Medical imaging device with biological signal processing system, medical imaging system, and biological signal processing method

Abstract

To provide a medical image pickup apparatus capable of accurately and automatically setting an area of interest for acquiring biological information, on the basis of a biological information signal obtained in a non-contact manner from a subject put in an examination space.SOLUTION: A signal analysis part 310 of a medical image pickup apparatus selects an area of interest for acquiring a subject's movement, among a plurality of areas, by using a biological information signal in each of the plurality of areas included in a predetermined range, among signals measured by a biological information measurement device. The subject's movement is calculated by using the biological information signal measured by the biological information measurement device from the selected area of interest.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technique for acquiring biological information of a subject under examination using an examination device such as a medical imaging device, and providing the information to the medical imaging device. [Background technology]

[0002] When examining subjects (often patients) using medical imaging devices such as MRI (Magnetic Resonance Imaging), imaging synchronized with the subject's pulsation and respiratory movements is widely used to reduce the effects of artifacts caused by these movements. The subject's pulsation and respiratory movements are usually monitored by attaching measuring devices such as an electrocardiograph or a respiratory balloon to the subject during the examination, and the imaging is controlled by inputting signals from the measuring devices into the imaging device. Furthermore, if respiratory movements can be accurately determined, it is possible to correct the measurement data and images using these movements.

[0003] However, measurement devices such as respiratory balloons require preparation for setting them on the patient, and there are cases where respiratory movement cannot be detected accurately due to the setting method and individual differences in the subject.

[0004] In contrast, a widely used technique for MRI devices is to collect signals from moving parts of the body, such as the diaphragm, to detect respiratory movement. However, this technique inevitably requires longer imaging times because navigation echoes are generated and collected separately from the nuclear magnetic resonance signals used to form images.

[0005] Meanwhile, Patent Document 1 discloses a camera system that automatically measures physiological parameters such as pulse and respiratory movement of a subject, and describes applying this camera system to an MRI device to automatically measure physiological parameters during an examination using the MRI device. In this camera system, before the subject is transported into the bore (examination space) of the examination device, a digital camera installed outside the bore measures biometric parameters of the subject, and a predetermined range of the subject is determined. After that, a camera installed distal to the entrance side photographs the predetermined range of the subject transported into the bore, and a region of interest is determined using the biometric parameters, and physiological parameters are calculated from photographic data of the region of interest. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Patent No. 6714006 Specification DISCLOSURE OF THE INVENTION [Problem to be solved by the invention]

[0007] As mentioned above, in order to obtain physiological information (movement information) such as respiratory movement and pulsation from a subject without contact, it is important to set a region of interest that best reflects that information. Setting the region of interest correctly is particularly essential when performing respiratory-gated imaging. However, Patent Document 1 describes determining the region of interest based on biometric parameters, specifically the distance between the subject's sternum and right clavicle. However, if the region of interest is determined solely based on biometric parameters such as the subject's size, the region of interest may be too large, or if the region of interest is too small, it may be misaligned, and appropriate setting of the region of interest is not guaranteed. Furthermore, the technology described in Patent Document 1 requires a camera installed outside the bore in addition to a camera capturing the area including the region of interest in order to obtain the biometric parameters. In other words, two cameras are required.

[0008] The present invention solves the problems of the conventional technology described above, and aims to provide a technology that can accurately and automatically set a region of interest for acquiring biometric information based on biometric information signals obtained non-contact from a subject placed in an examination space, thereby enabling efficient capture of medical images using biometric information (movement information) and reducing the time and effort required by doctors, technicians, etc. [Means for solving the problem]

[0009] In order to solve the above problems, the medical imaging apparatus of the present invention is provided with a biological signal processing system, which is installed in or near the examination space of the medical imaging apparatus and includes a non-contact biological information measurement unit that measures the state of a subject during examination, and a signal analysis unit that processes the biological information signals measured by the biological information measurement unit and calculates the subject's movement. The biological information measurement unit acquires the biological information signals from a predetermined area of ​​the subject, and the signal analysis unit has a region-of-interest selection unit that uses the biological information signals from each of a plurality of areas included in the predetermined area to select a region of interest from the plurality of areas from which the subject's movement should be acquired, and calculates the subject's movement using the biological information signals measured from the region of interest selected by the region-of-interest selection unit.

[0010] A medical imaging system according to the present invention includes an inspection device, a biological signal processing system including the biological information measuring unit and signal analyzing unit described above, and a device for displaying a GUI.

[0011] Furthermore, the biosignal processing method of the present invention is a biosignal processing method that is installed within or near the examination space of an examination device, processes bioinformation signals of a subject under examination measured by a non-contact bioinformation measuring device, and calculates the movement of the subject, and includes the steps of generating bioinformation signals for each of a plurality of regions using bioinformation signals measured from a predetermined range of the subject, calculating an index related to the intensity of noise or movement for each of the bioinformation signals of the plurality of regions, and selecting a region of interest of the subject for which movement is to be calculated based on the index. [Effects of the Invention]

[0012] According to the present invention, a position or area where the bio-information measuring device can accurately capture the subject's movement can be set as a region of interest, and by processing the bio-information signal collected from the region of interest, the subject's movement can be collected with high accuracy. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a diagram showing an overview of a biological signal processing system according to the present invention and a medical imaging system including the biological signal processing system; [Figure 2] FIG. 2 is a diagram showing an example of a biological information signal. [Figure 3] FIG. 2 is a block diagram showing the configuration of a signal analysis unit according to the first embodiment. [Figure 4] FIG. 2 is a diagram showing an example of the installation position of a camera in an inspection device. [Figure 5] 10A and 10B are diagrams showing other examples of camera installation positions in an inspection device. [Figure 6] FIG. 2 is a diagram showing the flow of operations of the biological signal processing system according to the first embodiment. [Figure 7] FIG. 4 is a diagram showing an example of an analysis result by a signal analysis unit according to the first embodiment. [Figure 8] 4A and 4B are diagrams for explaining selection of a region of interest by a region of interest selection unit according to the first embodiment. [Figure 9] FIG. 10 is a diagram illustrating an example of selecting a region of interest using an index. [Figure 10] FIG. 10 is a diagram for explaining the arrangement of cameras according to the second embodiment. [Figure 11] FIG. 10 is a diagram showing the configuration of a signal processing device according to a third embodiment. [Figure 12] FIG. 10 is a diagram showing the flow of operations of the biological signal processing system of the third embodiment. [Figure 13] FIG. 10 is a diagram showing an example of an index (time series change) when an abnormality occurs. [Figure 14] (A) and (B) are diagrams showing examples of indicators (two types of time series changes) when an abnormality occurs. DETAILED DESCRIPTION OF THE INVENTION

[0014] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of a biological signal processing system and a medical imaging system including the biological signal processing system according to the present invention will be described with reference to the accompanying drawings.

[0015] As shown in FIG. 1, the medical imaging system 10 mainly comprises an inspection device 100 and a biological information measuring device. (Hereinafter referred to as biosignal measuring device) The inspection device 100 includes a medical imaging device such as an MRI device, a CT device, or a PET device, and is capable of performing imaging using biological information measured by the biological signal measuring device 200. Specifically, the inspection device (hereinafter referred to as imaging device) 100 performs synchronized imaging using biological information such as pulsation and respiratory movement, and correction of measurement data using the biological information.

[0016] The biosignal measuring device 200 is a device that acquires bioinformation from a subject under examination using the imaging device 100 in a non-contact manner. It is composed of a camera, a distance sensor for electromagnetic waves such as infrared or millimeter waves, or ultrasound (hereinafter collectively referred to as the sensor), and detects information such as the distance between the sensor and the subject and the subject's movement, and outputs this as a bioinformation signal. When the sensor is a camera, the video data (time-series image data) captured by the camera over a predetermined range of the subject is the primary bioinformation signal, and bioinformation (secondary bioinformation signal) representing changes in pixel values ​​and pixel positions over time is generated. Furthermore, measuring devices that use electromagnetic waves or ultrasound include a source that generates electromagnetic waves such as millimeter waves or ultrasound and a receiver that receives the reflected waves. The reflected waves from a predetermined range of the subject are processed to generate a bioinformation signal for each position within the predetermined range.

[0017] The signal processing device 300 performs various processes using the biological information signal output by the biological signal measuring device 200 to determine a region of the subject (region of interest) from which biological information (movement of the subject) to be provided to the imaging device 100 is to be acquired. For this purpose, the signal processing device 300 includes a signal analysis unit 310. The signal analysis unit 310 includes a biological information calculation unit 311 that calculates biological information for each of a plurality of positions or regions within a predetermined range from the biological information signal sent from the biological signal measuring device 200, a region of interest selection unit 313 that analyzes the biological information for each position or region and determines the position or region from which the most accurate biological information can be obtained, and an index calculation unit 312 that calculates an index related to noise and intensity of the biological information.

[0018] The signal processing device 300 may be a signal processing device associated with the imaging device 100 that processes measurement signals and image signals within the imaging device 100, or it may be an independent device that processes signals from the biosignal measuring device 200. Here, a system including the biosignal measuring device 200 and the signal analysis unit 310 of the signal processing device 300 is referred to as the biosignal measuring system 20. The functions of the signal processing device 300, including the signal analysis unit 310, are realized by a computer equipped with a memory and a processing unit such as a CPU or GPU that loads an analysis program. However, some or all of the functions of the signal processing device 300 may also be realized by hardware such as an ASIC, and such cases are also encompassed by this embodiment. Although not required, the computer that realizes the functions of the signal processing device 300 may, like a general computer, be equipped with a display 400 for displaying processing results and a GUI, input devices such as a pointing device and a keyboard, a storage device for storing the above-mentioned analysis program, processing results, and data required for processing, etc. The display 400 that displays the GUI may also be equipped in the imaging device 100.

[0019] The specific content of the bio-information signal will be described later, but when the bio-information is a periodic movement such as the subject's pulsation or breathing, the secondary bio-information signal will be a periodic signal with a predetermined amplitude as shown in Figure 2. The subject region from which the bio-information signal as shown in Figure 2 can be obtained is limited to a relatively narrow range, and even within that range, there are areas where the noise is large and the periodicity is difficult to determine, or areas where the signal amplitude is small and difficult to determine. Therefore, if the bio-information signal is obtained as the average of these areas, the accuracy of the bio-information will be degraded. Furthermore, the optimal region for acquiring the bio-information signal varies from person to person, and determining the optimal region from landmarks on the subject does not necessarily result in an accurate bio-information signal.

[0020] The biosignal measurement system 20 of this embodiment first determines the optimum position of the subject (region of interest) for obtaining bioinformation using the bioinformation signals measured by the biosignal measurement device 200, and then calculates the bioinformation using the bioinformation signals obtained from the determined region of interest. To determine the region of interest, indices related to noise and movement intensity are calculated using the bioinformation signals obtained from multiple regions. Based on the calculated one or more indices, a region with low noise and high movement intensity is selected from the multiple regions and used as the region of interest. There are various methods for determining the size and division of the multiple regions, and the number of regions of interest selected is not limited to one, but may be two or more.

[0021] Hereinafter, an embodiment will be described in which the imaging device 100 is an MRI device and the sensor of the biological signal measuring device 200 is a camera 210.

[0022] <Embodiment 1> In this embodiment, the sensor of the biosignal measuring device 200 is a single camera, which acquires a video signal as a primary bioinformation signal and calculates a signal representing a positional variation obtained from the optical flow of the image as a secondary bioinformation signal. The overall configuration of the device is similar to that shown in Fig. 1. Fig. 3 shows details of the signal analysis unit 310. In Fig. 3, elements having the same functions as those shown in Fig. 1 are designated by the same reference numerals.

[0023] As shown in the figure, the signal analysis unit 310, as the biological information calculation unit 311 in FIG. 1, includes an optical flow calculation unit 311A ​​that receives a video signal (primary biological information signal) from the sensor (camera) 210, calculates an optical flow from image data of two or more temporally adjacent frames, and calculates fluctuations in the subject position for each pixel or subpixel. The index calculation unit 312 calculates an index representing noise or the intensity of movement in the biological information signal for each pixel or subpixel generated by the optical flow calculation unit 311A. The index calculation unit 312 calculates, for example, band power as an index of the intensity of movement. For this purpose, the index calculation unit 312 includes an FFT unit 312A that converts biological signal information into frequency information. The region of interest selection unit 313 uses the index calculated by the index calculation unit 312 to determine a region (region of interest) from which a highly accurate biological information signal can be collected.

[0024] For example, as shown in FIG. 4, in the case of an apparatus in which the examination apparatus 100 has a long, thin cylindrical bore 101 as an examination space, such as an MRI apparatus, and the subject 103 is placed on a table 102 and placed in the examination space, the camera 210 is installed at the end of the bore 101, in a position that captures the subject 103 obliquely from above, thereby obtaining an image of a relatively wide range including the subject's chest. Note that FIG. 4 shows an example in which the camera 210 is installed at the entrance side where the subject is inserted into the bore, but as shown in FIGS. 5(A) and 5(B), it is also possible to install it on the opposite side or on both sides. Two or more cameras may also be installed. As shown in FIG. 5(B), installing it on both sides makes it possible to select and use camera images suitable for detecting movement. For example, if the camera on the entrance side where the subject is inserted into the bore is close to the abdomen and the camera on the opposite side is close to the face, respiratory movement is detected using the image from the camera on the entrance side, and pulsation is detected using the image from the camera on the opposite side. Respiratory movement may also be detected using images from the cameras on both sides.

[0025] An overview of the operation of the biosignal measurement system 20 in the above configuration is shown in Fig. 6. As shown in the figure, prior to imaging by the imaging device 100, measurement by the biosignal measurement device 200 is started and information is acquired from the sensor (S1). In this case, the sensor is a camera, and a video signal is output as a bioinformation signal. This video signal is received by the optical flow calculation unit 311A, which calculates optical flow, which is information on movement, from changes in the image between frames.

[0026] Optical flow is a velocity vector representing the change in pixel position between frames for each pixel, and can be calculated using a gradient method such as Lucas-Kanade. By calculating this between each frame, the variation of each pixel with respect to the time axis can be obtained as the integral value of the velocity vector (S2). If the body axis direction of the subject 103 is defined as the Y direction, this variation can be obtained as the component in the direction perpendicular to the Y direction (Z direction) (the vector absolute value of the Z component). An example of the variation obtained in this way is shown in Figure 7(A).

[0027] Next, to determine the position of the variation that most accurately reflects the body movement to be determined among the variations for each pixel (each position in the image), the index calculation unit 312 divides the image into multiple regions and calculates movement and noise indices for the variation in each region (S3). In this embodiment, the standard deviation (SD) of the variation values ​​and the band power (BP) of the variation are calculated as indices. SD is an index of noise and is used to eliminate regions with large noise. BP is also an index for determining whether large movement is occurring in a frequency band related to body movement.

[0028] To calculate the band power, the FFT unit 312A performs a Fourier transform on the fluctuations over the time axis as shown in Fig. 7(A), and calculates the power for each frequency as shown in Fig. 7(B). The power can be expressed by equation (1), and this is integrated over the frequency band (f1-f2) using equation (2) to calculate the band power. If the target movement is respiratory movement, its period is assumed to be 2 to 5 seconds (0.2 to 0.5 Hz), for example, and the power for that band is calculated.

[0029]

number

[0030]

number

[0031] The index calculation unit 312 calculates the indices SD and BP for each region, and the region of interest selection unit 313 selects a region with low noise and large movement as a region of interest based on the indices calculated by the index calculation unit 312 (S4). Here, the minimum unit for the region for which the index calculation unit 312 calculates the indices is a pixel. However, the index calculation unit 312 may select one region from roughly divided regions, further subdivide that region, and select one or more regions from that. Furthermore, since optical flow and index calculations tend to fail for regions with too high or too low image brightness, a threshold may be set in advance to exclude those regions. Furthermore, while calculating BP requires information from a certain period of time, SD may potentially be calculated in a relatively short time. Therefore, the index SD may be used first to select a region of interest and begin acquiring biometric information, and then the index BP may be used to narrow down the region of interest. This can shorten the time until biometric information acquisition begins.

[0032] The above band power calculation formula is not limited to formulas (1) and (2). An appropriate calculation formula can be used depending on the measurement data.

[0033] For example, as shown in FIG. 8, first, a predetermined range of an image (or optical flow map) is divided into relatively large regions 71-74 (e.g., 140×140 pixels), and an index is calculated for each region. Of the multiple regions, a region with high accuracy (region 72 shown in gray) is selected, and region 72 is further divided into multiple small regions (e.g., 20×20 pixels), and an index for each small region is calculated. Of these small regions, one or more regions with the highest accuracy are designated as regions of interest. The index for a region can be calculated using the average or median value of the optical flow (variation) of all pixels included in the region.

[0034] Note that while an example of narrowing down the region in two stages, a large region and a region with high accuracy, is described here, a single stage is acceptable if you want to set the region in a shorter time even if the accuracy is somewhat lower, and three or more stages are acceptable if you want to set the region with higher accuracy. Also, while an example of creating an optical flow map and then dividing it into regions is described here, optical flow processing can also be performed after slightly limiting the region using an image before optical flow processing. For example, regions where there is clearly no living organism can be excluded from the region to be processed by optical flow at the image stage before optical flow processing.

[0035] The region of interest selection unit 313 can use the following method to select a region of interest using the indices SD and BP. For example, if BP is high compared to other regions, it is considered to reflect periodic body movement. SD can be a high value both when noise other than body movement is large and when movement is large, but if SD is large despite BP being small or if SD is prominent compared to other regions, it is considered to be noise. Therefore, the region of interest selection unit 313 can select a region of interest by, for example, first selecting multiple regions with high BP and then excluding regions where BP or SD exceed a predetermined threshold.

[0036] Furthermore, to improve the accuracy of index values ​​(especially SD), filtering or any order of regression processing may be performed on the time series data of fluctuations before calculating the index values. Furthermore, since the waveforms of biological information are not necessarily perfectly periodic, it is also possible to prepare a typical waveform of the target biological information and search for similar shapes. When searching for similar shapes, AI such as machine learning may be applied. Furthermore, a frequency analysis method using wavelet transform may be adopted.

[0037] As an example, Figure 9 shows the fluctuations calculated from optical flow for four regions, along with the calculated SD and BP. As shown in the figure, region 1 has a large BP, but the SD is also significantly large, so it is excluded as being noisy. Of the remaining three regions, region 3, which has a large BP, is selected as the region of interest. This result matches well with the fluctuation graph, and the region that reflects body movement is set as the region of interest. The threshold values ​​for SD and BP can be set from empirically determined values.

[0038] In the above example, the region of interest selection unit 313 selected the region of interest using BP and SD, but it is also possible to use an index such as the ratio of BP to SD. Furthermore, since noise and body movement, which are factors that increase SD, have different frequency distributions as shown in Fig. 7(B), it is also possible to use the range of the distribution (for example, the range of frequencies above a predetermined power) as an index.

[0039] As shown in FIG. 5(B), when two or more cameras are used, the image signals from the cameras are used to calculate the above-mentioned indexes for each camera, and a region of interest is selected for each camera.

[0040] Once the region of interest is determined by the region of interest selector 313, the signal analyzer 310 calculates the fluctuation of the region of interest using the video signal sent from the camera 210 when the imaging device 100 starts imaging (examination), and sends the calculated fluctuation to the imaging device 100 as biometric information (S5). As shown in FIG. 1, the imaging device (medical imaging device) 100 includes a computer 105 that functions as a calculation unit for image reconstruction and a control unit for controlling imaging using biometric information. When performing synchronous imaging, the computer 105 performs synchronous imaging using this biometric information. For example, the control unit controls the imaging so that imaging is performed at a certain phase of the fluctuation. Alternatively, the calculation unit of the imaging device 100 can correct the acquired image using movement information of the imaging region. Since well-known techniques can be used for synchronous imaging and correction methods using biometric information, their description will be omitted here.

[0041] According to this embodiment, optical flow is calculated from the video signal acquired by the camera, a region of interest is determined from which biometric information with large movement and small noise can be obtained with high accuracy, and the biometric information is acquired from the region of interest, so that biometric information (movement of the subject) can be obtained with high accuracy without depending on the skill of the examiner in setting the region of interest or on individual differences between subjects. Furthermore, the use of a camera eliminates the time and effort required for setting the subject.

[0042] Although the imaging device 100 has been described as an MRI device, the imaging device may be a medical imaging device other than an MRI device, and the biological signal processing system of the present invention may also be applied to an examination device such as an endoscope or an ultrasound device inserted into the body. In such cases, the examination space is interpreted in a broad sense to include a support table or support column that supports the examination device.

[0043] 7 and 8, graphs of time-dependent changes in body movements such as breathing, and diagrams visualizing the positions of automatically set regions can also be displayed as GUIs on the display 400 within the diagnostic device. This allows the technician to more clearly grasp the condition of the subject. Furthermore, since the frequency of body movements can be determined by the FFT unit 312A performing a Fourier transform on the fluctuations over the time axis, the breathing rate can be calculated from that frequency and displayed on the display.

[0044] <Embodiment 2> In the first embodiment, the optical flow was calculated using the video signal from the camera, and the optical flow was analyzed to select the region of interest. In this embodiment, however, a stereo camera is used, and the distance from the camera to the subject, calculated using the image shift between the left and right cameras, is analyzed to select the region of interest.

[0045] In this embodiment, the configuration of the signal processing device 300 is the same as that of the first embodiment, except that the optical flow calculation unit 311A ​​in Fig. 3 is replaced with a distance calculation unit, and the processing procedure is also the same as that shown in Fig. 6. The following description will focus on the differences from the first embodiment.

[0046] When the body axis direction of the subject is defined as the Y direction and the left-right direction perpendicular to the Y direction is defined as the X direction, the stereo camera 220 is installed in the bore so that the left and right cameras are aligned in the X direction, as shown in FIG.

[0047] When the signal analysis unit 310 (distance calculation unit) inputs the video signals from the left camera and the right camera of the stereo camera 220, it detects the image shift S for each frame of both video signals, and calculates the distance D from the focal point to the object using the focal length f of both cameras and the reference length (distance between the focal points) B according to the following equation (3). [Number 3] D=B×f / S (3)

[0048] The amount of deviation S between the images from the left and right cameras can be calculated using techniques such as block matching. Here, one image is used as a reference and divided into multiple regions, and for each region, a region with high correlation in the other image is determined, and the deviation S between the images is calculated for each frame. This allows the variation in distance D for each region to be obtained. This variation becomes biological information reflecting body movement, similar to the graphs shown in Figure 2 and Figure 7(A).

[0049] When the distance calculation unit calculates the variation in the distance between the subject and the camera, the index calculation unit 312 calculates an index of the magnitude of noise and movement using the distance variation for each region. The index may be the standard deviation SD of the variation, the band power BP, or a combination thereof, as in the first embodiment, and can be calculated in the same manner as in the first embodiment. Thereafter, the region of interest selection unit 313 selects a region with less noise and greater movement using the index calculated for each region by the index calculation unit 312, and then calculates the variation from the selected region of interest and outputs it to the imaging device as a biological information signal, as in the first embodiment.

[0050] According to this embodiment, by using a stereo camera, distances that directly reflect body movements can be acquired, making it possible to select areas with high accuracy.

[0051] <Modification> In the first and second embodiments, the case where only one body movement (for example, respiratory movement) is obtained as a bioinformation signal has been described, but it is also possible to obtain respiratory movement and pulsation simultaneously. As shown in FIG. 7(B), the power for each frequency can be obtained by Fourier transforming the fluctuation graph. Respiratory movement is approximately 0.2 to 0.5 Hz, while pulsation is approximately 1 Hz to 2 Hz, which is significantly different. In a graph reflecting the frequencies of body movements, these two body movements appear as peaks at different frequencies.

[0052] Therefore, when monitoring two body movements, the index calculation unit 312 calculates the BP for each of the two body movements by changing the range of integration (band f1-f2) expressed by equation (2), and the region of interest selection unit 313 selects a region of interest for each type of body movement based on the calculated BP and the SD of the overall fluctuation.

[0053] In addition, in the above-mentioned embodiments 1 and 2, video signals from a camera were used, but it is also possible to use a range finder using non-contact infrared or millimeter waves as the bio-information measuring device 200.In this case, by obtaining the distance fluctuations for each region, it is possible to analyze the fluctuations using indicators and select regions of interest, as in embodiments 1 and 2.

[0054] <Embodiment 3> The biological signal processing system of this embodiment is characterized in that it can also handle sudden movements of the subject and abnormal situations in addition to respiratory movement and pulsation. The method of acquiring the biological signal may be any of the methods of the above-mentioned embodiments. As shown in FIG. 11, an abnormal signal detection unit 314 is added to the signal processing device 300 (signal analysis unit 310) of this embodiment. The other configurations are the same as those of FIG. 3 (or its modified example).

[0055] The operation of the biological signal processing system in this embodiment will be described below with reference to the flow in Fig. 12. In Fig. 12, the same processes as those in Fig. 6 are denoted by the same reference numerals, and overlapping descriptions will be omitted.

[0056] In this embodiment, biometric information is acquired from the biosignal measuring device 200 (S1), movement information (variation) is calculated (S2), and an index indicating the magnitude of noise and movement is calculated (S3). When a region of interest is selected based on the index (S4), imaging is initiated. During imaging, the biometric information acquired by the biometric measuring device 200 from the selected region of interest is analyzed to calculate movement information (S5). The signal processing device 300 displays this information on the display device 400 provided in the signal processing device 200 or the display device provided in the imaging device 100, and also transmits it to the inspection device 100. In the case of synchronized imaging, for example, it is necessary to present information that clearly shows the period of body movement, as shown in FIG. 2. However, to detect abnormalities, a display with a different scale, as shown in FIG. 13, may be used. In this case, if the subject is stationary, the line will be a nearly flat line, indicating that imaging can continue.

[0057] Imaging is performed while referring to such movement information, but if there is a large movement, for example, as shown on the right side of the graph in Figure 13, the position set as the region of interest may be shifted. If the magnitude of the movement exceeds a predetermined threshold, the abnormal signal detection unit 314 determines that an abnormality has occurred (S6, S7). As a result, the signal analysis unit 310 again repeats the steps of calculating movement information for multiple regions (S2) using the biological signal calculation unit 311 (optical flow calculation unit and distance calculation unit), calculating an index for each region (S3), and selecting a region of interest based on the index (S4), and sets the newly selected region of interest as the subsequent region of interest.

[0058] Thereafter, imaging continues while referring to biological information from the newly set region of interest (S8), as described above.

[0059] According to this embodiment, even when an unexpected movement other than the body movement of interest occurs, the region of interest can be immediately updated, and accurate bio-information signals can be continuously acquired.

[0060] Furthermore, as shown in Figure 14, it is also possible to use the amount of change (equivalent to the differential value of the change) instead of the variation (coordinate information). Figure 14(B) shows the change over time in the amount of change (differential value of the variation), but it is also possible to set a certain threshold and detect an abnormality when the threshold is exceeded. Also, the amount of change shown here is the amount of change in the up and down direction of the figure (the direction thought to be movement due to breathing), but it is also possible to calculate the amount of change in the perpendicular component and use that information. The vertical component is a component that is nearly 0 due to breathing movement, so it may be possible to detect abnormalities with greater sensitivity.

[0061] Furthermore, the techniques of the above-described embodiments and modifications can be applied to various imaging fields including medical imaging. Furthermore, the present invention is not limited to the above-described embodiments and modifications. [Explanation of symbols]

[0062] 10: Medical imaging system, 20: Biosignal measurement system, 100: Inspection device (medical imaging device), 200: Biosignal measurement device, 210: Sensor (camera), 300: Signal processing device, 310: Signal analysis unit, 311: Bioinformation calculation unit, 311A: Optical flow calculation unit, 312: Index calculation unit, 313: Region of interest selection unit, 314: Abnormal signal detection unit

Claims

1. A medical imaging device equipped with a biological signal processing system, The biological signal processing system includes: a non-contact camera that is installed in or near the examination space of the imaging device and measures the state of the subject under examination; and a signal analysis unit that processes a biological information signal measured by the camera and calculates the movement of the subject, The camera acquires a camera image from a predetermined range of the subject, the signal analysis unit includes a region of interest selection unit that calculates an optical flow from the camera image, calculates a band power (BP) for each of a plurality of regions included in the predetermined range based on the optical flow, and selects a region of interest from the plurality of regions from which the movement of the subject should be acquired using the band power as an index of movement; and an abnormal signal detection unit that detects an abnormal value included in the biological information signal; the region of interest selection unit reselects a region of interest when the abnormal signal detection unit detects an abnormal value; The signal analysis unit calculates the movement of the subject using the biological information signal measured from the region of interest selected by the region of interest selection unit.

2. 2. The medical imaging apparatus according to claim 1, The medical imaging apparatus is characterized in that the camera is installed in the examination space so as to photograph a predetermined range of the subject from an oblique angle.

3. 2. The medical imaging apparatus according to claim 1, The biological information signal is a signal reflecting any one of a pulsation, a heartbeat, and a body movement of the subject, The region of interest selection unit calculates a band power of fluctuations as an index of movement for the bioinformation signals of the plurality of regions, and selects the region of interest based on the index.

4. an inspection device having an inspection space in which a subject is placed; a non-contact camera installed in or near the inspection space and measuring the state of the subject during inspection; a signal analysis device that processes biological information signals measured by the camera and calculates the movement of the subject; and a display device that displays a GUI; The camera acquires a camera image from a predetermined range of the subject, The signal analysis device includes a region of interest selection unit that calculates an optical flow of the camera image, calculates band power (BP) for each of a plurality of regions included in the predetermined range based on the optical flow, and selects a region of interest from the plurality of regions from which the movement of the subject should be acquired using the band power as an index of movement, and an abnormal signal detection unit that detects an abnormal value included in the biological information signal, the region of interest selection unit reselects a region of interest when the abnormal signal detection unit detects an abnormal value; The signal analysis device calculates the movement of the subject using the biological information signal measured by the camera from the region of interest selected by the region of interest selection unit.

5. 5. The medical imaging system of claim 4, The examination device is a magnetic resonance imaging device including a static magnetic field generating unit that generates a static magnetic field, an imaging unit that applies a high frequency magnetic field to a subject placed in a static magnetic field space, receives a nuclear magnetic resonance signal generated by the subject, and generates an image of the subject using the nuclear magnetic resonance signal, and a control unit that controls the imaging unit, The medical imaging system is characterized in that the control unit controls the operation of the imaging unit using biological information signals from the region of interest of the subject measured by the camera.

6. 5. The medical imaging system of claim 4, The examination device is a magnetic resonance imaging device including a static magnetic field generating unit that generates a static magnetic field, an imaging unit that applies a high frequency magnetic field to a subject placed in a static magnetic field space, receives a nuclear magnetic resonance signal generated by the subject, and generates an image of the subject using the nuclear magnetic resonance signal, The medical imaging system is characterized in that the imaging unit corrects the nuclear magnetic resonance signal or the image using a biological information signal from the region of interest of the subject measured by the camera.

7. 5. The medical imaging system of claim 4, A medical imaging system, wherein the device for displaying the GUI displays, as the GUI, at least one of the plurality of regions and a region of interest selected by the region of interest selection unit.

8. 5. The medical imaging system of claim 4, A medical imaging system, characterized in that the device displaying the GUI displays at least one of the biological information signal measured by the camera, the analysis result of the signal analysis device, and data during analysis.

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