-series image captured without using a contrast agent, and the burden on the subject P due to the use of a contrast agent can be reduced. good.
- FIG. 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 up.
- the image acquisition unit 110 can acquire a first three-dimensional time-series image including the analysis target region of the subject p imaged by the MRI imaging device 2 using the phase contrast method (S2). Further, the image acquisition unit 110 can acquire a second three-dimensional time-series image showing the anatomy of the subject p (S4).
- the blood flow distribution identifying unit 111 may identify the blood flow velocity distribution of the analysis target region by analyzing the first three-dimensional time-series image using a known blood flow visualization technique (S6).
- the shape identifying unit 112 may analyze the second three-dimensional time-series image and identify the shape of the region to be analyzed (S8).
- the image generation unit 113 may generate a fused image by superimposing the first three-dimensional time-series image and the second three-dimensional time-series image (S10) by using a known image synthesis technique for medical images. .
- the index generation unit 114 may generate an index regarding the blood flow flowing inside the shape based on the blood flow velocity distribution and the shape in the fused image (S12).
- the output unit 115 may output the shape of the analysis target region and the blood flow-related index in correspondence to the display unit of the information processing device 1 or a terminal capable of communicating with the information processing device 1 (S14). That is, the output unit 115 may output the shape of the analysis target region and the index related to blood flow in association with each other. Once the output unit outputs the index, the processing in this flowchart may end.
- the present invention provides an information processing system that performs the functions described in the information processing device 1 according to the embodiment, and an information processing method that performs the function, in which a program for causing a computer to perform the function is recorded. It can be implemented as a computer-readable recording medium and as a program that causes a computer to perform the function.
- This information processing system may be the information processing system described above as the second aspect of the present invention. That is, this information processing system analyzes a first three-dimensional time-series image that includes the analysis target region of a subject, which is imaged by an MRI (Magnetic Resonance Imaging) imaging device using a phase contrast method, and detects blood in the analysis target region.
- MRI Magnetic Resonance Imaging
- a shape specifying means for specifying the shape of the analysis target region; an image generating means for generating a fused image in which the first three-dimensional time series image and the second three-dimensional time series image are superimposed; An indicator generating means for generating an indicator regarding the blood flow flowing inside the shape based on the blood flow velocity distribution and the shape, and an output means for outputting the shape and the index in association with each other, It may be an information processing system.
- 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 section 111 described above.
- the shape specifying means may correspond to the shape specifying section 112 described above.
- the image generation means may correspond to the image generation section 113 described above.
- the index generation means may correspond to the index generation section 114 described above.
- the output means may correspond to the output section 115 described above.
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Abstract
Description
図1は、実施の形態に係る情報処理システムSの概要を説明するための図である。以下、図1を参照して、実施の形態の概要を述べる。
(2)医療従事者は、第1三次元時系列画像と同一の撮像シーケンスにおいて位相コントラスト法とは異なる手法で被験者Pを撮像することにより、被験者Pの解剖を示す第2三次元時系列画像を生成しうる。
図2は、情報処理装置1の全体構成の一例を示す図である。この図に示すように、情報処理装置1の全体構成は、演算処理等を行うことができるCPU20、BIOS等を格納できるROM21、作業領域であってよいRAM22、プログラム等を格納できるストレージ23を備えてよく。さらに情報処理装置1の全体構成は、入出力インターフェース24を介して入力部25、出力部26、記憶媒体27を備えることができる。入力部25は、キーボードなどの入力機器を含んでよい。出力部26は、ディスプレイなどの出力機器を含んでよい。MRI撮像装置2と情報処理装置1とのデータの送受信は、入力部25及び出力部26を介して行われてもよい。図3に示す情報処理装置1の機能構成は、図2に示す全体構成に含まれるものでよい。図3の構成においては、ROM21、RAM22、ストレージ23等の記憶装置は、記憶部10にまとめられていてよい。
この構成について説明する図4は、実施の形態に係る形状特定部112の機能構成例を模式的に示す図である。実施の形態に係る形状特定部112は、領域分割部1120、特徴点抽出部1121、追跡部1122、領域変更部1123、及び格子点管理部1124を備えていてよい。以下、実施の形態に係る情報処理装置1が解析対象とする解析対象部位が被験者Pの心臓及び心臓大血管であることを前提として、形状特定部112の機能構成について説明する。しかしながら、解析対象部位は心臓及び心臓大血管に限定されず、血液が流れる器官であれば他の部位であってもよいことは当業者であれば理解できることである。
実施の形態に係る情報処理システムSにおいて、第1三次元時系列画像と第2三次元時系列画像とは、ともにMRI撮像装置2が被験者Pを撮像することによって生成されるものでよい。このため、医療従事者は、被験者Pの第1三次元時系列画像と第2三次元時系列画像とを撮像するために撮像機器を変更する必要がないものでよい。第1三次元時系列画像と第2三次元時系列画像とは順番に連続して撮像可能であり、被験者Pの観点で見ると、被験者PはMRI撮像装置2が備える寝台に寝ているだけで第1三次元時系列画像と第2三次元時系列画像との撮像が終わるものでよい。なお、第1三次元時系列画像と第2三次元時系列画像を連続して撮像する際に両画像の撮影順序はどちらを先に行なうことでもよい。
図7は、実施の形態に係る情報処理装置1が実行する情報処理の流れを説明するためのフローチャートの例である。本フローチャートにおける処理は、例えば情報処理装置1が起動したときに開始するものでよい。
以上説明したように、実施の形態に係る情報処理装置1によれば、血流計測における被験者の負担を低減することができる。
10・・・記憶部
11・・・制御部
110・・・画像取得部
111・・・血流分布特定部
112・・・形状特定部
1120・・・領域分割部
1121・・・特徴点抽出部
1122・・・追跡部
1123・・・領域変更部
1124・・・格子点管理部
113・・・画像生成部
114・・・指標生成部
115・・・出力部
2・・・MRI撮像装置
S・・・情報処理システム
Claims (14)
- MRI(Magnetic Resonance Imaging)撮像装置によって位相コントラスト法を用いて撮像された被写体の解析対象部位を含む第1三次元時系列画像を解析して前記解析対象部位の血流速度分布を特定する血流分布特定部と、
前記位相コントラスト法を用いた撮像とは異なる手法で撮像された画像であって前記被写体の解剖を示す第2三次元時系列画像を解析して前記解析対象部位の形状を特定する形状特定部と、
前記第1三次元時系列画像と前記第2三次元時系列画像とを重ね合わせた融合画像を生成する画像生成部と、
前記融合画像における前記血流速度分布と前記形状とに基づいて、前記形状の内部を流れる血流に関する指標を生成する指標生成部と、
前記形状と前記指標とを対応づけて出力する出力部と、を備える、
情報処理装置。 - 前記解析対象部位は心臓及び心臓大血管であり、
前記形状特定部は、
前記第2三次元時系列画像を構成する複数の時系列画像のうちの一つの時系列画像である基準画像を、前記心臓の領域を含む複数の領域に分割する領域分割部と、
前記基準画像において1又は複数の特徴点を抽出する特徴点抽出部と、
前記特徴点を始点として、前記第2三次元時系列画像における前記特徴点の遷移を追跡する追跡部と、
前記特徴点の追跡結果に基づいて前記複数の領域の形状を時系列的に変化させる領域変更部と、を備える、
請求項1に記載の情報処理装置。 - 前記指標生成部は、前記形状特定部が特定した前記心臓の領域の内部を流れる血流に関する指標を生成する、
請求項2に記載の情報処理装置。 - 前記形状特定部は、前記基準画像中に格子を生成するとともに前記特徴点の追跡結果に基づいて前記格子を変形させる格子点管理部をさらに備え、
前記画像生成部は、少なくとも前記第2三次元時系列画像に変形後の格子を重畳させた解剖画像を生成する、
請求項2又は3に記載の情報処理装置。 - 前記情報処理装置は、
前記第1三次元時系列画像の撮像時刻と前記第2三次元時系列画像の撮像時刻との差が所定の時間内である画像のセットを取得する画像取得部をさらに備える、
請求項1から4のいずれか1項に記載の情報処理装置。 - 前記所定の時間が10分以内である、請求項5に記載の情報処理装置。
- 前記画像取得部は、造影剤を用いずに撮像された非造影の前記第2三次元時系列画像を取得する、
請求項5又は6に記載の情報処理装置。 - 前記位相コントラスト法を用いた撮像とは異なる手法が、SSFP、Fast Gradient Echo法、Gradient Echo法、及びBlack blood法から成る群より選択される、請求項1から7のいずれか1項に記載の情報処理装置。
- 前記血流に関する指標が、心室容量、駆出率、壁運動異常、心拍出量、加速血流の有無、心臓弁での逆流量の定量、心内シャント率の定量、局所血流量の定量、大動脈弁、僧帽弁、肺動脈弁、三尖弁等の弁を通過する流量、血管壁面のせん断応力(Wall Shear Stress;WSS)、WSSの時間変動の指標値、大動脈の流量又はエネルギー損失、血管又は心臓の変形量、血管又は心臓の長軸方向の伸び縮み、大動脈弓の曲率又は捩率の変化、心室容積の変化、並びに駆出率の変化から成る群より選択される、請求項1から8のいずれか1項に記載の情報処理装置。
- MRI撮像装置によって位相コントラスト法を用いて撮像された被写体の解析対象部位を含む第1三次元時系列画像を解析して前記解析対象部位の血流速度分布を特定する血流分布特定部と、
前記位相コントラスト法を用いた撮像とは異なる手法で撮像された画像であって前記被写体の解剖を示す第2三次元時系列画像を解析して前記解析対象部位の形状を特定する形状特定部と、
前記第1三次元時系列画像と前記第2三次元時系列画像とを重ね合わせた融合画像を生成する画像生成部と、
前記融合画像における前記血流速度分布と前記形状とに基づいて、前記形状の内部を流れる血流に関する指標を生成する指標生成部と、
前記形状と前記指標とを対応づけて出力する出力部と、を備え、
前記解析対象部位は心臓及び心臓大血管であり、
前記位相コントラスト法を用いた撮像とは異なる手法は、SSFP、Fast Gradient Echo法、Gradient Echo法、及びBlack blood法から成る群より選択され、
前記血流に関する指標は、心室容量、駆出率、壁運動異常、心拍出量、加速血流の有無、心臓弁での逆流量の定量、心内シャント率の定量、局所血流量の定量、大動脈弁、僧帽弁、肺動脈弁、三尖弁等の弁を通過する流量、血管壁面のせん断応力(Wall Shear Stress;WSS)、WSSの時間変動の指標値、大動脈の流量又はエネルギー損失、血管又は心臓の変形量、血管又は心臓の長軸方向の伸び縮み、大動脈弓の曲率又は捩率の変化、心室容積の変化、並びに駆出率の変化から成る群より選択され、
前記形状特定部は、
前記第2三次元時系列画像を構成する複数の時系列画像のうちの一つの時系列画像である基準画像を、前記心臓の領域を含む複数の領域に分割する領域分割部と、
前記基準画像において1又は複数の特徴点を抽出する特徴点抽出部と、
前記特徴点を始点として、前記第2三次元時系列画像における前記特徴点の遷移を追跡する追跡部と、
前記特徴点の追跡結果に基づいて前記複数の領域の形状を時系列的に変化させる領域変更部と、を備え、
前記指標生成部は、前記形状特定部が特定した前記心臓の領域の内部を流れる血流に関する指標を生成し、
前記形状特定部は、前記基準画像中に格子を生成するとともに前記特徴点の追跡結果に基づいて前記格子を変形させる格子点管理部をさらに備え、
前記画像生成部は、少なくとも前記第2三次元時系列画像に変形後の格子を重畳させた解剖画像を生成する、情報処理装置であって、
前記情報処理装置は、
前記第1三次元時系列画像の撮像時刻と前記第2三次元時系列画像の撮像時刻との差が10分以内である画像のセットを取得する画像取得部をさらに備え、
前記画像取得部は、造影剤を用いずに撮像された非造影の前記第2三次元時系列画像を取得する、
請求項1に記載の情報処理装置。 - MRI(Magnetic Resonance Imaging)撮像装置によって位相コントラスト法を用いて撮像された被写体の解析対象部位を含む第1三次元時系列画像を解析して前記解析対象部位の血流速度分布を特定する血流分布特定手段と、
前記位相コントラスト法を用いた撮像とは異なる手法で撮像された画像であって前記被写体の解剖を示す第2三次元時系列画像を解析して前記解析対象部位の形状を特定する形状特定手段と、
前記第1三次元時系列画像と前記第2三次元時系列画像とを重ね合わせた融合画像を生成する画像生成手段と、
前記融合画像における前記血流速度分布と前記形状とに基づいて、前記形状の内部を流れる血流に関する指標を生成する指標生成手段と、
前記形状と前記指標とを対応づけて出力する出力手段と、を備える、
情報処理システム。 - プロセッサが、
MRI撮像装置によって位相コントラスト法を用いて撮像された被写体の解析対象部位を含む第1三次元時系列画像を解析して前記解析対象部位の血流速度分布を特定するステップと、
前記位相コントラスト法を用いた撮像とは異なる手法で撮像された画像であって前記被写体の解剖を示す第2三次元時系列画像を解析して前記解析対象部位の形状を特定するステップと、
前記第1三次元時系列画像と前記第2三次元時系列画像とを重ね合わせた融合画像を生成するステップと、
前記融合画像における前記血流速度分布と前記形状とに基づいて、前記形状の内部を流れる血流に関する指標を生成するステップと、
前記形状と前記指標とを対応づけて出力するステップと、を実行する、
情報処理方法。 - コンピュータに、
MRI撮像装置によって位相コントラスト法を用いて撮像された被写体の解析対象部位を含む第1三次元時系列画像を解析して前記解析対象部位の血流速度分布を特定する機能と、
前記位相コントラスト法を用いた撮像とは異なる手法で撮像された画像であって前記被写体の解剖を示す第2三次元時系列画像を解析して前記解析対象部位の形状を特定する機能と、
前記第1三次元時系列画像と前記第2三次元時系列画像とを重ね合わせた融合画像を生成する機能と、
前記融合画像における前記血流速度分布と前記形状とに基づいて、前記形状の内部を流れる血流に関する指標を生成する機能と、
前記形状と前記指標とを対応づけて出力する機能と、を実現させる、
プログラムを記録したコンピュータ読み取り可能な記録媒体。 - コンピュータに、
MRI撮像装置によって位相コントラスト法を用いて撮像された被写体の解析対象部位を含む第1三次元時系列画像を解析して前記解析対象部位の血流速度分布を特定する機能と、
前記位相コントラスト法を用いた撮像とは異なる手法で撮像された画像であって前記被写体の解剖を示す第2三次元時系列画像を解析して前記解析対象部位の形状を特定する機能と、
前記第1三次元時系列画像と前記第2三次元時系列画像とを重ね合わせた融合画像を生成する機能と、
前記融合画像における前記血流速度分布と前記形状とに基づいて、前記形状の内部を流れる血流に関する指標を生成する機能と、
前記形状と前記指標とを対応づけて出力する機能と、を実現させる、
プログラム。
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| JP7794489B1 (ja) * | 2024-09-20 | 2026-01-06 | ソウル市立大学産学協力団 | 二尖大動脈弁を有する大動脈の血流の流れ及び大動脈のせん断応力の演算方法、これを保存した記録媒体及びこれを利用した医療機器{method for calculating blood flow and shear stress of aorta having a bicuspid aortic valve, readable medium storing the same and medical device using the same} |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012024582A (ja) * | 2010-07-21 | 2012-02-09 | Siemens Corp | 包括的な患者固有の心臓のモデリング方法およびシステム |
| WO2013077013A1 (ja) | 2011-11-25 | 2013-05-30 | 国立大学法人 東京大学 | 血流可視化診断装置 |
| WO2021084916A1 (ja) * | 2019-10-28 | 2021-05-06 | 富士フイルム株式会社 | 領域同定装置、方法およびプログラム |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| WO2013077013A1 (ja) | 2011-11-25 | 2013-05-30 | 国立大学法人 東京大学 | 血流可視化診断装置 |
| WO2021084916A1 (ja) * | 2019-10-28 | 2021-05-06 | 富士フイルム株式会社 | 領域同定装置、方法およびプログラム |
Non-Patent Citations (5)
| Title |
|---|
| ITATANI KSEKINE TYAMAGISHI MMAEDA YHIGASHITANI NMIYAZAKI SMATSUDA JTAKEHARA Y.: "Hemodynamic Parameters for Cardiovascular System in 4D Flow MRI: Mathematical Definition and Clinical Applications", MAGN RESON MED SCI, vol. 21, no. 2, 2022, pages 380 - 399 |
| ITATANI KSEKINE TYAMAGISHI MMAEDA YHIGASHITANI NMIYAZAKI SMATSUDA JTAKEHARA Y.: "Hemodynamic Parameters for Cardiovascular System in 4D Flow MRI: Mathematical Definition and Clinical Applications", MAGN RESON MED SCI., vol. 21, no. 2, 2022, pages 380 - 399 |
| MICHAEL MARKL, ALEX FRYDRYCHOWICZ, SEBASTIAN KOZERKE, MIKE HOPE, OLIVER WIEBEN: "4D flow MRI", JOURNAL OF MAGNETIC RESONANCE IMAGING, SOCIETY FOR MAGNETIC RESONANCE IMAGING, OAK BROOK, IL,, US, vol. 36, no. 5, 1 November 2012 (2012-11-01), US , pages 1015 - 1036, XP055222904, ISSN: 1053-1807, DOI: 10.1002/jmri.23632 * |
| QI ZHANG ; ROY EAGLESON ; T. M. PETERS: "GPU-Based Visualization and Synchronization of 4-D Cardiac MR and Ultrasound Images", IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE., IEEE SERVICE CENTER, LOS ALAMITOS, CA., US, vol. 16, no. 5, 1 September 2012 (2012-09-01), US , pages 878 - 890, XP011490951, ISSN: 1089-7771, DOI: 10.1109/TITB.2012.2205011 * |
| See also references of EP4512323A4 |
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|---|---|---|---|---|
| JP7794489B1 (ja) * | 2024-09-20 | 2026-01-06 | ソウル市立大学産学協力団 | 二尖大動脈弁を有する大動脈の血流の流れ及び大動脈のせん断応力の演算方法、これを保存した記録媒体及びこれを利用した医療機器{method for calculating blood flow and shear stress of aorta having a bicuspid aortic valve, readable medium storing the same and medical device using the same} |
| CN119887748A (zh) * | 2025-03-24 | 2025-04-25 | 中国人民解放军总医院第一医学中心 | 一种应用于磁共振影像的数据处理方法及其系统 |
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