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

Abstract

The present invention relates to a medical imaging device, a medical imaging system, and a biological signal processing method equipped with a biological signal processing system. A technique is provided for accurately and automatically setting a region of interest for acquiring biological information based on biological information signals obtained non-contact from a subject placed in an examination space. A signal analysis unit of the medical imaging device uses the biological information signals of each of multiple regions within a given range measured by a biological information measurement device to select a region of interest from among multiple regions for acquiring the subject's activity. The subject's activity is calculated using the biological information signals measured by the biological information measurement device from the selected region of interest.

Description

Technical Field

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

[0002] When examining subjects (mostly patients) using medical imaging devices such as MRI (Magnetic Resonance Imaging) devices, synchronization with the subject's movement is widely used to reduce the effects of artifacts caused by their pulse and respiratory movements. This is typically accomplished by attaching a measuring device, such as an electrocardiograph or a breathing balloon, to the subject being examined to measure their pulse and respiratory movements. The imaging is controlled by feeding signals from the measuring device into the imaging device. Furthermore, if respiratory movement can be accurately detected, this movement can be used to correct the measured data and images.

[0003] However, a measuring device such as a respiratory balloon requires preparation for attaching it to a patient, and depending on the placement method and individual differences in the subject, it may not be possible to detect respiratory movements with high accuracy.

[0004] In contrast, MRI systems widely use technology to detect respiratory motion by collecting signals from a specific moving location, such as the diaphragm, and monitoring respiratory motion. However, this technology requires extended imaging time in order to generate and collect navigator echoes separately from the nuclear magnetic resonance signals used for image formation.

[0005] Meanwhile, Patent Document 1 discloses a camera system for automatically measuring physiological parameters such as pulse and respiratory movement of a subject. The system describes the use of this camera system in an MRI apparatus to automatically measure physiological parameters during MRI examinations. In this camera system, before the subject is transported into the bore (examination space) of the examination apparatus, a digital camera located outside the bore measures the subject's biometric parameters. After a predetermined range of the subject is determined, a camera positioned distally from the bore captures the predetermined range of the subject once it has been transported into the bore. The biometric parameters are used to determine a region of interest, and physiological parameters are calculated from the image data of the region of interest.

[0006] Prior art literature

[0007] Patent Literature

[0008] Patent Document 1: JP Patent No. 6714006

[0009] As described above, in order to obtain physiological information (activity information) such as respiratory movement and pulsation from the subject in a non-contact manner, it is important to set a region of interest that best reflects this information. In particular, when performing respiratory-synchronized imaging, correctly setting the region of interest becomes indispensable. However, in Patent Document 1, the region of interest is determined based on biometric parameters, specifically the distance between the subject's sternum and right clavicle. However, when the region of interest is determined solely based on biometric parameters such as the subject's size, there is a possibility that the region of interest is too large. In addition, when the region of interest is narrow, there is a possibility that positional deviation occurs, and the appropriate setting of the region of interest cannot be guaranteed. In addition, in the technology described in Patent Document 1, in order to obtain biometric parameters, it is necessary to set a camera outside the chamber separately from the camera that captures the range including the region of interest. In other words, two cameras become necessary. Summary of the Invention

[0010] The present invention solves the problems of the above-mentioned prior art, and the problem is to provide a technology that can correctly and automatically set the area of ​​interest for obtaining biological information based on the biological information signal obtained non-contact from the subject placed in the examination space; thereby, the capture of medical images utilizing biological information (information on activity) can be efficiently performed, reducing the time and trouble of doctors, technicians, etc.

[0011] To address the above-mentioned issues, the medical imaging apparatus of the present invention includes a biological signal processing system comprising: a biological information measuring unit, disposed within or near an examination space of the medical imaging apparatus, which measures the state of a subject under examination in a non-contact manner; and a signal analysis unit, which processes the biological information signals measured by the biological information measuring unit to calculate the subject's motion. The biological information measuring unit acquires the biological information signals from a predetermined range of the subject, and the signal analysis unit includes a region of interest selection unit, which uses the biological information signals of each of a plurality of regions within the predetermined range to select a region of interest from among the plurality of regions for which the subject's motion is to be acquired. The signal analysis unit calculates the subject's motion using the biological information signals measured from the region of interest selected by the region of interest selection unit.

[0012] Furthermore, the medical imaging system of the present invention includes: an inspection apparatus; a biological signal processing system including the biological information measuring unit and the signal analyzing unit described above; and a device for displaying a GUI.

[0013] Furthermore, the biological signal processing method of the present invention processes the biological information signal of the subject under inspection measured by a non-contact biological information measuring device set in the inspection space of the inspection device or near the inspection space, and calculates the activity of the subject. The biological signal processing method includes: a step of using the biological information signal measured from a given range of the subject to generate a biological information signal of each of a plurality of regions; a step of calculating an index related to the intensity of noise or activity for the biological information signals of the plurality of regions; and a step of selecting a region of interest of the subject for calculating the activity based on the index.

[0014] Effects of the Invention

[0015] According to the present invention, a position or area where the biological information measuring device can accurately capture the subject's activities can be set as a region of interest, and by processing the biological information signals collected from the region of interest, the subject's activities can be collected with high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a diagram showing the overall outline of the biological signal processing system of the present invention and the medical imaging system including the same.

[0017] Figure 2 This is a diagram showing an example of a biological information signal.

[0018] Figure 3 This is a block diagram showing the structure of the signal analysis unit according to the first embodiment.

[0019] Figure 4 This is a diagram showing an example of the installation position of a camera in an inspection device.

[0020] Figure 5 (A) and (B) are diagrams showing other examples of the installation positions of cameras in the inspection device.

[0021] Figure 6 This is a diagram showing the flow of operations of the biological signal processing system according to the first embodiment.

[0022] Figure 7 This is a diagram showing an example of analysis results by the signal analysis unit in the first embodiment.

[0023] Figure 8 (A) and (B) are diagrams for explaining selection of an area of ​​interest by the area of ​​interest selection unit in the first embodiment.

[0024] Figure 9 This is a diagram illustrating an example of selecting a region of interest using an indicator.

[0025] Figure 10This is a diagram illustrating the arrangement of cameras in the second embodiment.

[0026] Figure 11 This is a diagram showing the structure of a signal processing device according to a third embodiment.

[0027] Figure 12 This is a diagram showing the flow of operations of the biological signal processing system according to the third embodiment.

[0028] Figure 13 This is a diagram showing an example of an indicator (time-series change) indicating an abnormality.

[0029] Figure 14 (A) and (B) are diagrams showing examples of indicators (two types of time-series changes) indicating abnormality.

[0030] Description of Reference Signs

[0031] 10: Medical imaging system, 20: Biological signal measurement system, 100: Inspection device (medical imaging device), 200: Biological signal measurement device, 210: Sensor (camera), 300: Signal processing device, 310: Signal analysis unit, 311: Biological information calculation unit, 311A: Optical flow calculation unit, 312: Index calculation unit, 313: Region of interest selection unit, 314: Abnormal signal detection unit. DETAILED DESCRIPTION

[0032] Hereinafter, embodiments of a biological signal processing system and a medical imaging system including the same according to the present invention will be described with reference to the accompanying drawings.

[0033] Medical image camera system 10 Figure 1 As shown, the main components include an inspection apparatus 100, a biological signal measurement apparatus 200, and a signal processing apparatus 300. The inspection apparatus 100 is a medical imaging apparatus such as an MRI apparatus, a CT apparatus, or a PET apparatus, and is capable of capturing images using biological information measured by the biological signal measurement apparatus 200. Specifically, the inspection apparatus (hereinafter referred to as the imaging apparatus) 100 performs synchronous imaging using biological information such as pulse and respiratory movement, and performs correction of measurement data using biological information.

[0034] The biometric signal measuring device 200 is a device that non-contactly acquires biometric information from a subject being examined using the imaging device 100. It is comprised of a camera, a distance sensor (hereinafter collectively referred to as a sensor, including cameras) that uses electromagnetic waves such as infrared and millimeter waves, and ultrasound. It detects information related to the distance between the sensor and the subject, the subject's movements, and so on, and outputs this information as a biometric information signal. If the sensor is a camera, the image data (time-series image data) obtained by the camera capturing a given range of the subject is a one-dimensional biometric information signal, which generates biometric information representing changes in pixel values ​​and pixel positions over time (a two-dimensional biometric information signal). Furthermore, a measuring device that utilizes electromagnetic waves, ultrasound, or the like includes a source that generates electromagnetic waves such as millimeter waves and ultrasound, and a receiver that receives their reflected waves. The reflected waves from a given range of the subject are processed to generate a biometric information signal for each position within the given range.

[0035] The signal processing device 300 uses the biological information signal output by the biological signal measurement device 200 to perform various processes to determine the part of the subject (region of interest) from which biological information (subject activity) is obtained and provided to the imaging device 100. To this end, 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 multiple positions or regions within a predetermined range based on the biological information signal transmitted from the biological signal measurement device 200; a region of interest selection unit 313 that analyzes the biological information for each position or region to determine the position or region that will yield the most accurate biological information; and an index calculation unit 312 that calculates an index related to the noise and intensity of the biological information.

[0036] The signal processing device 300 can be attached to the imaging device 100 and serve as a signal processing device for processing measurement signals and image signals within the imaging device 100. Alternatively, it can be a standalone device for processing signals from the biological signal measurement device 200. Herein, the system including the biological signal measurement device 200 and the signal analysis unit 310 of the signal processing device 300 is referred to as the biological signal measurement system 20. The functions of the signal processing device 300, including the signal analysis unit 310, are implemented by a computer equipped with a processing device such as a memory and a CPU, or a memory and a GPU, by loading an analysis program. However, some or all of the functions of the signal processing device 300 may be implemented using hardware such as an ASIC, and such implementations are also included in this embodiment. Furthermore, although not required, the computer implementing the functions of the signal processing device 300 may include, like a conventional computer, a display 400 for displaying processing results and a GUI, input devices such as a pointing device and a keyboard, and a storage device for storing the aforementioned analysis program, processing results, and data required for processing. Furthermore, the display provided by the imaging device 100 may also serve as the display 400 for displaying the GUI.

[0037] The specific content of the biological information signal will be described later. In the case where the biological information is a periodic activity such as the pulse and respiratory movement of the subject, the two-dimensional biological information signal is as follows: Figure 2 As shown in the figure, it becomes a periodic signal with a given amplitude. Figure 2 The subject area for such a biometric signal is limited to a relatively narrow range. Even within its periphery, there are areas where noise levels are high, making it difficult to detect periodicity, and areas where it is difficult to determine the signal amplitude to be small. Obtaining a biometric signal as an average of these areas degrades the accuracy of the biometric information. Furthermore, the area most suitable for acquiring a biometric signal varies from person to person, so even if a location is determined based on landmarks on the subject, a highly accurate biometric signal cannot necessarily be obtained.

[0038] The biological signal measurement system 20 of this embodiment first uses the biological information signals measured by the biological signal measurement device 200 to determine the location of the subject (region of interest) that is most suitable for obtaining biological information. The biological information signals obtained from the determined region of interest are then used to calculate the biological information. To determine the region of interest, indicators related to noise and activity intensity are calculated using the biological information signals obtained from multiple regions. Based on one or more calculated indicators, a region with low noise and high activity intensity is selected from the multiple regions and set as the region of interest. Various methods exist for the size and division of the multiple regions, and the selected region of interest is not limited to one but can also be two or more.

[0039] An embodiment in which the imaging apparatus 100 is an MRI apparatus and the sensor of the biological signal measurement apparatus 200 is a camera 210 will be described below.

[0040] <Implementation Method 1>

[0041] In this embodiment, the sensor of the biological signal measurement device 200 is a single camera, which obtains an image signal as a one-dimensional biological information signal and calculates a signal representing the position change obtained from the optical flow of the image as a two-dimensional biological information signal. Figure 1 The structure shown is the same. Figure 3 The details of the signal analysis unit 310 are shown in FIG. Figure 3 In, with Figure 1 Elements having the same function are shown with the same reference numerals.

[0042] As shown in the figure, the signal analysis unit 310 includes an optical flow calculation unit 311A ​​as Figure 1 The biological information calculation unit 311 receives an image signal (one-dimensional biological information signal) from the sensor (camera) 210, calculates the optical flow from two or more frames of image data that are temporally adjacent, and calculates the change in the position of the subject for each pixel or each sub-pixel. The index calculation unit 312 calculates an index that characterizes the noise and activity intensity of the biological information signal for each pixel or each sub-pixel generated by the optical flow calculation unit 311A. The index calculation unit 312 calculates, for example, frequency band power as an index of activity intensity. To this end, the index calculation unit 312 includes an FFT unit 312A that converts the 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 the biological information signal can be collected with high accuracy.

[0043] For example, Figure 4 As shown, in the case of an MRI apparatus such as an MRI apparatus in which the inspection apparatus 100 is a structured apparatus having an elongated cylindrical chamber 101 as an inspection space and a subject 103 placed on a bed 102 and arranged in the inspection space, the camera 210 is set at a position where it can obliquely capture the subject 103 from above the end of the chamber 101, thereby obtaining an image of a relatively large range including the chest of the subject 103. Figure 4 In the example, the camera 210 is installed on the entrance side where the subject is inserted into the chamber, but it is also possible to install the camera 210 on the entrance side where the subject is inserted into the chamber. Figure 5 As shown in (A) and (B), they can be installed on opposite sides or on both sides. In addition, more than two cameras can be installed. Figure 5As shown in (B), the camera can be installed on both sides, and the camera image suitable for detecting movement can be selected. For example, if the camera on the entrance side of the insertion chamber is close to the abdomen and the camera on the opposite side is close to the face, the camera image on the entrance side can be used to detect respiratory movement, and the camera image on the opposite side can be used to detect pulsation. Alternatively, the camera images on both sides can be used to detect respiratory movement.

[0044] exist Figure 6 The following diagram summarizes the operation of the biological signal measurement system 20 in the above-described configuration. As shown, before the imaging device 100 captures images, the biological signal measurement device 200 begins measurement and acquires information from the sensor (S1). Here, the sensor is a camera that outputs an image signal as a biological information signal. The optical flow calculation unit 311A ​​receives this image signal and calculates optical flow, which is motion information, based on changes in the image between frames.

[0045] The optical flow uses a velocity vector to represent the change in pixel position between frames for each pixel, which can be calculated using gradient methods such as Lucas-Kanade. By calculating it between frames, the change of each pixel relative 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 set to the Y direction, the change can be obtained as a component in the direction orthogonal to it (the vector absolute value of the Z component). Figure 7 (A) shows an example of the change obtained in this way.

[0046] Next, to determine the location within each pixel (each position in the image) that most accurately reflects the desired body motion, the index calculation unit 312 divides the image into multiple regions and calculates activity and noise indices for the changes in each region (S3). In this embodiment, the standard deviation (SD) of the variation values ​​and the frequency band power (BP) of the variation are calculated as indices. SD is an indicator of noise and is used to exclude regions with significant noise. Furthermore, BP serves as an indicator for determining whether significant activity is occurring in the frequency band associated with body motion.

[0047] In order to calculate the frequency band power, the FFT unit 312A performs Figure 7 The change with respect to the time axis as shown in (A) is Fourier transformed, as shown in Figure 7 As shown in (B), the power of each frequency is calculated. Power can be expressed by formula (1), and it is integrated in the frequency band (f1-f2) using formula (2) to calculate the frequency band power. If the target activity is breathing, its period is, for example, 2 to 5 seconds (0.2 to 0.5 Hz), and the power of the frequency band is calculated.

[0048]

Mathematical formula 1

[0049]

[0050] In formula (1), f is the frequency, x is the sampled measurement signal, N is the number of measurement points, and Δt is the sampling interval.

[0051]

Mathematical formula 2

[0052]

[0053] The index calculation unit 312 calculates the aforementioned indices SD and BP for each region. The region of interest selection unit 313 selects a region with low noise and high activity as a region of interest based on the indices calculated by the index calculation unit 312 (S4). While the minimum unit for the region for which the index calculation unit 312 calculates the indices is each pixel, it is also possible to select a single region from the roughly divided regions, further subdivide them, and select one or more regions from these regions. Furthermore, for regions with excessively high or low image brightness, since optical flow and index calculations are more likely to fail, a threshold value may be pre-set to exclude these regions. Furthermore, while calculating BP requires information over a certain period of time, calculating SD may be possible in a shorter time. Therefore, it is also possible to first select the region of interest using the SD indicator to begin acquiring biometric information, and then narrow the region of interest using the BP indicator. This can also shorten the time until biometric information acquisition begins.

[0054] The calculation formula for the above-mentioned band power is not limited to formulas (1) and (2), and an appropriate calculation formula may be used according to the measurement data.

[0055] For example, Figure 8 As shown, first, a given range of an image (or optical flow map) is divided into relatively large areas 71 to 74 (e.g., 140×140 pixels), an index is calculated for each area, and a high-precision area (area 72 shown in gray) is selected from the multiple areas. Then, the area 72 is divided into multiple small areas (e.g., 20×20 pixels), and the index of the small areas is calculated. One or more areas with the highest accuracy among these small areas are set as the focus area. In calculating the index of the area, the average value or median value of the optical flow (variation) of all pixels contained in the area can be used.

[0056] In addition, while this example describes how the region is reduced in two stages: a large area and a high-precision area, if even slightly reduced precision is desired and the region setting is desired in a shorter time, a single stage is acceptable, and if even higher precision is desired, three or more stages are acceptable. Furthermore, while this example describes how the region is divided after the optical flow map is created, it is also possible to perform optical flow processing after slightly limiting the region using the image before optical flow processing. For example, areas where organisms are clearly absent can be excluded from the regions subjected to optical flow processing at the stage of the image before optical flow processing.

[0057] The region of interest selection unit 313 can use the following method to select a region of interest using the indicators SD and BP. For example, if BP is higher than other regions, it is considered to reflect periodic body movement. Regarding SD, it will be high in both cases where there is a lot of noise other than body movement and when there is a lot of movement. If BP is low but SD is high, or if the SD is prominent compared to other regions, it is considered to be noise. Therefore, the region of interest selection unit 313 first selects multiple regions with high BP, and then excludes those regions where BP and SD exceed predetermined thresholds to select the region of interest.

[0058] Furthermore, to improve the accuracy of the index values ​​(especially the SD), the fluctuating time series data can be filtered or regressed any number of times before calculating the index values. Furthermore, the waveform of biological information is not limited to having complete periodicity, so a typical waveform of the biological information being studied can be prepared and similar shapes can be found. AI, including machine learning, can be used to find similar shapes. Furthermore, frequency analysis techniques using Wavelet transforms can be employed.

[0059] As an example, in Figure 9 The figure shows the changes calculated based on optical flow for four regions, along with the calculated SD and BP. As shown, region 1, while having a large BP, has a significantly larger SD and is therefore excluded as excessively noisy. Of the remaining three regions, region 3, which has a large BP, is selected as the region of interest. As a result, the region that closely matches the change graph and reflects body motion is set as the region of interest. The SD and BP thresholds can be set empirically.

[0060] In the above example, the region of interest selection unit 313 uses BP and SD to select the region of interest. However, it is also possible to use an index such as the ratio of BP to SD. Figure 7 Since the frequency distribution shown in (B) is different, the range of the distribution (for example, the range of frequencies with a given power or more) can also be used as an indicator.

[0061] like Figure 5 As shown in (B) of FIG. 5 , when two or more cameras are used, the above-mentioned indexes are calculated using the video signals of the plurality of cameras, and a region of interest is selected for each camera.

[0062] When the ROI selection unit 313 determines the ROI, and the imaging device 100 starts imaging (inspection), the signal analysis unit 310 causes the optical flow calculation unit 311A ​​to calculate the change of the ROI using the image signal sent from the camera 210, and sends it to the imaging device 100 as biological information (S5). Figure 1 As shown, the computer 105, which includes a computing unit for image reconstruction and a control unit for controlling imaging using biometric information, uses this biometric information when performing synchronized imaging. For example, the control unit controls the imaging to occur at a fixed, variable phase. Alternatively, the computing unit of the imaging device 100 can use information about the movement of the imaging site to correct the acquired image. Since the synchronized imaging and correction methods using biometric information can be well-known, their description is omitted here.

[0063] According to this embodiment, optical flow is calculated from the image signal acquired by the camera, and a region of interest (ROI) is determined where high-precision biometric information with high motion and low noise can be obtained. Biometric information is then acquired from this region of interest. This allows for highly accurate acquisition of biometric information (subject motion) independent of the quality of the examiner setting the ROI or individual differences in the examinee. Furthermore, the use of a camera eliminates the time and effort required for positioning the examinee.

[0064] While the imaging device 100 is described as an MRI device, the imaging device may also be a medical imaging device other than an MRI device. Furthermore, the biological signal processing system of the present invention may be applied to inspection devices such as endoscopes and ultrasonic devices inserted into the body. In this case, the term "inspection space" is interpreted broadly to include a support platform or support columns that support the inspection device.

[0065] In addition, Figure 7 、 Figure 8 A graph showing temporal changes in body motion, such as respiration, and a visualization of the automatically set areas are displayed as a GUI on the display 400 within the diagnostic apparatus. This allows the technician to more clearly understand the condition of the subject. Furthermore, the FFT unit 312A performs a Fourier transform on the time axis to determine the frequency of body motion. The respiratory rate can then be calculated from this frequency and displayed on the display.

[0066] <Implementation Method 2>

[0067] In embodiment 1, the optical flow is calculated using the image signal from the camera, the optical flow is analyzed, and the area of ​​interest is selected, but in this embodiment, a stereo camera is used to analyze the distance from the camera to the subject calculated using the deviation of the images of the left and right cameras to select the area of ​​interest.

[0068] In this embodiment, the structure of the signal processing device 300 is as follows: Figure 3 Except that the optical flow calculation unit 311A ​​is replaced by the distance calculation unit, the other operations are the same as those in the first embodiment. In addition, the processing order is also the same as that in the first embodiment. Figure 6 The following description will focus on the differences from the first embodiment.

[0069] If the body axis direction of the subject is set as the Y direction, and the left and right directions orthogonal to the Y direction are set as the X direction, the stereo camera 220 is as follows: Figure 10 As shown, the left and right cameras are arranged side by side in the X direction in the chamber.

[0070] When the signal analysis unit 310 (distance calculation unit) receives the image signal from the left camera and the image signal from the right camera of the stereo camera 220, it detects the image deviation S for each frame of the two image signals, and uses the focal length f of the two cameras and the reference length (the distance between the focal points) B to calculate the distance D from the focal point to the object using the following formula (3).

[0071] [Mathematical formula 3]

[0072] D=B×f / S (3)

[0073] The deviation S between the left and right camera images can be calculated using methods such as block matching. Here, one image is used as a reference and divided into multiple regions. 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 results in a change in the distance D for each region. This change is related to Figure 2 、 Figure 7 The graph shown in (A) also reflects biological information of body movement.

[0074] Once the distance calculation unit calculates the variation in the distance between the subject and the camera, the index calculation unit 312 uses the distance variation for each region to calculate indices for noise and motion levels. Similar to the first embodiment, the indices can be calculated using the standard deviation (SD) of the variation, the band power (BP), or a combination thereof. Similarly to the first embodiment, the region of interest selection unit 313 uses the indices calculated for each region by the index calculation unit 312 to select a region with low noise and high motion levels. The variation from the selected region of interest is then calculated and output to the imaging device as a biological information signal.

[0075] According to this embodiment, since the distance that directly reflects the body movement can be obtained by using a stereo camera, high-precision area selection can be performed.

[0076] Modifications

[0077] In the first and second embodiments, the case where only one body movement (e.g., respiratory movement) is obtained as a biological information signal is described, but respiratory movement and pulsation can also be obtained simultaneously. Figure 7 As shown in (B), the power of each frequency can be determined by Fourier transforming the variation graph. Respiratory movement is approximately 0.2-0.5 Hz, while pulsation is approximately 1-2 Hz, significantly different. In the graph reflecting the frequency of body movement, these two body movements are represented by peaks at different frequencies.

[0078] Therefore, when monitoring the movements of two people, the indicator calculation unit 312 calculates BP for each of the two movements by varying the range of the integral represented by formula (2) (frequency band f1-f2), and the region of interest selection unit 313 selects a region of interest for each type of movement based on the calculated BP and the overall SD of the variation.

[0079] In addition, in the above-mentioned embodiments 1 and 2, the image signal from the camera is used, but as the biological information measuring device 200, a non-contact rangefinder using infrared rays, millimeter waves, etc. can also be used. In this case, by obtaining the change in distance for each area, analysis using the change in indicators and selection of the area of ​​interest can be performed in the same way as in embodiments 1 and 2.

[0080] <Implementation Method 3>

[0081] The characteristic point of the biological signal processing system of this embodiment is that it can also deal with the subject's activities and abnormal conditions that may occur suddenly in addition to respiratory movements and pulsations. The method for obtaining biological signals can also adopt any of the methods of the above-mentioned embodiments. The signal processing device 300 (signal analysis unit 310) of this embodiment is as follows: Figure 11 As shown in FIG, an abnormal signal detection unit 314 is added. Figure 3 (or its variations) the same.

[0082] The following references Figure 12 The operation of the biological signal processing system in this embodiment is described by the following process. Figure 12 In the Figure 6 The same processing contents are denoted by the same reference numerals, and repeated descriptions are omitted.

[0083] In the embodiment, biological information is obtained from the object signal measuring device 200 (S1), activity information (change) is calculated (S2), and an index indicating the size of noise and the size of activity is calculated (S3). If a region of interest is selected based on the index (S4), video recording is started. During video recording, the biological information obtained from the selected region of interest among the biological information obtained by the biological information measuring device 200 is analyzed, and activity information is calculated (S5). The signal processing device 300 displays the information on the display device 400 included in the signal processing device 200 and the display device included in the imaging device 100, and also sends it to the inspection device 100. Regarding display, in the case of synchronous video recording, etc., Figure 2 As shown, it is necessary to clearly know the information of the body movement cycle, but it is also possible to detect abnormalities. Figure 13 As shown in the figure, the scale of the display is changed. In this case, it can be seen that if the subject is in a stationary state, it becomes a substantially flat straight line and the imaging continues.

[0084] The video is taken with reference to information about such activities, for example Figure 13 As shown on the right side of the graph, if there is significant movement, there is a possibility that the position set as the target area may deviate. When the magnitude of the movement exceeds a predetermined threshold, the abnormal signal detection unit 314 determines that an abnormality has occurred (S6, S7). Consequently, the signal analysis unit 310 repeats the steps performed by the biometric signal calculation unit 311 (optical flow calculation unit, distance calculation unit) to calculate movement information for multiple areas (S2), calculate an index for each area (S3), and select a target area based on the index (S4), setting the newly selected target area as the target area for the future.

[0085] Thereafter, as described above, imaging is continued with reference to the biological information from the newly set region of interest ( S8 ).

[0086] According to this embodiment, even when unexpected motion other than the body motion of interest occurs, the region of interest can be immediately updated, and a highly accurate biological information signal can be continuously acquired.

[0087] In addition, you can also Figure 14 As shown, instead of using the change (coordinate information), the amount of change (equivalent to the differential value of the change) is used. Figure 14(B) represents the temporal change of the variation (differential value of the change), but for example, a certain threshold value can be set and an abnormality can be detected when the threshold value is exceeded. In addition, the variation shown here is the variation in the vertical direction of the graph (the direction of movement believed to be due to breathing), but for example, the variation of the component perpendicular to it can also be calculated and the information can be used. Since the vertical component is approximately 0 during respiratory activity, it is possible to detect abnormalities with greater sensitivity.

[0088] Furthermore, the techniques of the above-described embodiments and modifications can be applied to various imaging fields including medical applications.

Claims

1. A medical imaging device comprising a biological signal processing system, wherein: The biological signal processing system comprises: a biological information measuring unit provided in or near an examination space of the medical imaging apparatus to measure a state of the subject under examination without contacting the subject under examination, and to acquire a biological information signal corresponding to the measurement of the state of the subject under examination from a given range of the subject; and a signal analysis unit that processes the biological information signal to calculate the motion of the subject, The signal analysis unit includes: An optical flow calculation unit calculates the optical flow using the camera image of the subject. an index calculation unit that calculates, for each of a plurality of regions within the given range of the subject, a band power of a frequency band of motion acquired from the optical flow as a corresponding index related to the intensity of the motion in the region, the band power indicating the magnitude of the motion in the region; and a region of interest selection unit that selects a region of interest for each of the plurality of regions based on the frequency band power as the corresponding index related to the intensity of the motion in the region, The signal analysis unit calculates the motion of the subject using the biological information signal measured from the region of interest, wherein: The region of interest is selected from the plurality of regions based on the frequency band power in the region of interest.

2. The medical imaging device according to claim 1, wherein: The biological information measuring unit includes a distance meter that generates electromagnetic waves or ultrasonic waves and receives reflected waves thereof to measure distance.

3. The medical imaging device according to claim 1, wherein: The biological information measuring unit includes an imaging device installed in the examination space so as to be able to image a predetermined range of the subject from an oblique direction.

4. The medical imaging device according to claim 1, wherein The biological information measuring unit includes a camera, The signal analysis unit calculates the motion of the subject based on temporal changes in the image captured by the camera.

5. The medical imaging device according to claim 1, wherein The biological information measuring unit includes a stereo camera. The signal analysis unit calculates the distance between the stereo camera and the subject based on image data captured by the stereo camera, and calculates the movement of the subject based on a temporal change in the distance.

6. The medical imaging device according to claim 1, wherein: The biological information signal reflects any one of the pulse, pulsation, and body movement of the subject.

7. The medical imaging device according to claim 1, wherein: The index includes any one of a standard deviation SD of the biological information signal at each time and intensity information of the biological information signal.

8. The medical imaging device according to claim 1, wherein: The signal analysis unit further includes an abnormal signal detection unit configured to detect an abnormal value included in the biological information signal. When the abnormal signal detection unit detects the abnormal value, the region of interest selection unit selects another region of interest.

9. A medical imaging system, characterized in that: have: An inspection device having an inspection space where an object to be inspected is arranged; a biological information measuring device provided in or near the examination space to measure a state of the subject under examination without contacting the subject under examination, and to acquire a biological information signal corresponding to the measurement of the state of the subject under examination from a given range of the subject; A display device that displays a graphical user interface (GUI); and a signal analysis device that processes the biological information signal to calculate the motion of the subject, The signal analysis device comprises: an optical flow calculation unit for calculating an optical flow using a camera image of the subject; an index calculation unit configured to calculate, for each of a plurality of regions within the given range of the subject, a band power of a frequency band of motion acquired from the optical flow as a corresponding index related to the intensity of the motion in the region, the band power indicating the magnitude of the motion in the region; and a region of interest selection unit that selects a region of interest for each of the plurality of regions based on the frequency band power as the corresponding index related to the intensity of the motion in the region, The signal analysis device calculates the motion of the subject using the biological information signal measured by the biological information measurement device from the region of interest selected from the plurality of regions based on the frequency band power in the region of interest.

10. The medical imaging system according to claim 9, wherein: The inspection device is a magnetic resonance imaging device, comprising: 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 disposed in a static magnetic field space, receives nuclear magnetic resonance signals generated by the subject, and generates an image of the subject using the nuclear magnetic resonance signals; and a control unit that controls the imaging unit. The control unit controls the operation of the imaging unit using the biological information signal from the region of interest of the subject measured by the biological information measurement device.

11. The medical imaging system according to claim 9, wherein: The inspection device is a magnetic resonance imaging device, comprising: 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 disposed in a static magnetic field space, receives nuclear magnetic resonance signals generated by the subject, and generates an image of the subject using the nuclear magnetic resonance signals. The imaging unit corrects the nuclear magnetic resonance signal or the image using the biological information signal from the region of interest of the subject measured by the biological information measurement device.

12. The medical imaging system according to claim 9, wherein: The device for displaying the GUI displays at least one of the plurality of regions and the region of interest selected by the region of interest selection unit as the GUI.

13. The medical imaging system according to claim 9, wherein: The device for displaying the GUI displays at least one of the biological information signal measured by the biological information measuring device, the analysis result of the signal analyzing device, and the analysis mid-process data.

14. A biological signal processing method comprising processing biological information signals of a subject under examination measured by a non-contact biological information measuring device disposed within or near an examination space of an examination apparatus, to calculate a movement of the subject. The biological signal processing method is characterized by comprising: generating a biological information signal for each of a plurality of regions using the biological information signal measured from a given range of the subject; a step of calculating an optical flow using a camera image of the subject, and calculating, for each of the plurality of regions, a band power of a frequency band of motion obtained from the optical flow as an indicator related to the intensity of the motion for the region, the band power indicating the magnitude of the motion in the region; and A step of selecting a region of interest of the subject from the plurality of regions based on the frequency band power in each of the plurality of regions to calculate the motion of the subject.

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