Motion image processing device, motion image processing method, and program

Abstract

The present invention provides a motion image processing device, etc., that can acquire motion images suitable for motion analysis processing. [Solution] The motion analysis device 3 includes an acquisition unit that acquires motion images composed of multiple frame images obtained by motion imaging using radiation, a setting unit that sets a predetermined region of interest for each of the multiple frame images acquired by the acquisition unit, and a generation unit that generates waveform information showing the change in the signal value of each pixel in the region of interest of the multiple frame images set by the setting unit. The setting unit sets a region of interest in the other frame images by performing tracking of the region of interest set in one of the multiple frame images for the other frame images.

Description

Technical Field

[0001] The present invention relates to a dynamic image processing apparatus, a dynamic image processing method, and a program.

Background Art

[0002] Clinical research on dynamic analysis using X-ray dynamic images has been progressing, and dynamic analysis is being utilized in the examination of various diseases. For example, a dynamic analysis theory for analyzing blood flow such as pulmonary blood flow and cardiac blood flow using X-ray dynamic images has been developed. Patent Document 1 describes a dynamic image analysis apparatus that generates information related to pulmonary valve regurgitation based on dynamic images of at least one of the pulmonary artery and the heart.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In dynamic analysis processing, a predetermined region of interest is set for each frame image of a dynamic image, and a blood flow waveform or the like is observed from changes in the signal values of each region of interest. Here, when setting the region of interest, unexpected movements of the patient, such as body movement due to coughing or the like, may occur. When an unexpected movement of the patient occurs, the position of the region of interest shifts between frame images, and there is a possibility of observing changes in the signal values of an unexpected region different from the region of interest set in the frame image. As a result, there is a problem that false analysis occurs and an appropriate analysis result of the expected region cannot be obtained.

[0005] Therefore, an object of the present invention is to provide a dynamic image processing apparatus, a dynamic image processing method, and a program that can acquire a dynamic image suitable for dynamic analysis processing in order to solve the above problems.

Means for Solving the Problems

[0006] The motion image processing apparatus according to the present invention is An acquisition unit that acquires a motion image composed of multiple frame images obtained by motion imaging using radiation, A setting unit sets a predetermined region of interest for each of the plurality of frame images acquired by the acquisition unit, The system includes a generation unit that generates waveform information showing the change in the signal value of each pixel in the region of interest of the plurality of frame images set by the setting unit, The setting unit sets the region of interest in the other frame images by performing tracking of the region of interest set in one of the multiple frame images as a reference frame image on the other frame images.

[0007] The motion image processing method according to the present invention is An acquisition step to acquire a motion image consisting of multiple frame images obtained by motion imaging using radiation, A setting step of setting a predetermined region of interest for each of the acquired multiple frame images, The process includes a generation step of generating waveform information that shows the change in the signal value of each pixel in the region of interest of the set plurality of frame images, In the setting step, the region of interest is set on the other frame images by performing tracking of the region of interest set on one of the reference frame images among the plurality of frame images on the other frame images.

[0008] The program according to the present invention is Computers, An acquisition unit that acquires a motion image composed of multiple frame images obtained by motion imaging using radiation. A setting unit sets a predetermined region of interest for each of the plurality of frame images acquired by the acquisition unit. The generation unit functions as a unit that generates waveform information showing the change in the signal value of each pixel in the region of interest of the plurality of frame images set by the setting unit, The setting unit sets the region of interest in the other frame images by performing tracking of the region of interest set in one of the multiple frame images as a reference frame image on the other frame images. [Effects of the Invention]

[0009] According to the present invention, by performing tracking of the region of interest of a reference frame image on other frame images, a region of interest is set on the other frame images, so that a predetermined motion analysis can be performed using appropriate motion images. [Brief explanation of the drawing]

[0010] [Figure 1] This figure shows an example of a schematic configuration of the image acquisition system according to the first embodiment. [Figure 2] This flowchart shows an example of the operation of the motion analysis device when tracking a region of interest set in a reference frame image according to the first embodiment is performed on other frame images. [Figure 3] This figure shows an example of a reference frame image in which a region of interest is set according to the first embodiment. [Figure 4] This figure shows an example of a second frame image in which a region of interest has been set by tracking a template image set in the reference frame image according to the first embodiment. [Figure 5] This figure shows an example of a third frame image in which a region of interest has been set by tracking a template image set in the reference frame image according to the first embodiment. [Figure 6] This is a signal value change waveform showing the change in the signal value of a pixel in the region of interest of the motion image according to the first embodiment. [Figure 7] This flowchart shows an example of the operation of the motion analysis device when tracking a region of interest set on a reference frame image according to the second embodiment is performed on other frame images. [Figure 8]It is a flowchart showing an example of the operation of the control unit during the first process according to the second embodiment. [Figure 9] It is a diagram showing a signal value change waveform in which a reference frame waveform or the like according to the second embodiment is set. [Figure 10] It is a flowchart showing an example of the operation of the control unit during the second process according to the second embodiment. [Figure 11] It is a diagram showing a signal value change waveform in which a first frame waveform, a second frame waveform, a third frame waveform, and a fourth frame waveform are set within each respiratory cycle according to the second embodiment.

Embodiments for Carrying Out the Invention

[0011] Hereinafter, a dynamic image processing apparatus, a dynamic image processing method, and a program according to preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

[0012] <First Embodiment> [Configuration Example of Image Capturing System 100] FIG. 1 is a diagram showing an example of the schematic configuration of an image capturing system 100 according to the first embodiment. The image capturing system 100 includes a capturing device 1, a console 2, and a motion analysis device 3 which is an example of a dynamic image processing device. The capturing device 1, the console 2, and the motion analysis device 3 are communicably connected via a network N such as a LAN (Local Area Network). The communication method of the network N may be wired communication or wireless communication.

[0013] The imaging device 1 captures dynamic images of a predetermined area of ​​the subject M. The console 2 controls the radiography performed by the imaging device 1 and also controls the reading operation of the radiography images by the imaging device 1. The motion analysis device 3 performs predetermined motion analysis processing on the dynamic images transmitted from the console 2, etc. In this embodiment, before performing the motion analysis processing, the motion analysis device 3 performs preprocessing to reduce noise caused by motion fluctuations of the subject M in the region of interest of the dynamic image. The region of interest is called ROI (Region of Interest). Each device constituting the image acquisition system 100 conforms to the DICOM standard, and communication between each device is performed in accordance with the DICOM standard. DICOM is an abbreviation for Digital Image and Communications in Medicine.

[0014] [Example configuration of imaging device 1] The imaging device 1 can capture dynamic images of, for example, the morphological changes of lung expansion and contraction associated with respiratory movement, the beating of the heart, etc. Dynamic imaging refers to acquiring a series of images of a subject M by repeatedly irradiating it with pulsed radiation, such as X-rays, at predetermined time intervals in response to a single imaging operation. Repeatedly irradiating with pulsed radiation at predetermined time intervals is called pulsed irradiation. Alternatively, dynamic imaging refers to acquiring a series of images of a subject M by continuously irradiating it with a low dose rate without interruption in response to a single imaging operation. Continuously irradiating with radiation without interruption is called continuous irradiation. A series of images obtained by dynamic imaging is called a dynamic image. Each of the images that make up a dynamic image is called a frame image. Here, dynamic imaging includes video recording, but does not include still images taken while displaying video. Also, dynamic images include video, but do not include images obtained by taking still images while displaying video.

[0015] As shown in Figure 1, the imaging device 1 comprises a radiation source 11, a radiation irradiation control device 12, a radiation detection unit 13, and a reading control device 14. The radiation irradiation control device 12 and the reading control device 14 are connected via a communication cable or the like, and synchronize the radiation irradiation operation and the image reading operation by exchanging synchronization signals with each other. Note that the radiation detection unit 13 and the reading control device 14 may be configured as a single unit.

[0016] The radiation source 11 is positioned opposite the radiation detection unit 13, with the subject M in between. The radiation source 11 irradiates the subject M with radiation such as X-rays according to the control of the radiation irradiation control device 12. The radiation irradiation control device 12 is connected to the console 2. The radiation irradiation control device 12 controls the radiation source 11 to perform radiography based on the radiation irradiation conditions input from the console 2. The radiation irradiation conditions input from the console 2 include, for example, the pulse rate, pulse width, pulse interval, number of imaging frames per imaging, value of the X-ray tube current, value of the X-ray tube voltage, and type of additional filter. The pulse rate is the number of radiation irradiations per second and is the same as the frame rate, which will be described later. The pulse width is the radiation irradiation time per radiation irradiation. The pulse interval is the time from the start of one radiation irradiation to the start of the next radiation irradiation and is the same as the frame interval, which will be described later.

[0017] The radiation detection unit 13 is composed of a semiconductor image sensor such as an FPD (Flat Panel Detector). The FPD has a substrate made of glass or the like. Multiple detection elements, including pixels, are arranged in a matrix at predetermined positions on the substrate. The multiple detection elements detect radiation irradiated from the radiation source 11 that has passed through at least the subject M according to its intensity, and convert the detected radiation into an electrical signal for storage. Each pixel has a switching unit such as a TFT (Thin Film Transistor). FPDs can be of the indirect conversion type or the direct conversion type, and either type may be used. The indirect conversion type is a method in which radiation is converted into an electrical signal by a photoelectric conversion element via a scintillator. The direct conversion type is a method in which radiation is directly converted into an electrical signal.

[0018] The reading control device 14 is connected to the console 2. The reading control device 14 controls the switching unit of each pixel of the radiation detection unit 13 based on the image reading conditions input from the console 2. The reading control device 14 switches the reading of the electrical signals accumulated in each pixel of the radiation detection unit 13, and acquires image data by reading the electrical signals accumulated in the radiation detection unit 13. The image data is either a frame image of a moving image or a still image. If a structure exists between the radiation source 11 and the radiation detection unit 13, the amount of radiation reaching the radiation detection unit 13 decreases due to the structure. In this case, the signal value of each pixel of the image data changes according to the structure of the subject M. The signal value includes the pixel value, density value, etc. The reading control device 14 outputs the acquired moving image or still image to the console 2. The image reading conditions are, for example, the frame rate, frame interval, pixel size, image size, etc. The frame rate is the number of frames acquired per second and is the same as the pulse rate. The frame interval is the time from the start of one frame image acquisition operation to the start of the next frame image acquisition operation, and it coincides with the pulse interval.

[0019] [Example configuration for Console 2] Console 2 is comprised of a computer, such as a personal computer or workstation. As shown in Figure 1, Console 2 includes a control unit 21, a storage unit 22, an operation unit 23, a display unit 24, and a communication unit 25. The control unit 21, storage unit 22, operation unit 23, display unit 24, and communication unit 25 are connected by wiring such as a bus 26.

[0020] The control unit 21 includes a CPU (Central Processing Unit), RAM (Random Access Memory), etc. In response to the operation of the operation unit 23, the CPU 21 reads the system program and various processing programs stored in the memory unit 22, loads them into the RAM, and executes various processes according to the loaded programs. The control unit 21 centrally controls the operation of each part of the console 2, the radiation irradiation operation and reading operation of the imaging device 1.

[0021] The storage unit 22 is a non-volatile semiconductor memory, hard disk, etc. The storage unit 22 stores data such as various programs executed by the control unit 21, parameters necessary for executing processing by the programs, and processing results. The various programs are stored in the form of readable program code. The control unit 21 sequentially executes operations according to the program code.

[0022] The operation unit 23 includes a keyboard, mouse, etc. The operation unit 23 may also be a touch panel combined with the display screen of the display unit 24. The operation unit 23 receives various instructions from the user's input and outputs instruction signals corresponding to the received instructions to the control unit 21.

[0023] The display unit 24 is a monitor such as an LCD (Liquid Crystal Display). The display unit 24 displays input instructions and data from the operation unit 23 according to the instructions of the display signals input from the control unit 21.

[0024] The communication unit 25 includes a LAN adapter, modem, etc. The communication unit 25 transmits and receives signals, data, etc., to and from the imaging device 1, motion analysis device 3, etc., which are connected to the network N.

[0025] [Example configuration of Dynamic Analysis System 3] The dynamic analysis device 3 is used as a diagnostic support device to assist physicians in their diagnoses. The dynamic analysis device 3 is composed of a computer, such as a personal computer or workstation. As shown in Figure 1, the dynamic analysis device 3 comprises a control unit 31, a storage unit 32, an operation unit 33, a display unit 34, and a communication unit 35. The control unit 31, storage unit 32, operation unit 33, display unit 34, and communication unit 35 are connected by wiring on a bus 36.

[0026] The control unit 31 includes a CPU, RAM, etc. The CPU reads various programs P, such as system programs, stored in the memory unit 32 in response to operations on the operation unit 33, expands them into RAM, and executes various processes according to the expanded programs. The control unit 31 centrally controls the operation of each part of the dynamic analysis device 3.

[0027] The storage unit 32 includes non-volatile semiconductor memory, a hard disk, etc. The storage unit 32 stores data such as various programs P executed by the control unit 31, parameters necessary for executing the processing by programs P, and processing results. The various programs P are stored in the form of readable program code. The control unit 31 sequentially executes operations according to the program code.

[0028] The operation unit 33 includes a keyboard, mouse, etc. The operation unit 33 may also be a touch panel combined with the display screen of the display unit 24. The operation unit 33 receives various instructions from the user's input and outputs instruction signals corresponding to the received instructions to the control unit 31.

[0029] The display unit 34 has a monitor such as an LCD. The display unit 34 displays various information according to the instructions of the display signals input from the control unit 31. The communication unit 35 has a LAN adapter, modem, etc. The communication unit 35 sends and receives signals, data, etc. to and from the console 2, etc., which is connected to the network N.

[0030] The control unit 31 of the dynamic analysis device 3 functions as at least an acquisition unit, a setting unit, a generation unit, and an extraction unit. The control unit 31, which includes a processor, realizes the functions of the acquisition unit, setting unit, generation unit, and extraction unit by executing a program P stored in the storage unit 32, etc. The acquisition unit acquires a dynamic image consisting of multiple frame images obtained by dynamic imaging using radiation. The setting unit sets a predetermined region of interest for each of the multiple frame images acquired by the acquisition unit. Specifically, the setting unit sets a region of interest, which is the target observation area, in one of the multiple frame images that will serve as a reference frame image. The region of interest is a local area within the frame image. Hereinafter, the reference frame image will be referred to as the reference frame image.

[0031] Next, the setting unit sets the region of interest within other frame images by tracking the region of interest set in the reference frame image. This is because, during dynamic imaging, random body movement fluctuations occur due to unpredictable movements by the patient, coughing, poor breath-holding, etc., which can cause the region of interest to shift between frame images. Tracking the region of interest with respect to other frame images is a process performed to achieve high accuracy in dynamic analysis and is a pre-processing step executed before dynamic analysis. The generation unit generates signal value change waveforms (dose waveforms) as waveform information showing the change in signal value of each pixel in the region of interest of multiple frame images set by the setting unit. The extraction unit extracts frame images that contain dose fluctuations different from blood flow fluctuations and respiratory fluctuations included in the signal value change waveforms generated by the generation unit. For example, the extraction unit extracts noise caused by periodic or random body movements that could not be identified by tracking by the setting unit.

[0032] [Example of operation of image capture system 100] Figure 2 is a flowchart showing an example of the operation of the dynamic analysis device 3 when tracking a region of interest set in a reference frame image according to the first embodiment is performed on other frame images. The control unit 31 executes the program P stored in the storage unit 32 to realize each process, including the acquisition step, setting step, generation step, and extraction step. Hereinafter, the reference frame image will be referred to as the reference frame image.

[0033] First, let's explain the operation of console 2 during dynamic imaging. The control unit 21 of console 2 acquires image data of multiple frame images captured by the imaging device 1. The control unit 21 stores each acquired frame image in the storage unit 22, associating it with a frame number indicating the order of capture. Next, the control unit 21 displays the dynamic image composed of each acquired frame image on the screen of the display unit 24. The user checks whether the image is suitable for diagnosis. Based on the user's confirmation instruction, the control unit 21 adds patient information and examination information to the dynamic image and transmits the dynamic image with added patient information to the dynamic analysis device 3.

[0034] As shown in Figure 2, the control unit 31 of the motion analysis device 3 acquires motion images of a predetermined imaging area from the console 2 via the communication unit 35 (step S10). The imaging area is, for example, the front of the chest, as will be described later. The motion image consists of multiple frame images. The control unit 31 stores the acquired motion image in the storage unit 32.

[0035] The control unit 31 sets a predetermined region of interest in the reference frame image that constitutes the acquired dynamic image (step S11). Figure 3 is a diagram showing an example of a reference frame image G1 in which the region of interest R1 has been set according to the first embodiment. In Figure 3, the horizontal direction of the reference frame image G1 is the x direction and the vertical direction is the y direction. The control unit 31 uses the first frame image from among the multiple acquired frame images as the reference frame image G1. The control unit 31 sets the region of interest R1 within the reference frame image G1. For example, the control unit 31 sets the region of interest R1 near the pulmonary artery in the lung field, which is the target observation site. The area near the pulmonary artery is a part with a lot of blood flow and appears whitish in the dynamic image. Therefore, the control unit 31 can automatically set the region of interest R1 as a region in the lung field area of ​​the dynamic image where there are many pixels with high brightness values. Note that the setting of the region of interest R1 is not limited to automatic setting by the control unit 31. A user such as a radiologist may manually set the region of interest R1. In this case, for example, the display unit 34 may display an image of the lung field region that clearly shows the contrast between the areas that appear white due to blood flow and the other areas. The user can set the region of interest R1 by selecting the area near the pulmonary artery using the operation unit 33 in the image displayed on the display unit 34. Subsequently, the control unit 31 crops the image within the set region of interest R1 and sets the cropped image as the template image GT. In this embodiment, the template image GT is the same size as or approximately the same size as the region of interest R1.

[0036] Furthermore, the control unit 31 may set multiple regions of interest R within the reference frame image G1. For example, if only one region of interest R is set within the reference frame image G1, the movement may be breathing rather than body movement depending on where the region of interest R is set. In this case, tracking of the region of interest R between frame images is not necessarily performed in accordance with body movement. Therefore, the control unit 31 may set multiple regions of interest R within the reference frame image G1 and determine that tracking between frame images is based on body movement when the same movement is observed in many of the regions of interest R between frame images. By setting multiple regions of interest R in this way, it may be possible to determine body movement more accurately.

[0037] The control unit 31 performs tracking of the region of interest R1 of the reference frame image G1 on other frame images in the dynamic image, and sets the region of interest for the other frame images (step S12). As a method for identifying the region of interest from each frame image, template matching can be used, for example. Figure 4 shows an example of a second frame image G2 in which the region of interest R2 has been set by tracking the template image GT set on the reference frame image G1. Figure 5 shows an example of a third frame image G3 in which the region of interest R3 has been set by tracking the template image GT set on the reference frame image G1. In Figures 4 and 5, the horizontal direction of the reference frame image G1 is the x direction and the vertical direction is the y direction.

[0038] First, the control unit 31 sets a region of interest R2 for the second frame image G2 using the template image GT set in the reference frame image G1. As shown in Figure 4, the control unit 31 shifts the template image GT in the frame image G2 one pixel at a time in the x direction, starting from the upper left edge of the frame image G2. When the scanning of the template image GT reaches the right edge of the frame image G2, the control unit 31 shifts the template image GT one pixel in the y direction, and then shifts it one pixel at a time in the x direction. In this way, the control unit 31 compares the template image GT with the entire frame image G2 to identify the position in the frame image G2 that has the highest similarity to the template image GT. The control unit 31 sets the identified position as the region of interest R2 in the frame image G2.

[0039] The position within frame image G2 that has the highest similarity to template image GT can be calculated using the following formula (1). In formula (1) below, a smaller SSD (Sum of Squared Difference) value indicates a higher similarity between the two images.

[0040]

number

[0041] Alternatively, the position within frame image G2 that has the highest similarity to template image GT may be calculated using the following equation (2). In equation (2) below, a smaller value of SAD (Sum of Absolute Difference) indicates a higher similarity between the two images. Equation (2) does not use the squared error, so it can tolerate some abnormal differences in pixel values.

[0042]

number

[0043] As shown in Figure 4, the control unit 31 identifies a position diagonally to the upper right of the position of region of interest R1 set in the reference frame image G1 as the position with the highest similarity to the template image GT. The region of interest R1 in the reference frame image G1 can be said to have moved diagonally to the right relative to the reference line A of the initial reference frame image G1, from the reference frame image G1 to the frame image G2, due to the patient's body movement. Therefore, the control unit 31 sets the position diagonally to the upper right of the region of interest R1 in the reference frame image G1 as the region of interest R2 in the frame image G2.

[0044] Next, the control unit 31 identifies the region of interest R3 within the third frame image G3. As described above, the control unit 31 compares the template image GT with the entire frame image G3. As shown in Figure 5, the control unit 31 identifies the position diagonally to the upper left of the position of the region of interest R1 set in the reference frame image G1 as the position with the highest similarity to the template image GT. The position with the highest similarity to the template image GT can be identified by the above equation (1) or equation (2). The region of interest R1 in the reference frame image G1 can be said to have moved diagonally to the upper left of the reference frame image G1 relative to the reference line A of the reference frame image G1 from the reference frame image G1 to the frame image G3 due to the patient's body movement. Therefore, the control unit 31 sets the position diagonally to the upper left of the region of interest R1 in the reference frame image G1 as the region of interest R3 in the frame image G3.

[0045] In addition to template matching, techniques such as extracting feature points from frame images can be used to identify regions of interest within each frame image. Specifically, the control unit 31 extracts feature points from the first reference frame image G1 that constitutes the dynamic image and sets the extracted feature points as the region of interest R1. Similarly, the control unit 31 extracts feature points from other frame images G2, etc., that constitute the dynamic image. The control unit 31 matches the feature points of the reference frame image G1 with the feature points extracted from the other frame images, extracts feature points with high similarity from each of the other frame images, and sets the extracted feature points as the region of interest. This allows the control unit 31 to track regions of interest between each frame image.

[0046] The control unit 31 generates a signal value change waveform that shows the change in the signal value of each pixel within the region of interest for all image frames (step S13). Figure 6 is a signal value change waveform showing the change in the signal value of pixels in the region of interest R of a motion image according to the first embodiment. In Figure 6, the vertical axis is the signal value of the pixel, and the horizontal axis is time. The signal value change waveform is, for example, a graph obtained by averaging the signal values ​​of each pixel in the region of interest R. The signal value change waveform includes at least respiratory fluctuations associated with inhalation and exhalation in the subject M and blood flow fluctuations associated with the beating of the heart (heartbeat).

[0047] Let's explain respiratory variability. During the inspiratory time from maximum expiratory to maximum inhalation, air flows into the lung field. Maximum expiratory position is the moment when the maximum amount of air has been exhaled from the lung field. Maximum inspiratory position is the moment when the maximum amount of air has been taken into the lung field. In this case, the amount of X-ray transmission in the lung field region increases, and the signal value of the pixels in the region of interest R increases from the maximum expiratory position to the maximum inspiratory position. On the other hand, during the expiratory period from maximum inhalation to maximum expiratory, air flows out of the lung field. In this case, the amount of X-ray transmission in the lung field region decreases, and the signal value of the pixels in the region of interest R of the dynamic image decreases from maximum inhalation to maximum expiratory position. Therefore, as shown in Figure 6, respiratory variability is a waveform that gradually shifts between the maximum expiratory position and the maximum inspiratory position in accordance with the patient's inhalation and exhalation.

[0048] Next, let's discuss blood flow fluctuations. When the heart is in ventricular diastole, less blood flows into the lung field. In this case, the amount of X-ray transmission in the pulmonary artery increases, and the signal value of each pixel in the region of interest R of the dynamic image also increases. On the other hand, when the heart is in ventricular systole, a large amount of blood flows from the heart into the lung field via the pulmonary artery. Therefore, the amount of X-ray transmission in the lung field decreases, and the signal value of each pixel in the region of interest R of the dynamic image also decreases. As a result, blood flow fluctuations appear as a waveform that repeatedly increases and decreases in signal value in accordance with the heartbeat, as shown in Figure 6, and are superimposed on the waveform of respiratory fluctuations.

[0049] The control unit 31 uses the generated signal value change waveform to perform dynamic analysis processing according to the objective (step S14). For example, if the region of interest R is the pulmonary artery, the control unit 31 calculates and analyzes the amount of signal value change or the rate of signal value change of the pulmonary artery to calculate features that serve as indicators of pulmonary circulating blood volume, etc. If the region of interest R is the heart, the control unit 31 calculates and analyzes the amount of signal value change or the rate of signal value change of the heart to calculate feature quantities that serve as indicators of cardiac function, etc.

[0050] The control unit 31 displays the generated signal value change waveform and dynamic analysis results on the screen of the display unit 34 (step S15). Note that the signal value change waveform and dynamic analysis results may be displayed on a device other than the display unit 34 of the dynamic analysis device 3. For example, the signal value change waveform may be displayed on a display device such as the display unit 24 of the console 2.

[0051] According to the first embodiment, by performing tracking of the region of interest R1 of the reference frame image G1 on other frame images G2, etc., the region of interest R2, etc. is set on the other frame images G2, etc. As a result, even if the region of interest R2, etc. moves due to the patient's body movements such as coughing in other frame images G2, etc., it is possible to follow the patient's movements and set the region of interest R2, etc. on the expected target observation area. In other words, a mismatch of the target observation area can be prevented in each frame image. This makes it possible to reduce noise caused by the patient's body movements, etc. in each frame image of the motion image before the motion analysis processing. As a result, since the predetermined motion analysis processing can be performed using appropriate motion images, accurate motion analysis processing results can be obtained.

[0052] <Second Embodiment> In the second embodiment, in addition to tracking the region of interest in each frame image as described in the first embodiment, frame waveforms containing random and periodic noise are extracted using signal value change waveforms based on the region of interest. The following description will focus on the differences from the first embodiment, with the same reference numerals used for components substantially common to both embodiments, and common descriptions omitted.

[0053] [Example of operation of image capture system 100] Figure 7 is a flowchart showing an example of the operation of the dynamic analysis device 3 when tracking a region of interest set on a reference frame image according to the second embodiment is performed on other frame images. The control unit 31 executes the program P stored in the storage unit 32 to realize each process, including the acquisition step, setting step, generation step, and extraction step.

[0054] As shown in Figure 7, the control unit 31 of the motion analysis device 3 acquires motion images of a predetermined imaging area from the console 2 via the communication unit 35 (step S20). Next, the control unit 31 sets a region of interest within the reference frame image that constitutes the acquired motion image (step S21).

[0055] The control unit 31 performs tracking of the region of interest of the reference frame image for all frame images other than the reference frame image in the motion image, and sets the region of interest for the other frame images (step S22). Next, as shown in Figure 6, the control unit 31 generates a signal value change waveform that shows the change in the signal value of each pixel within the region of interest for all image frames (step S23).

[0056] Before the motion analysis process, one of the first, second, and third processes is executed on the generated signal value change waveform according to the analysis purpose (step S24). For example, the user may select a process suitable for the purpose of analyzing the motion image from the items of the first to third processes displayed on the screen of the display unit 34 by operating the operation unit 33. Alternatively, the control unit 31 may automatically acquire a process suitable for the purpose of analyzing the acquired motion image based on information such as the shooting area and region of interest. Here, the first process is a process for extracting a frame waveform that includes fluctuations corresponding to random body movements from the signal value change waveform. The second process is a process for extracting a period that is less affected by periodic noise from the signal value change waveform. The third process is a process for extracting a frame that includes body movements based on a reference frame when the region of interest R is the entire image.

[0057] If the process branches to the first process in step S24, the control unit 31 executes the first process on the acquired dynamic image (step S25). In this case, the control unit 31 transitions to the subroutine shown in Figure 8. Figure 8 is a flowchart showing an example of the operation of the control unit 31 during the first process according to the second embodiment. As shown in Figure 8, the control unit 31 sets a reference frame waveform in the signal value change waveform of the region of interest in each frame image of the dynamic image (step S100). Figure 9 is a diagram showing the signal value change waveform with the reference frame waveform FS etc. set according to the second embodiment. The reference frame waveform FS may be composed of, for example, multiple frame images at and around the maximum expiratory position, or multiple frame images at and around the maximum inspiratory position. This is because the frame images at the maximum expiratory position and maximum inspiratory position are least affected by respiratory fluctuations, and when used in dynamic analysis processing, appropriate dynamic analysis results can be obtained. In the second embodiment, the reference frame waveform FS is set using multiple frame images at and around the maximum expiratory position. The reference frame waveform FS is set to include, for example, two heartbeats' worth of peaks due to blood flow fluctuations. In Figure 9, the range including the reference frame waveform FS is shown by a dotted-dotted rectangular frame. The control unit 31 may set the reference frame waveform FS according to the type of dynamic analysis being performed.

[0058] The control unit 31 sets the comparison frame waveform to be compared with the reference frame waveform FS in the signal value change waveform (step S101). The control unit 31 may, for example, set the comparison frame waveforms Fa, etc. in order by moving the rectangular frame of the reference frame waveform FS along the time direction of the signal value change waveform. Specifically, if the reference frame waveform FS is 50 to 60 frames, the comparison frame waveforms Fa, etc. can be set in order by moving it every 5 frames, for example. In this case, the comparison frame waveform Fa is 55 to 65 frames. Note that the number of frames to move is not limited to 5 frames, and may be, for example, 1 frame. In Figure 9, the range including the comparison frame waveforms Fa, Fb, etc. is shown by a dashed rectangular frame. Note that the number of comparison frame waveforms to set is not limited to the number shown in Figure 9. Alternatively, the user may manually set the reference frame waveform FS, comparison frame waveform Fa, etc. while checking the screen of the display unit 34.

[0059] The control unit 31 sequentially determines whether the reference frame waveform FS and the comparison frame waveform Fa, etc., match (step S102). Specifically, the control unit 31 compares the reference frame waveform FS and the comparison frame waveform Fa, etc., and determines the degree of similarity between these frame waveforms. The control unit 31 may determine the degree of similarity with the comparison frame waveform Fa, etc., using, for example, the number of peaks or signal values ​​of the reference frame waveform FS. For example, when the control unit 31 determines the degree of similarity using signal values, it can determine that the similarity between the reference frame waveform FS and the comparison frame waveform is high when the amplitude of the comparison frame waveform is in the range of 90 to 110% with the amplitude of the reference frame waveform FS being 100%. Furthermore, the conditions for determining similarity may be other conditions besides the number of peaks or signal value width of the reference frame waveform FS, such as a cross-correlation function that utilizes the entire signal value waveform.

[0060] Specifically, when the comparison target is the comparison frame waveform Fa with the reference frame waveform FS, the similarity is determined as follows. As shown in Figure 9, the number of peaks in the reference frame waveform FS and the number of peaks in the comparison frame waveform Fa are both 2 within the rectangular frame. Therefore, the control unit 31 can determine that the similarity between the reference frame waveform FS and the comparison frame waveform Fa is high. In this case, the control unit 31 determines that the reference frame waveform FS and the comparison frame waveform Fa are identical and proceeds to step S104.

[0061] When the comparison target is the comparison frame waveform Fb with the reference frame waveform FS, the similarity is determined as follows. As shown in Figure 9, the reference frame waveform FS has 2 peaks within the rectangular frame, while the number of peaks in the comparison frame waveform Fb is unknown within the rectangular frame. Therefore, the control unit 31 can determine that the similarity between the reference frame waveform FS and the comparison frame waveform Fb is low. The control unit 31 extracts the comparison frame waveform Fb as a frame waveform that includes the patient's body movements, etc. In this case, the control unit 31 determines that the reference frame waveform FS and the comparison frame waveform Fa do not match and proceeds to step S103.

[0062] The control unit 31 generates analysis-unsuitable information for comparison frame waveforms Fb, etc., that do not match the reference frame waveform FS, indicating that they are unsuitable for dynamic analysis processing (step S103). Specifically, when the dynamic image consists of 100 frames, and the 80th to 90th frames contain noise due to body movement fluctuations, the processing is performed as follows. In this case, the control unit 31 generates analysis-unsuitable information for the 80th to 90th frames and adds the generated analysis-unsuitable information to each of the 80th to 90th frames. After generating the analysis-unsuitable information, the control unit 31 proceeds to step S104.

[0063] The control unit 31 determines whether the comparison of all set comparison frame waveforms Fa, etc. has been completed (step S104). If the control unit 31 determines that the comparison of all set comparison frame waveforms Fa, etc. has not been completed, it returns to step S102. The control unit 31 moves the comparison target with the reference frame waveform FS to an adjacent comparison frame waveform, etc., and repeatedly executes the comparison process of the reference frame waveform FS as described above. On the other hand, if the control unit 31 determines that the comparison with all set comparison frame waveforms Fa, etc. has been completed, it proceeds to step S28 shown in Figure 7.

[0064] If the process branches to the second process in step S24, the control unit 31 executes the second process on the acquired motion image (step S26). In this case, the control unit 31 transitions to the subroutine shown in Figure 10. Figure 10 is a flowchart showing an example of the operation of the control unit 31 during the second process according to the second embodiment.

[0065] The control unit 31 sets multiple frame waveforms within each respiratory cycle in the signal value change waveform (step S200). Figure 11 is a diagram showing the signal value change waveform in which a first frame waveform F1, a second frame waveform F2, a third frame waveform F3, and a fourth frame waveform F4 are set within each respiratory cycle according to the second embodiment. In the first respiratory cycle C1, the control unit 31 sets the first frame waveform F1 during the maximum inspiratory period, the second frame waveform F2 during the expiratory period, the third frame waveform F3 during the maximum expiratory period, and the fourth frame waveform F4 during the inspiratory period. In the second respiratory cycle C2 and beyond, the control unit 31 sets the first frame waveform F1, the second frame waveform F2, the third frame waveform F3, and the fourth frame waveform F4 in the same manner as in the first respiratory cycle C1.

[0066] Here, the first frame waveform F1 is composed of multiple frame images during the maximum inspiratory period. The second frame waveform F2 is composed of multiple frame images at approximately the midpoint between the maximum inspiratory position and the maximum expiratory position. The third frame waveform F3 is composed of multiple frame images during the maximum expiratory period. The fourth frame waveform F4 is composed of multiple frame images at approximately the midpoint between the maximum expiratory position and the maximum inspiratory position. Note that the number of frame waveforms to be set is not limited to those shown in Figure 11. Furthermore, the setting position of the frame waveform is not limited to those shown in Figure 11, and can be set to any position (period) of the signal value change waveform.

[0067] The control unit 31 compares frame waveforms within the same period set for each respiratory cycle. Based on the comparison results, the control unit 31 determines whether or not there is an abnormality in any of the multiple frame waveforms within each respiratory cycle (step S201). Specifically, as shown in Figure 11, the control unit 31 compares the first frame waveform F1, the second frame waveform F2, the third frame waveform F3, and the fourth frame waveform F4, which are set for each n respiratory cycles. n is a positive integer. The control unit 31 may also determine the similarity between each frame waveform based on the number of peaks in each frame waveform, the width of the waveform signal values, etc.

[0068] If the first frame waveform F1 of the first respiratory cycle C1 does not contain any frame waveforms with low similarity to the corresponding frame waveforms of other respiratory cycles, the control unit 31 determines that the first respiratory cycle C1 does not contain periodic noise. The control unit 31 performs the same processing on other respiratory cycles as it did on the first respiratory cycle C1. If no periodic noise is found in any respiratory cycle, the control unit 31 determines that there are no abnormalities in any respiratory cycle. In this case, the control unit 31 proceeds to step S28 in Figure 7.

[0069] On the other hand, if the first frame waveform F1 of the first respiratory cycle C1 contains a frame waveform that has low similarity to the corresponding frame waveform of another respiratory cycle, the control unit 31 determines that the first respiratory cycle C1 contains periodic noise. The control unit 31 performs the same processing on other respiratory cycles as it did on the first respiratory cycle. If periodic noise is found in at least one respiratory cycle, the control unit 31 determines that there is an abnormality in one of the respiratory cycles. In this case, the control unit 31 extracts the respiratory cycle containing the periodic noise and proceeds to step S202.

[0070] The control unit 31 generates analysis-unsuitable information for the frame waveforms of the extracted respiratory cycles that have abnormalities, indicating that they are unsuitable for dynamic analysis processing (step S202). For example, the control unit 31 may extract respiratory cycles with less periodic noise by adding analysis-unsuitable information to all frame waveforms of the identified respiratory cycles. Once the control unit 31 has generated the analysis-unsuitable information, it proceeds to step S28 in Figure 7.

[0071] If the process branches to the third process in step S24, the control unit 31 performs the third process on the acquired motion images (step S27). Specifically, the control unit 31 determines a frame image from a normal location that is assumed not to contain body motion, among the signal value waveforms when the region of interest R of each frame is considered as the overall image, as the reference frame image. The control unit 31 calculates the similarity between each frame of a specific number of frames to be used for motion analysis and the reference frame image. The similarity can be determined using signal values, etc., as described above. Based on the similarity comparison results, the control unit 31 determines that frame images with low similarity that exceed a threshold are abnormal frame images containing noise due to body motion, and extracts the frame images with low similarity. The control unit 31 may discard the extracted frame images, or it may add information that makes the frame images unanalyzable to the extracted frame images as described above.

[0072] The control unit 31 uses the generated signal value change waveform to perform motion analysis processing according to the purpose (step S28). If the first and second processes have been performed, the control unit 31 performs motion analysis processing on frame images in which no unanalyzable information has been added to the motion image. In other words, the control unit 31 performs motion analysis processing on frame images in which noise caused by patient movement, etc., is not included.

[0073] The control unit 31 displays the generated signal value change waveform and the dynamic analysis results on the screen of the display unit 34 (step S29). For example, when the control unit 31 has executed the first and second processes, it displays the results of the dynamic analysis process performed on frame images that do not have analysis-unavailable information attached on the screen of the display unit 34. At this time, the control unit 31 may also display a pop-up message on the screen of the display unit 34 indicating that frame images with analysis-unavailable information attached are not used for dynamic analysis processing.

[0074] According to the second embodiment, the same effects as the first embodiment can be achieved. Specifically, noise caused by patient body movements, etc., in each frame of the motion image can be reduced at the timing before motion analysis processing. As a result, a predetermined motion analysis can be performed using appropriate motion images, and accurate motion analysis results can be obtained. Furthermore, according to the second embodiment, frame images containing noise due to random or periodic body movements are further eliminated using signal value change waveforms based on the region of interest from which noise such as body movements has been reduced. As a result, noise such as body movements that could not be extracted by tracking in the first embodiment can be extracted, and highly accurate motion images can be obtained.

[0075] Although preferred embodiments of this disclosure have been described in detail above with reference to the attached drawings, the technical scope of this disclosure is not limited to these examples. Furthermore, various modifications and improvements naturally fall within the technical scope of this disclosure, within the scope of the technical ideas described in the claims, as would be expected by those skilled in the art.

[0076] For example, in the above embodiment, the motion analysis device 3 performed the process of extracting noise such as random fluctuations in the patient's body movement included in the motion image, but it is not limited to this. For example, the console 2 may function as a motion image processing device and perform actions such as tracking the region of interest of a reference frame image on other frame images. Alternatively, an information processing device such as a client terminal may function as a motion image processing device and perform actions such as tracking the region of interest of a reference frame image on other frame images. [Explanation of symbols]

[0077] 3. Dynamic Analysis Device (Dynamic Image Processing Device) 31 Control Unit (Acquisition Unit, Setting Unit, Generation Unit, Extraction Unit) G1 Reference Frame Image G2, G3 Other frame images R1, R2, R3 Areas of Interest

Claims

1. An acquisition unit that acquires a motion image composed of multiple frame images obtained by motion imaging using radiation, A setting unit sets a predetermined region of interest for each of the plurality of frame images acquired by the acquisition unit, The system includes a generation unit that generates waveform information showing the change in the signal value of each pixel in the region of interest of the plurality of frame images set by the setting unit, The setting unit sets the region of interest in the other frame images by performing tracking of the region of interest set in one of the multiple frame images as a reference frame image on the other frame images. Dynamic image processing device.

2. The region of interest is a local region within the frame image. The motion image processing apparatus according to claim 1.

3. If the area where the dynamic image is captured is the lung field, the region of interest is the pulmonary artery. The motion image processing apparatus according to claim 2.

4. The system includes an extraction unit that extracts a frame image containing dose fluctuations different from blood flow fluctuations and respiratory fluctuations included in the waveform information generated by the generation unit. The motion image processing apparatus according to claim 1.

5. An acquisition step to acquire a motion image consisting of multiple frame images obtained by motion imaging using radiation, A setting step of setting a predetermined region of interest for each of the acquired multiple frame images, The process includes a generation step of generating waveform information that shows the change in the signal value of each pixel in the region of interest of the set plurality of frame images, In the setting step, the region of interest set in one of the multiple frame images is tracked on the other frame images, thereby setting the region of interest on the other frame images. A method for processing motion images.

6. Computers, An acquisition unit that acquires a motion image composed of multiple frame images obtained by motion imaging using radiation. A setting unit sets a predetermined region of interest for each of the plurality of frame images acquired by the acquisition unit. The generation unit functions as a unit that generates waveform information showing the change in the signal value of each pixel in the region of interest of the plurality of frame images set by the setting unit, The setting unit sets the region of interest in the other frame images by performing tracking of the region of interest set in one of the multiple frame images as a reference frame image on the other frame images. program.

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