Medical imaging support device, operating method for medical imaging support device, program, and medical imaging device

Abstract

A medical image pickup support device, a method for operating the medical image pickup support device, a program, and a medical image pickup device that can realize highly accurate identification of the body position of a subject are provided. [Solution] A medical image capture support device acquires multiple time-series captured images generated by capturing images of a subject, detects from the multiple time-series captured images areas of the subject's body movement in the captured images where the subject's movement occurs with a periodicity and magnitude corresponding to the subject's respiratory movement, and identifies the subject's body position based on the body movement areas.

Description

[Technical Field]

[0001] The present disclosure relates to a medical imaging support device, a method for operating a medical imaging support device, a program, and a medical imaging device. [Background technology]

[0002] In a typical MRI examination, the user sets the imaging conditions, such as the patient's position, in advance, then places the patient on a table in a shielded room, starts the scan, and begins the examination. The term "user" refers to the person who operates the MRI device, such as a technician, operator, or technician. The patient is the subject of the examination and may also be referred to as a subject, examinee, or examinee. MRI is an abbreviation for Magnetic Resonance Imaging.

[0003] Patent Document 1 describes an X-ray CT device that issues a warning when a subject's body position detected using a camera differs from a preset body position. The device described in this document identifies the subject's craniocaudal orientation and body position, etc., and if the identified body position, etc., of the subject is set to an inappropriate position, displays an inappropriate condition and a message urging the user to change the setting to an appropriate condition. Note that CT is an abbreviation for Computed Tomography. Furthermore, in this specification, identification is synonymous with recognition described in Patent Document 1. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2014-121364 Summary of the Invention [Problem to be solved by the invention]

[0005] However, when image processing is performed on the image of the subject obtained by capturing an image of the subject using a camera and the subject's posture is identified based on the results of the image processing, there is a concern that sufficient accuracy in the identification may not be achieved, and there is a desire to achieve even more accurate identification of the subject's posture.

[0006] The present disclosure has been made in consideration of the above circumstances, and aims to provide a medical image capture support device, an operating method for a medical image capture support device, a program, and a medical image capture device that can realize highly accurate identification of a subject's posture. [Means for solving the problem]

[0007] A medical image capture support device according to a first aspect of the present disclosure includes a processor and a memory for storing a program to be executed by the processor, wherein the processor acquires a plurality of time-series captured images generated by imaging a subject, detects from the plurality of time-series captured images a body movement area of ​​the subject in the captured image where the subject is moving with a periodicity and magnitude corresponding to the subject's respiratory movement, and identifies the subject's body position based on the body movement area.

[0008] According to the medical imaging support device of the first aspect, a body movement region in a captured image of a subject is detected, and the body position of the subject is identified based on the body movement region, thereby enabling the body position of the subject to be identified with high accuracy.

[0009] An example of the subject's body position is the subject's orientation relative to the direction of travel of the bed. Examples of the subject's orientation include head-first and feet-first.

[0010] The plurality of captured images in time series may be frames of a moving image, or may be a plurality of still images that are successive in time series.

[0011] A medical image pickup support device according to a second aspect is the medical image pickup support device of the first aspect, wherein the processor may detect at least one of the chest and abdomen of the subject in the captured image based on the body movement region.

[0012] In the medical image capturing support device of the third aspect, in the medical image capturing support device of the first or second aspect, the processor may detect a body movement area by applying an optical flow calculation process that calculates optical flow in a plurality of captured images in a time series.

[0013] A medical image capturing support device according to a fourth aspect is a medical image capturing support device according to any one of the first to third aspects, wherein the processor acquires a plurality of first captured images in time series obtained by capturing images of the subject using a first camera arranged on one side of the imaging space, detects a first body movement region from the plurality of first captured images in time series as a body movement region, acquires a plurality of second captured images in time series obtained by capturing images of the subject using a second camera arranged on the other side of the imaging space, detects a second body movement region from the plurality of second captured images in time series as a body movement region, and identifies the body position of the subject based on a comparison result between the first body movement region and the second body movement region.

[0014] A medical image capturing support device according to a fifth aspect is a medical image capturing support device according to any one of the first to fourth aspects, wherein the processor acquires examination site information representing the examination site, identifies the position of a body movement area in the captured image by referring to the examination site information, and identifies the subject's posture according to the position of the body movement area in the captured image.

[0015] A medical image capturing support device according to a sixth aspect is a medical image capturing support device according to any one of the first to fifth aspects, wherein the processor acquires a respiratory signal representing the respiratory movement of the subject from a respiratory sensor, and detects a body movement area based on a comparison result between the periodicity of the respiratory signal and the periodicity in an area in the captured image where periodic movement of the subject occurs.

[0016] A medical image capturing support device according to a seventh aspect is a medical image capturing support device according to any one of the first to sixth aspects, wherein the processor may identify the subject's body position as being head-first or feet-first when moving to the capturing position.

[0017] An operating method of a medical image capture support device according to an eighth aspect of the present disclosure is a method of operating a medical image capture support device, in which a computer functioning as the medical image capture support device acquires a plurality of time-series captured images generated by capturing images of a subject, detects from the plurality of time-series captured images a body movement area of ​​the subject in an image in which subject movement occurs having a periodicity and magnitude corresponding to the subject's respiratory movement, and identifies the subject's body position based on the body movement area.

[0018] According to the operation method of the medical imaging support device according to the eighth aspect of the present disclosure, it is possible to obtain the same effects as the medical imaging support device according to the first aspect. The constituent elements of the medical imaging support devices according to the second to seventh aspects can be applied as constituent elements of the operation method of the medical imaging support device according to the other aspects.

[0019] A program according to a ninth aspect of the present disclosure is a program that enables a computer functioning as a medical image capturing support device to realize the following functions: acquiring a plurality of time-series captured images generated by capturing images of a subject; detecting a body movement area of ​​the subject in the captured images from the plurality of time-series captured images where the subject is moving with a periodicity and magnitude corresponding to the subject's respiratory movement; and identifying the subject's body position based on the body movement area.

[0020] According to the program of the ninth aspect of the present disclosure, it is possible to obtain the same operational effects as those of the medical image capture support device of the first aspect. The components of the medical image capture support device of the second to seventh aspects may be applied as components of the program of the other aspects.

[0021] A medical imaging device according to a tenth aspect of the present disclosure is a medical imaging device comprising: an imaging unit that images a subject and generates imaging data of the subject; an image reconstruction unit that generates a reconstruction based on the imaging data; a processor; and a memory that stores a program to be executed by the processor, wherein the processor acquires a plurality of time-series images generated by imaging the subject; detects from the plurality of time-series images an area of ​​body movement of the subject in the image where subject movement having a periodicity and magnitude corresponding to the subject's respiratory movement occurs; and identifies the subject's body position based on the area of ​​body movement.

[0022] The medical imaging device according to the tenth aspect of the present disclosure can achieve the same effects as the medical imaging support device according to the first aspect. The components of the medical imaging support devices according to the second to sixth aspects can be applied as the components of the medical imaging devices according to the other aspects. [Effects of the Invention]

[0023] According to the present disclosure, a body movement region in a captured image of a subject is detected, and the body position of the subject is identified based on the body movement region, thereby enabling highly accurate identification of the body position of the subject. [Brief explanation of the drawings]

[0024] [Figure 1] FIG. 1 is a schematic diagram of a medical imaging system according to the first embodiment. [Figure 2] FIG. 2 is a block diagram showing a specific example of the signal analysis unit shown in FIG. [Figure 3] FIG. 3 is a block diagram showing an example of the hardware configuration of the signal processing device shown in FIGS. [Figure 4] FIG. 4 is a flowchart of the body posture identification method according to the first embodiment. [Figure 5] FIG. 5 is an explanatory diagram of a captured image of a subject captured using the first camera. [Figure 6]FIG. 6 is a schematic diagram showing the arrangement of the first camera and the second camera provided in the MRI apparatus according to the second embodiment. [Figure 7] FIG. 7 is an explanatory diagram of an image of the subject captured by the second camera. [Figure 8] FIG. 8 is a schematic diagram of a medical imaging system according to the third embodiment. [Figure 9] FIG. 9 is a flowchart of a body posture identification method according to the third embodiment. [Figure 10] FIG. 10 is an explanatory diagram of an image captured by the first camera of a subject undergoing a head examination. [Figure 11] FIG. 11 is an explanatory diagram of an image captured by the first camera of a subject undergoing a pelvic region examination. [Figure 12] FIG. 12 is an explanatory diagram of an image captured by the second camera of a subject undergoing a head examination. [Figure 13] FIG. 13 is an explanatory diagram of an image captured by the second camera of a subject undergoing a pelvic region examination. [Figure 14] FIG. 14 is an explanatory diagram of an image captured by using the first camera and the second camera on a subject undergoing an abdominal examination. [Figure 15] FIG. 15 is a schematic diagram of a medical imaging system according to the fourth embodiment. [Figure 16] FIG. 16 is a flowchart of a body posture identification method according to the fourth embodiment. [Figure 17] FIG. 17 is an explanatory diagram showing the waveform of a respiratory signal acquired using a respiratory sensor. [Figure 18] FIG. 18 is an explanatory diagram of a captured image of a subject. [Figure 19] FIG. 19 is a schematic diagram showing the period of the optical flow. DETAILED DESCRIPTION OF THE INVENTION

[0025] Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In the following description and accompanying drawings, identical components are designated by the same reference numerals, and duplicate explanations will be omitted. In addition, when multiple components are listed in the following embodiments, it can be interpreted that at least one of the multiple components is included.

[0026] [First embodiment] 1 is a schematic configuration diagram of a medical imaging system according to the first embodiment. The medical imaging system 10 includes an MRI apparatus 100 and a biological information measuring system 20. The biological information measuring system 20 includes a biological signal measuring device 120 and a signal processing device 300.

[0027] The MRI apparatus 100 includes a gantry 112, which is the main body of the imaging apparatus, and a bed 114. The gantry 112 has a cylindrical imaging space 118 called a bore. The gantry 112 is equipped with a static magnetic field generating magnet that generates a magnetic field in the imaging space 118, a gradient magnetic field coil, and various other coils.

[0028] The bed 114 includes a top plate 115 and legs 116 that support the top plate 115. The top plate 115 can be advanced into and retreated from the imaging space 118 using a drive mechanism (not shown) provided on the legs 116. The bed 114 may be configured to be fixed to the gantry 112, or may be a movable, dockable bed that can be attached to and detached from the gantry 112.

[0029] In the MRI apparatus 100, three apparatus axes are defined, which are three-dimensional Cartesian coordinate axes of a real space including an imaging space 118. The direction of each of the three apparatus axes is uniquely determined by the gantry 112 and the bed 114. In Fig. 1, the Z direction is the static magnetic field direction, the Y direction is the vertical direction, and the X direction is the direction perpendicular to the Y and Z directions.

[0030] The MRI apparatus 100 can perform imaging using biological information measured using the biological signal measuring device 120. Specifically, the MRI apparatus 100 performs synchronized imaging using biological information such as pulsation and respiratory movement. The MRI apparatus 100 also performs correction of measurement data using the biological information.

[0031] The MRI apparatus 100 includes a control device 105. The control device 105 is implemented as a computer including a processor and a memory in which a program executed by the processor is stored.

[0032] The control device 105 performs various controls such as control of capturing medical images in the MRI device 100 and control of movement of the bed 114. The control device 105 transmits signals representing various types of information in the MRI device 100 to the display device 30, and causes the display device 30 to display the various types of information.

[0033] The control device 105 may acquire various types of information transmitted from the signal processing device 300. The control device 105 may use the various types of information transmitted from the signal processing device 300 to control the imaging of medical images.

[0034] The MRI apparatus 100 is an example of a medical imaging apparatus including an imaging unit that generates imaging data of a subject according to the present disclosure and an image reconstruction unit that generates a reconstruction based on the imaging data. The medical image may be a two-dimensional reconstructed image or a three-dimensional reconstructed image.

[0035] The biological signal measuring device 120 acquires biological information in a non-contact manner from the subject 103 undergoing an examination using the MRI device 100. The biological signal measuring device 120 acquires a captured image of the subject 103 acquired by the first camera 110 as biological information, and transmits the captured image to the signal processing device 300. The signal processing device 300 identifies the body position of the subject 103 using the captured image of the subject 103.

[0036] The first camera 110 may be disposed in a shielded room. For example, the first camera 110 may be disposed on the bore side inside the gantry 112 shown in FIG. 1 . The first camera 110 may be disposed at a position on the rear side of the gantry 112. The first camera 110 may be a device capable of acquiring an image of the subject 103 other than those described above. The first camera 110 is preferably equipped with a fisheye lens and configured to be able to capture an image of the entire body of the subject 103.

[0037] The biosignal measuring device 120 may acquire a signal representing the distance between the sensor and the subject 103 as a bioinformation signal from a sensor such as a camera, infrared, or distance sensor, and transmit the acquired bioinformation signal to the signal processing device 300. The distance sensor may be an electromagnetic wave sensor such as a millimeter wave sensor, or may be an ultrasonic sensor.

[0038] The signal processing device 300 may generate various types of information about the subject 103 to be used for capturing medical images of the subject 103 based on the biological information signal acquired from the biological signal measuring device 120.

[0039] The signal processing device 300 applies image processing technology to the captured image of the subject 103 acquired using the biological signal measuring device 120, and detects a body movement region of the subject 103 that moves periodically and significantly. The signal processing device 300 identifies the body position of the subject 103 by utilizing the fact that the body movement region of the subject 103 that moves periodically and significantly is generally the upper body part of the subject 103 where respiratory movement occurs. For example, the body position of the subject 103 is identified as being head-first or feet-first.

[0040] Here, head-first refers to a body position in which the subject is carried head-first into the imaging space, and foot-first refers to a body position in which the subject is carried feet-first into the imaging space.

[0041] An example of image processing for captured images of the subject 103 is optical flow calculation processing that detects the movement of an object between two captured images in time series and calculates an optical flow that represents the movement of the object as a velocity vector.

[0042] The signal processing device 300 acquires a motion vector amount representing the magnitude of the motion of the subject 103 for a region where the subject 103 moves significantly. The signal processing device 300 may acquire the area of ​​the region where the subject 103 moves significantly, and a combination thereof.

[0043] The signal processing device 300 includes a signal analysis unit 310. The signal analysis unit 310 includes a biological information calculation unit 311, an index calculation unit 312, and a body posture identification unit 313. The biological information calculation unit 311 acquires moving images to which a specified frame rate is applied, which are captured images of the subject 103 transmitted from the biological signal measurement device 120, and detects the movement of the subject 103 based on the movement of an object between temporally adjacent frame images.

[0044] The index calculation unit 312 calculates an index value that indicates the magnitude of movement of the subject 103. The index calculation unit 312 may calculate index values ​​of areas where the subject 103 moves significantly, and combinations of these index values. An example of an index value of an area where the subject 103 moves significantly is the area of ​​the area.

[0045] The body posture identification unit 313 detects a body movement region of the subject 103 that moves periodically and significantly, based on the index value of the subject 103 calculated using the index calculation unit 312. For example, at least one of the chest and abdomen, where respiratory movement occurs due to breathing, may be detected as the body movement region of the subject 103 that moves periodically and significantly. When multiple regions where periodic movement occurs are detected, the region with the largest periodic movement may be determined to be the body movement region.

[0046] The body posture identification unit 313 identifies whether the body posture of the subject 103 is head-first or feet-first based on a body movement area in a captured image of the subject 103 that has a periodicity and size corresponding to respiratory movement.

[0047] The signal processing device 300 transmits a signal representing the body position of the subject 103 to the display device 30. The display device 30 displays information representing the body position of the subject 103. The display device 30 may display text information representing the body position of the subject 103.

[0048] The display device 30 may be used in combination with the display device provided in the bio-information measurement system 20, or may be used in combination with the display device provided in the MRI apparatus 100. The display device 30 may be a device independent of the bio-information measurement system 20 and the MRI apparatus 100.

[0049] The medical imaging system 10 may include an input device. The input device may include a keyboard, a mouse, etc. The input device may also be used as the display device 30 as a touch panel display.

[0050] [Example of signal analysis section] Fig. 2 is a block diagram showing a specific example of the signal analysis unit shown in Fig. 1. The signal analysis unit 310 includes an optical flow calculation unit 311A ​​as the biological information calculation unit 311 shown in Fig. 1.

[0051] The optical flow calculation unit 311A ​​acquires a moving image as a captured image of the subject 103 captured using the first camera 110. The captured images of the subject 103 may be a plurality of still images in time series. The image capturing time of the subject 103 may be equal to or longer than two general respiratory cycles. For example, the image capturing time of the subject 103 may be equal to or longer than 10 seconds. Here, the term "image" in this specification may include the meaning of an image signal representing an image and image data.

[0052] The optical flow calculation unit 311A ​​calculates an optical flow representing the fluctuation of the position of each pixel between two temporally adjacent frame images. The optical flow calculation unit 311A ​​may calculate the optical flow for each sub-pixel that includes multiple adjacent pixels.

[0053] The optical flow calculation unit 311A ​​switches between the frame images in chronological order for a plurality of frame images in time series, and calculates the optical flow for each combination of temporally adjacent frame images.

[0054] For example, the optical flow between the first and second frame images, which are adjacent in time, is calculated, and then the optical flow between the second and third frame images, which are adjacent in time, is calculated. Similar processing is then repeated for the third and subsequent frame images.

[0055] The index calculation unit 312 includes an FFT unit 312A. The FFT unit 312A acquires periodicity information that indicates the periodicity of the optical flow between two temporally adjacent frame images. Note that FFT is an abbreviation for Fast Fourier Transform.

[0056] The index calculation unit 312 detects a body movement region of the subject 103 in the captured image. The body movement region is a region of the subject 103 where movement occurs due to the breathing of the subject 103. The captured image of the subject 103 here may be any one of a plurality of frame images included in a moving image.

[0057] The body posture identifying section 313 identifies whether the body posture of the subject 103 is head-first or feet-first based on the body movement area of ​​the subject 103 in the captured image calculated by the index calculating section 312.

[0058] That is, the signal analysis unit 310 receives as input data moving images that are images captured of the subject 103 during an MRI examination, detects the movement of an object between two consecutive frame images, and calculates an optical flow expressed as a velocity vector.

[0059] Furthermore, the signal analysis unit 310 identifies, as a breathing area, a body movement area of ​​the subject 103 in the captured image where the most movement occurs within a certain period of time, using characteristics of respiratory movement, which is a periodic movement of the subject 103. The signal analysis unit 310 can distinguish between periodic body movement of the subject 103 and sudden body movement.

[0060] As a result, the signal analysis unit 310 identifies the body movement region of the subject 103 in the captured image, which moves periodically and significantly due to respiratory movement, as the chest of the subject 103, and identifies whether the actual body position of the subject 103 is head-first or feet-first. The body movement region may be estimated to be the abdomen of the subject 103, and the body position of the subject 103 may be identified based on the estimation result.

[0061] [Hardware configuration of signal processing device] Fig. 3 is a block diagram showing an example of the hardware configuration of the signal processing device shown in Fig. 1 and Fig. 2. Various processes of the signal processing device 300 are implemented by applying an arbitrary computer. In the arbitrary computer, a processor may execute a program to execute various processes of the signal processing device 300.

[0062] Any computer may be a general-purpose computer such as a personal computer, or a special-purpose computer such as a server computer. Any computer may be a system such as a workstation, or any other piece of hardware capable of running programs, such as a virtual machine.

[0063] At least a part of the functions of the signal processing device 300 may be realized using cloud computing. At least a part of the functions of the signal processing device 300 may be provided as SaaS. SaaS is an abbreviation for Software as a Service.

[0064] The signal processing device 300 includes a processor 322 , a memory 324 which is a main storage device, a storage 326 which is an auxiliary storage device, an input / output interface 328 , and a bus 330 .

[0065] The processor 322 is connected to a memory 324 , a storage 326 , an input / output interface 328 , an input device 332 , and a display device 334 via a bus 330 .

[0066] The memory 324 includes RAM. The memory 324 may also include ROM. The storage 326 may be, for example, a hard disk drive, a solid state drive, or a combination thereof. The storage 326 may also include an external storage device such as removable media.

[0067] RAM is an abbreviation for Random Access Memory, and ROM is an abbreviation for Read Only Memory. A hard disk drive can be abbreviated as HDD, which stands for Hard Disk Drive. A solid state drive can be abbreviated as SSD, which stands for Solid State Drive.

[0068] The storage device including the memory 324 and the storage 326 stores programs, data, and the like that realize various functions of the signal processing device 300. The processor 322 realizes various functions by executing the programs stored in the memory 324. The processor 322 comprehensively controls each part of the signal processing device 300 and various devices and units provided in the signal processing device 300, and performs various processes.

[0069] The input / output interface 328 includes a communication interface connectable to a telecommunications line such as a local area network, a connection interface connectable to an external device, etc. Examples of the connection interface connectable to an external device include a universal serial bus and HDMI (HDMI is a registered trademark). HDMI is an abbreviation for High-Definition Multimedia Interface.

[0070] The processor 322 communicates with various devices of the signal processing device 300 via the input / output interface 328, and transmits and receives various information.

[0071] Examples of the input device 332 include pointing devices such as a keyboard and a mouse. The input device 332 may include a numeric keypad and various switch buttons. The input device 332 may include a voice input device. The input device 332 may be a touch panel type input device that is integrated with the display screen of the display device 334.

[0072] The display device 334 may be a liquid crystal display, an organic EL display, or a projector. The display device 334 may be an appropriate combination of liquid crystal displays, etc. The display device 334 displays various information in addition to images captured by the signal processing device 300. The display device 334 is used as part of a UI when receiving input from the input device 332. The display device 334 is not limited to one, and a multi-display configuration having multiple display devices is also possible.

[0073] The display device 334 shown in Fig. 3 may be the display device 30 shown in Fig. 1. Note that organic EL may be referred to as OEL, which is an abbreviation for organic electro-luminescence. UI is an abbreviation for User Interface.

[0074] In this embodiment, each process is executed by a computer. A processor, a program, or a combination thereof may be applied to the computer to execute the process. The computer may be a general-purpose computer, a computer for specific applications, a system such as a workstation, or any other hardware element capable of executing a program.

[0075] The processor 322 may be configured with one or more pieces of hardware, and the type of hardware is not limited. The hardware of the processor 322 may be a CPU, an MPU, or a programmable logic device such as an FPGA. The processor 322 may be configured with a dedicated circuit that executes specific processing, such as an ASIC. The hardware of the processor 322 may be configured with a GPU that performs processing specialized for image processing, an NPU that specializes in AI processing, or the like.

[0076] The processor 322 functions as Units, which are various processing units that execute various processes, and Means, which are various processing means that execute various processes.

[0077] CPU is an abbreviation for Central Processing Unit, MPU is an abbreviation for Micro-Processing Unit, FPGA is an abbreviation for Field-Programmable Gate Array, GPU is an abbreviation for Graphics Processing Unit, AI is an abbreviation for Artificial Intelligence, and NPU is an abbreviation for Neural network Processing Unit.

[0078] The processor 322 may be configured by combining different types of hardware, such as an electric circuit in which electric circuit elements such as semiconductor elements are combined.

[0079] When multiple pieces of hardware execute any one or more processes of the processor 322, the multiple pieces of hardware may be located in devices physically separate from each other, or may be located in the same device. The order of the processes executed by the processor 322 is not limited to the order disclosed in this specification and may be changed as appropriate. The hardware is configured using an electric circuit or the like that combines circuit elements such as semiconductor elements.

[0080] Furthermore, the present embodiment may be realized by applying hardware, software, firmware, microcode, or a combination thereof. The software, firmware, and microcode are configured by applying a program. For example, the program may be a group of program modules, and the functions of the software or the like may be realized by applying a processor that executes each function.

[0081] The program may be, for example, a program code and a plurality of code segments stored in one or more non-transitory computer-readable media such as a storage medium and a storage device. The program may be stored in a plurality of non-transitory computer-readable media that are physically separate from each other.

[0082] A program code or code segment may represent any combination of a procedure, a function, a subprogram, a routine, a subroutine, a module, a software package, a class, an instruction, a data structure, or a program statement. The program code or code segment may be connected to another code segment or a hardware circuit by sending or receiving information, data, arguments, parameters, or memory contents.

[0083] [Procedure of the body posture identification method according to the first embodiment] 4 is a flowchart of a body posture identification method according to the first embodiment. The body posture identification method whose steps are shown in the figure is an example of a method for operating the medical image pickup support device of the present disclosure.

[0084] In step S10, the subject 103 placed on the bed 114 arranged on the front side of the gantry 112 is transported to the imaging space 118 inside the gantry 112. That is, in step S10, an operator such as a technician operates a movement control device for the bed 114 to move the bed 114, on which the subject 103 lies on a top board 115, from a specified position outside the gantry 112 to a specified position inside the imaging space 118 of the gantry 112, and stop the bed 114. The front side of the gantry 112 may also be referred to as the front side of the gantry 112, the front side of the gantry 112, etc.

[0085] In step S12, imaging using the first camera 110 is started for the subject 103 placed on the bed 114 stopped at a specified position in the imaging space 118 according to the examination region, and acquisition of a moving image is started as a captured image of the subject 103. The captured image of the subject 103 may be referred to as a video signal of the subject 103.

[0086] The imaging of the subject 103 using the first camera 110 is performed before the imaging to acquire medical images of the subject 103 begins, and is completed before the imaging to acquire medical images of the subject 103 begins.

[0087] In step S14, the signal analysis unit 310 calculates an optical flow based on the captured image of the subject 103, and identifies at least one of the chest region and the abdominal region from the body movement region of the subject 103 in the captured image. The case where the chest region is identified will be described below. The chest region is designated by the reference numeral 402 and is illustrated in FIG. 5 etc.

[0088] In step S16, the body posture identification unit 313 identifies whether the body posture of the subject 103 is head-first or feet-first, based on the chest region in the captured image of the subject 103. Information on the body posture of the subject 103 may be displayed on the display device 30. Once the body posture of the subject 103 has been identified, the procedure of the body posture identification method is completed.

[0089] [Example of a photographed image of a subject] 5 is an explanatory diagram of a captured image of a subject captured using the first camera. In the first captured image 400 shown in the drawing, the left side as viewed from the center of the left and right sides is the rear side of the imaging space 118, and the right side as viewed from the center of the left and right sides of the first captured image 400 is the front side of the imaging space 118. The entrance 119 of the imaging space 118 is captured at the right end of the first captured image 400.

[0090] The rear side of the imaging space 118 may be referred to as the rear, back side, or deep side of the imaging space 118. The front side of the imaging space 118 may be referred to as the front, front side, or front side of the imaging space 118. The position of the rear side of the imaging space 118 is an example of one side of the imaging space of the present disclosure.

[0091] The first captured image 400 shows the subject 103 wearing the head receiver coil 150 on his head. The chest region 402 of the subject 103 in the first captured image 400 is identified in step S14 of FIG. 4 using the signal analysis unit 310 shown in FIG.

[0092] The body posture identifying section 313 identifies the body posture of the subject 103 as head-first based on the position of the chest region 402 of the subject 103 in the first captured image 400.

[0093] [Effects of the first embodiment] The signal processing device and the body posture identification method according to the first embodiment can achieve the following advantageous effects.

[0094] [1] Using the first camera 110 arranged on the rear side of the imaging space 118, a moving image is captured as a first captured image 400 of the subject 103 at a position where a medical image is captured. An optical flow is calculated from the first captured image 400 of the subject 103, and a chest region 402 of the subject 103 in the first captured image 400 is identified based on the optical flow.

[0095] Whether the body posture of the subject 103 is head-first or feet-first is identified based on the position of the chest region 402 of the subject 103 in the first captured image 400. This allows the body posture of the subject 103 to be identified with high accuracy.

[0096] [2] From the first captured image 400 of the subject 103, a body movement region where movement occurs with periodicity and magnitude corresponding to the respiratory movement of the subject 103 is identified as the chest region 402. In this way, the characteristics of respiratory movement that move periodically and significantly are used, and the chest region 402 of the subject 103 is identified with high accuracy.

[0097] In this embodiment, capturing of a moving image of the subject 103 is exemplified, but the image of the subject 103 may be capturing of continuous still images to which a specified cycle is applied. The specified cycle may be more than twice the respiratory cycle of a typical human.

[0098] [Second embodiment] 6 is a schematic diagram showing the arrangement of a first camera and a second camera provided in an MRI apparatus according to the second embodiment. In the MRI apparatus 100A according to the second embodiment, a first camera 110 is arranged on the rear side of an imaging space 118, and a second camera 111 is arranged on the front side of the imaging space 118. The second camera 111 may be a camera equipped with a fisheye lens, similar to the first camera 110. Note that the front side of the imaging space 118 is an example of the other side of the imaging space in the present disclosure.

[0099] The biosignal measuring device 120 shown in Figure 1 acquires a first captured image, which is a moving image of the subject 103 captured using a first camera 110, and a second captured image, which is a moving image of the subject 103 captured using a second camera 111.

[0100] The signal processing device 300 acquires a first captured image and a second captured image from the biological signal measuring device 120. The signal processing device 300 calculates a first optical flow based on the first captured image, and calculates a second optical flow based on the second captured image.

[0101] The body posture identification unit 313 detects a first body movement region based on the first optical flow and detects a second body movement region based on the second optical flow. The body posture identification unit 313 compares the first body movement region with the second body movement region, and identifies the chest region 402 of the subject 103 based on the comparison result.

[0102] The procedure of the body posture identification method according to the second embodiment is similar to the procedure of the body posture identification method according to the first embodiment shown in FIG. 4, except for the processes in steps S12, S13, and S14, as described above.

[0103] [Example of the second captured image] 7 is an explanatory diagram of a second captured image of the subject captured using the second camera. The second captured image 410 shown in the drawing is generated by capturing an image of the subject 103 shown in FIG. 6 using the second camera 111.

[0104] The left side of the center in the second captured image 410 is the front side of the imaging space 118, and the right side of the center in the second captured image 410 is the rear side of the imaging space 118.

[0105] 1 identifies the chest region 402 in the second captured image 410 from the second optical flow calculated based on the second captured image 410. The body posture identification unit 313 compares the chest region 402 in the first captured image 400 shown in Fig. 5 with the chest region 402 in the second captured image 410, and identifies the body posture of the subject 103 based on the more likely chest region.

[0106] The posture identification section 313 may compare the area of ​​the chest region 402 in the first captured image 400 with the area of ​​the chest region 402 in the second captured image 410, and identify the posture of the subject 103 based on the captured image having a chest region with a relatively larger area.

[0107] 5 and 7, the chest region 402 shown in Fig. 5 has a larger area than the chest region 402 shown in Fig. 7. The body posture identification section 313 may identify the body posture of the subject 103 based on the chest region 402 in the first captured image 400.

[0108] [Effects of the second embodiment] The configuration including the first camera 110 and the second camera 111 is effective for abdominal examinations where the accuracy of identifying the body position of the subject 103 is a concern when only one camera including the first camera 110 is used.

[0109] In the case of an abdominal examination, regardless of whether the subject 103 is in a head-first or feet-first position, upper body movements due to breathing may occur at multiple close positions in the first captured image 400. When a single camera is used, there is a problem that the subject's 103 position may be erroneously identified.

[0110] When two cameras are provided, it is possible to technically control which of the images is of the subject 103 whose breathing-related movements are relatively large, which is expected to improve the accuracy of identifying the position of the subject 103 during abdominal examinations, for example.

[0111] [Third embodiment] 8 is a schematic configuration diagram of a medical imaging system according to the third embodiment. The medical imaging system 10B shown in the figure includes an MRI apparatus 100 and a biological information measurement system 20B. The biological information measurement system 20B includes an examination region information acquisition unit 130.

[0112] The examination region information acquiring unit 130 acquires examination region information related to the examination region of the subject 103, including the name of the examination region, etc. The examination region information acquiring unit 130 may acquire examination region information registered in the MRI apparatus 100, or may acquire examination region information manually input by an operator.

[0113] 8 acquires examination region information from the examination region information acquisition unit 130. The body position identification unit 313B refers to the examination region of the subject 103 identified from the examination region information, and identifies whether the body position of the subject 103 is head-first or feet-first.

[0114] [Procedure of Body Posture Identification Method According to Third Embodiment] 9 is a flowchart of the body posture identification method according to the third embodiment. In the body posture identification method according to the third embodiment, first, step S100 is executed to acquire examination region information of the subject 103.

[0115] After the examination region information is acquired in step S100, steps S110, S112, S114, and S116 are executed. Steps S110, S112, and S114 shown in Fig. 8 are performed in the same manner as steps S10, S12, and S14 shown in Fig. 4, respectively.

[0116] In step S116, the body position of the subject 103 is identified based on the examination region information acquired in step S100 and the chest region 402 identified in step S114.

[0117] [Example of captured image] 10 is an explanatory diagram of a captured image of a subject undergoing a head examination, captured using the first camera. The figure shows a first captured image 400B1 when the examination site is the head. The first captured image 400B1 shows the subject 103 wearing the head receiver coil 150.

[0118] When the examination site is the head, if the subject 103 is in a head-first position, movement due to respiratory movement of the subject 103 may occur on the front side of the imaging space 118 in the first captured image 400B1. On the other hand, if the subject 103 is in a feet-first position, movement due to respiratory movement of the subject 103 may occur on the rear side of the imaging space 118 in the first captured image 400B1.

[0119] The area to the right of the horizontal center in the first captured image 400B1 is the front side of the imaging space 118, and the area to the left of the horizontal center is the rear side of the imaging space 118. If the subject 103 is in a head-first position, movement due to respiratory movement of the subject 103 may occur to the right of the horizontal center in the first captured image 400B1. On the other hand, if the subject 103 is in a feet-first position, movement due to respiratory movement of the subject 103 may occur to the left of the horizontal center in the first captured image 400B1.

[0120] When the examination site is the head, there may be cases where the chest region 402 is not identified as in the first captured image 400B1. In such cases, the body position of the subject 103 may be identified as head-first. On the other hand, when the chest region 402 is identified in the first captured image 400B1, the body position of the subject 103 may be identified as feet-first.

[0121] 11 is an explanatory diagram of a captured image of a subject undergoing a pelvic region examination using the first camera. The figure shows a first captured image 400B2 when the examination site is the pelvis or the vicinity of the pelvis. The first captured image 400B2 shows the subject 103 wearing the pelvic receiver coil 152. The chest region 402 of the subject 103 is also identified in the first captured image 400B2.

[0122] When the examination site is the pelvis or the vicinity of the pelvis, if the subject 103 is in a head-first position, movement due to respiratory movement of the subject 103 may occur on the rear side of the imaging space 118 in the first captured image 400B2. On the other hand, if the subject 103 is in a feet-first position, movement due to respiratory movement of the subject 103 may occur on the front side of the imaging space 118 in the first captured image 400B2.

[0123] 11, the right side of the horizontal center in the first captured image 400B2 is the front side of the imaging space 118, and the left side of the horizontal center is the rear side of the imaging space 118. If the subject 103 is in a head-first position, movement due to respiratory movement of the subject 103 may occur to the left of the horizontal center in the first captured image 400B1. On the other hand, if the subject 103 is in a feet-first position, movement due to respiratory movement of the subject 103 may occur to the right of the horizontal center in the first captured image 400B1.

[0124] 11, a chest region 402 of the subject 103 is identified as being relatively large and extending near the center of the left and right sides. In such a case, the body position of the subject 103 may be identified as being head-first. On the other hand, if a chest region 402 of the subject 103 is identified as being relatively small and to the right of the center of the left and right sides in the first captured image 400B2, the body position of the subject 103 may be identified as being feet-first.

[0125] In this way, the examination region information is used to identify the region in which the chest region 402 of the subject 103 may appear in the first captured image 400B1 etc., depending on the body position of the subject 103.

[0126] When the examination site is the abdomen, the subject 103 may be asked to move his / her head, and the body position of the subject 103 may be determined based on the part that the subject 103 moves.

[0127] [Modification of the third embodiment] The third embodiment may be combined with the second embodiment, that is, the MRI apparatus 100 shown in Fig. 8 may be provided with the second camera 111 shown in Fig. 6.

[0128] 12 is an explanatory diagram of an image captured by the second camera of a subject undergoing a head examination. The figure shows a second captured image 410B1 when the examination site is the head. The second captured image 410B1 shows the subject 103 wearing the head receiver coil 150.

[0129] 12, the left side of the horizontal center in the second captured image 410B1 is the front side of the imaging space 118, and the right side of the horizontal center is the rear side of the imaging space 118. When the examination site is the head, if the subject 103 is in a head-first position, movement due to respiratory movement of the subject 103 may occur to the left of the horizontal center in the second captured image 410B1. On the other hand, if the subject 103 is in a feet-first position, movement due to respiratory movement of the subject 103 may occur to the right of the horizontal center in the second captured image 410B1.

[0130] Comparing the first captured image 400B1 shown in FIG. 10 with the second captured image 410B1 shown in FIG. 12, the difference is that the chest region 402 of the subject 103 is not identified in the first captured image 400B1, whereas the chest region 402 of the subject 103 extending from the center to the left side is identified in the second captured image 410B1.

[0131] From the comparison result between the first captured image 400B1 and the second captured image 410B1, it is determined that the body position of the subject 103 is head-first, based on the position of the chest region 402 of the subject 103 in the second captured image 410B1.

[0132] 13 is an explanatory diagram of a captured image of a subject undergoing a pelvic region examination using the second camera. The figure shows a second captured image 410B2 when the examination site is the pelvis or the vicinity of the pelvis. The second captured image 410B2 shows the subject 103 wearing the pelvis receiver coil 152.

[0133] 13, the left side of the horizontal center in the second captured image 410B2 is the front side of the imaging space 118, and the right side of the horizontal center is the rear side of the imaging space 118. When the examination site is the pelvis or the vicinity of the pelvis, if the subject 103 is in a head-first position, movement due to respiratory movement of the subject 103 occurs to the right of the horizontal center in the second captured image 410B2. On the other hand, if the subject 103 is in a feet-first position, movement due to respiratory movement of the subject 103 occurs to the left of the horizontal center in the second captured image 410B2.

[0134] Comparing the first captured image 400B2 shown in FIG. 11 with the second captured image 410B2 shown in FIG. 13, the first captured image 400B2 identifies a chest region 402 of the subject 103 that is larger in area than the chest region 402 of the subject 103 identified in the second captured image 410B2.

[0135] From the comparison result between the first captured image 400B2 and the second captured image 410B2, it can be determined that the body position of the subject 103 is head-first, based on the position of the chest region 402 of the subject 103 in the first captured image 400B2.

[0136] Fig. 14 is an explanatory diagram of captured images of a subject undergoing an abdominal examination using the first and second cameras. Diagram 14A on the right in Fig. 14 illustrates a first captured image 400B3 captured using the first camera 110. Diagram 14B on the left illustrates a second captured image 410B3 captured using the second camera 111.

[0137] The first captured image 400B3 shown in FIG. 14A on the right shows the subject 103 wearing the abdominal receive coil 154. In the first captured image 400B3, a chest region 402 is identified on the right side of the center.

[0138] The second captured image 410B3 shown in FIG. 14B on the left shows the subject 103 wearing the abdominal receiver coil 154. In the second captured image 410B3, a chest region 402 that is larger in area than the chest region 402 in the first captured image 400B3 is identified to the left of the center in the left-right direction.

[0139] The right side of the horizontal center in the first captured image 400B3 is the front side of the imaging space 118, and the left side of the horizontal center is the rear side of the imaging space 118. The left side of the horizontal center in the second captured image 410B3 is the front side of the imaging space 118, and the right side of the horizontal center is the rear side of the imaging space 118.

[0140] When the examination site is the abdomen, if the subject 103 is in a head-first position, movement of the subject 103 due to respiratory movement of the subject 103 may occur on the rear side of the imaging space 118. On the other hand, when the examination site is the abdomen, if the subject 103 is in a feet-first position, movement of the subject 103 due to respiratory movement of the subject 103 may occur on the front side of the imaging space 118.

[0141] From the comparison result between the first captured image 400B3 and the second captured image 410B3, it can be identified that the body position of the subject 103 is feet-first, based on the chest region 402 identified in the second captured image 410B3.

[0142] [Effects of the third embodiment] The signal processing device and the body posture identification method according to the third embodiment can achieve the following advantageous effects.

[0143] [1] The examination region information assists in identifying the position of the chest region 402 in the first captured image of the subject 103. This allows the chest region 402 in the captured image of the subject 103 to be identified with high accuracy.

[0144] [2] A second captured image is acquired using the second camera 111, and based on a comparison result between the first captured image and the second captured image, the chest region 402 of the subject 103 in at least one of the first captured image and the second captured image is identified. This makes it possible to identify the chest region 402 in the captured image of the subject 103 with even higher accuracy.

[0145] [Fourth embodiment] 15 is a schematic diagram of a medical imaging system according to the fourth embodiment. An MRI apparatus 100C included in the medical imaging system 10C shown in the figure includes a respiratory sensor 140 that detects respiratory movement of a subject 103 and outputs a respiratory signal. The respiratory sensor 140 may be a contact type that comes into contact with the subject 103, or a non-contact type that does not come into contact with the subject 103.

[0146] The biological information measurement system 20C also includes a respiratory signal measuring device 142 that acquires a respiratory signal output from the respiratory sensor 140. The respiratory signal measuring device 142 acquires respiratory information of the subject 103 as biological information of the subject 103. The respiratory signal measuring device 142 transmits the respiratory signal to the signal processing device 300.

[0147] The biological information calculation unit 311 provided in the signal processing device 300 detects a periodically moving body movement area obtained as the optical flow of the subject 103, which is similar to the periodic breathing signal of the subject 103, and estimates the detected body movement area as at least one of the chest and abdomen of the subject 103.

[0148] The body posture identifying section 313 identifies whether the body posture of the subject 103 is head-first or feet-first based on a body movement region estimated as the chest or the like in a captured image of the subject 103 .

[0149] [Procedure of the posture identification method according to the fourth embodiment] 16 is a flowchart of a body posture identification method according to the fourth embodiment. In step S200, the same process as in step S10 shown in Fig. 1 is executed. In step S202, the signal analysis unit 310 acquires a respiratory signal from the respiratory sensor 140 via the respiratory signal measurement device 142.

[0150] In step S204, the same processing as in step S12 shown in Fig. 1 is executed. In step S206, the signal analysis unit 310 calculates an optical flow based on the captured image of the subject 103.

[0151] In step S208, the signal analysis unit 310 compares the period of the optical flow calculated in step S206 with the period of the respiratory signal acquired in step S202.

[0152] In step S208, based on the comparison result between the period of the optical flow and the period of the respiratory signal, it is identified which areas in the first captured image and the second captured image have a movement with a period similar to that of the respiratory signal. Furthermore, in step S208, based on the identification result, the chest region 402 of the subject 103 is specified.

[0153] 17 is an explanatory diagram showing the waveform of a respiratory signal acquired using a respiratory sensor. The figure is shown in a graph format. The horizontal axis of the graph shown in the figure represents time, and the vertical axis represents the signal value of the respiratory signal.

[0154] 18A is an explanatory diagram of captured images of a subject. The right-hand diagram 18A shows a first captured image 400C generated by capturing an image of the subject 103 using the first camera 110. The left-hand diagram 18B shows a second captured image 410C generated by capturing an image of the subject 103 using the second camera 111.

[0155] In the second captured image 410C, the period of the optical flow of the body movement region 420 corresponding to the abdomen and the period of the optical flow of the body movement region 424 corresponding to the hip joint are calculated, and in the first captured image 400C, the period of the optical flow of the body movement region 422 corresponding to the chest is calculated.

[0156] FIG. 19 is a schematic diagram showing the period of optical flow. A graph is used in the diagram to diagrammatically illustrate the period of optical flow. The horizontal axis of the graph shown in the diagram represents time, and the vertical axis represents the optical flow value. The optical flow value may be a representative value of the optical flow for each pixel. The representative value of the optical flow may be the maximum value of the optical flow for each pixel.

[0157] The optical flow value may be calculated by dividing the area to be calculated into sections and then calculating the average value of the optical flows of all pixels in the area. The average value may be an arithmetic average value.

[0158] Waveform 440 represents the period of the optical flow in body motion region 420 corresponding to the abdomen. Waveform 442 represents the period of the optical flow in body motion region 422 corresponding to the chest. Waveform 444 represents the period of the optical flow in body motion region 424 corresponding to the hip joint.

[0159] In step S208 shown in FIG. 16, the body posture identification unit 313 shown in FIG. 15 compares the period of the respiratory signal shown in FIG. 17 with the period of the optical flow of each part shown in FIG.

[0160] Furthermore, in step S208, based on the comparison result, the captured image of the subject 103 that includes a body movement region having a period similar to the period of the respiratory signal is identified, and the body position of the subject 103 is identified.

[0161] [Effects of the fourth embodiment] In the signal processing device and the body posture identification method according to the fourth embodiment, a respiratory signal representing the respiratory movement of the subject 103 is acquired using a respiratory sensor 140. A captured image of the subject 103 for which an optical flow having a period similar to that of the respiratory signal is calculated is identified. The body posture of the subject 103 is identified based on the identified captured image. This allows the body posture of the subject 103 to be identified with high accuracy.

[0162] [Outline of MRI imaging procedure] A typical imaging procedure applied to the MRI apparatus according to each of the first to fourth embodiments is roughly as follows.

[0163] [Step 1] An operator such as a technician sets subject information, an examination protocol that specifies the imaging region corresponding to the target disease, the type of imaging, and other information required for the examination using an input device 332 such as a mouse and keyboard. The operator is synonymous with the user and the operator.

[0164] The subject information includes the subject's name, subject code, etc. Some or all of this information may be manually input by the operator via the input device 332, or information stored in advance on a recording medium or the like may be read. Note that the automatically set or input parameters are ultimately checked by the operator, and are manually set via the input device 212 as necessary.

[0165] [Step 2] The subject 103 is placed on the top board 115 of the bed 114, and a receiving coil such as the head receiving coil 150 is attached to the subject 103. The operator connects the receiving side connector of the receiving coil to the nearest bed side connector.

[0166] When the receiving coil is connected to the bed-side connector, a determination is made of the body position of the subject 103. The body position of the subject 103 includes the posture of the subject 103 and the insertion direction of the subject 103 into the gantry 112.

[0167] Examples of the posture of the subject 103 include a supine position, a prone position, a right lateral position, and a left lateral position. Examples of the posture of the subject 103 and the insertion direction of the subject 103 into the gantry 112 include a head-first position and a feet-first position.

[0168] [Step 3] Using the gantry operation panel or foot switch, the tabletop 115 is moved to the imaging space 118, and the area to be examined of the subject 103 is moved to the center position of the static magnetic field of the gantry 112. The gantry operation panel and foot switch are not shown in the figures.

[0169] [Step 4] Scanogram imaging is performed to obtain a positioning image. In scanogram imaging, multiple slices are imaged on one or more of the axial, coronal, and sagittal planes. The slice thickness in scanogram imaging may be set to a value greater than the slice thickness in actual imaging.

[0170] [Step 5] After scanogram imaging is completed, an image for positioning is reconstructed. The reconstructed 3D scanogram image is displayed on the display device 334. The scanogram image may include 2D slice images in each of the axial, coronal, and sagittal planes. The 2D slice images may include multiple slice images for each plane.

[0171] [Step 6] The operator sets the imaging position for the actual imaging based on the cross-sectional image generated from the 3D scanogram image. In the MRI apparatus 100 according to this embodiment, the imaging position including the slice position, which is the cross-sectional position to be measured in the actual imaging, is automatically calculated from the 3D scanogram image, and the recommended imaging position is presented to the operator. The operator checks the presented slice position and the like, and manually adjusts the imaging position using the input device 332 as necessary.

[0172] The operator also sets the imaging parameters to be applied to the actual imaging. Some or all of the imaging parameters may be input by a user such as a technician, or may be set or input automatically. The automatically set or input parameters are finally checked by the operator, and if necessary, are manually set via the input device 212.

[0173] [Step 7] The actual imaging is performed according to the imaging parameters and imaging position set in step 6.

[0174] [Step 8] Actual imaging is performed and an image is reconstructed. The reconstructed image is displayed on the display device 334.

[0175] [Step 9] For the reconstructed image displayed on the display device 214, the operator uses the input device 332 to set a window value suitable for diagnosis, and obtains an image to be used for diagnosis.

[0176] [Step 10] When imaging is completed, the top board 115 is removed from the imaging space 118, and the subject 103 is removed from the gantry 112. The subject 103 is then removed from the bed 114, and the MRI examination is completed.

[0177] [Examples of application to programs and program products] The body posture identification method according to the embodiment may be configured as a program or a program product in which a processor or a computer including a processor implements the functions of the steps.

[0178] For example, a program or program product may be configured to cause a computer to realize the functions of acquiring an image of the subject 103, detecting the movement area of ​​the subject 103 from the image of the subject 103, and identifying the posture of the subject 103 based on the movement area of ​​the subject 103.

[0179] The program or program product may be stored in a computer-readable medium that is a tangible, non-transitory information storage medium, or may be provided through an information storage medium.

[0180] The present disclosure is not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the technical idea of ​​the present disclosure. Furthermore, the first to fourth embodiments can be combined as appropriate. [Explanation of symbols]

[0181] 10 Medical imaging system 10B Medical Imaging System 14A Right 14B Left figure 18A Right 18B Left figure 20 Biological Information Measurement System 20B Biological Information Measurement System 20C Biological Information Measurement System 30 Display device 100 MRI machine 100A MRI machine 103 Subjects 105 Control device 110 Camera 1 111 Second Camera 112 Gantry 114 berths 115 Top Plate 116 Legs 118 Imaging Space 119 Entrance 120 Biosignal Measurement Device 130 Examination area acquisition unit 140 Respiration Sensor 142 Respiratory signal measuring device 150 Head receiving coil 152 Pelvic receiving coil 154 Abdominal receiving coil 300 Signal Processing Device 300B Signal Processing Device 310 Signal analysis section 310B Signal analysis section 311 Biometric Information Calculation Unit 311A Optical flow calculation unit 312 Indicator calculation section 312A FFT section 313 Posture Identification Unit 313B Body position identification part 322 processors 324 memory 326 Storage 328 Input / Output Interface 330 Bus 332 Input Device 334 Display device 400 First captured image 400B1 First captured image 400B2 First captured image 400B3 First captured image 402 Thoracic region 410 Second captured image 410B1 Second captured image 410B2 Second captured image 410B3 Second captured image 420 Body Movement Area 422 Body Movement Area 424 Body Movement Area 440 waveform 442 Waveform 444 Waveform S10 to S16: Each step of the body position identification method S100 to S116: Each step of the body position identification method S200 to S208: Each step of the body position identification method

Claims

1. a processor; a memory for storing a program to be executed by the processor; Equipped with The processor: Acquiring a plurality of time-series captured images generated by capturing an image of a subject; detecting a body movement region of the subject in the captured images in which a movement of the subject occurs, the movement having a periodicity and magnitude corresponding to a respiratory movement of the subject, from the plurality of captured images in time series; identifying a body position of the subject based on the body movement region; Medical imaging support device.

2. The processor: detecting at least one of a chest region and an abdomen region of the subject in the captured image based on the body movement region; The medical image capture support device according to claim 1 .

3. The processor: detecting the body movement region by applying an optical flow calculation process that calculates an optical flow in the plurality of captured images in time series; The medical image capture support device according to claim 1 .

4. The processor: acquiring a plurality of first captured images in time series obtained by capturing an image of the subject using a first camera arranged on one side of an imaging space; detecting a first body movement region as the body movement region from the plurality of first captured images in time series; acquiring a plurality of second captured images in time series obtained by capturing an image of the subject using a second camera arranged on the other side of the imaging space; detecting a second body movement region as the body movement region from the plurality of second captured images in time series; identifying a body posture of the subject according to a comparison result between the first body movement region and the second body movement region; The medical image capture support device according to claim 1 .

5. The processor: Obtaining examination site information representing the examination site; By referring to the examination region information, the position of the body movement region in the captured image is identified; identifying a body posture of the subject according to a position of the body movement region in the captured image; The medical image capture support device according to claim 1 .

6. The processor: acquiring a respiratory signal representing the respiratory movement of the subject from a respiratory sensor; detecting the body movement region based on a comparison result between the periodicity of the respiratory signal and the periodicity of a region in the captured image where the subject's periodic movement occurs; The medical image capture support device according to claim 1 .

7. the processor identifies, as the body posture of the subject, whether the subject moving to the imaging position is head first or feet first; The medical image capture support device according to claim 1 .

8. A computer that functions as a medical image acquisition support device, Acquiring a plurality of time-series captured images generated by capturing an image of a subject; detecting a body movement region of the subject in the captured images in which a movement of the subject occurs, the movement having a periodicity and magnitude corresponding to a respiratory movement of the subject, from the plurality of captured images in time series; identifying a body position of the subject based on the body movement region; A method for operating a medical imaging support device.

9. A computer that functions as a medical image acquisition support device, A function of acquiring a plurality of time-series captured images generated by capturing an image of a subject; a function of detecting, from the plurality of time-series captured images, a body movement region of the subject in the captured images where the subject's movement occurs, the movement having a periodicity and magnitude corresponding to the subject's respiratory movement; and realizing a function of identifying the body posture of the subject based on the body movement region; program.

10. an imaging unit that images a subject and generates imaging data of the subject; an image reconstruction unit for generating a reconstruction based on the imaging data; a processor; a memory for storing a program to be executed by the processor; Equipped with The processor: Acquiring a plurality of time-series captured images generated by capturing an image of a subject; detecting a body movement region of the subject in the captured images in which a movement of the subject occurs, the movement having a periodicity and magnitude corresponding to a respiratory movement of the subject, from the plurality of captured images in time series; identifying a body position of the subject based on the body movement region; Medical imaging equipment.

Images