Patent Application
20240193990
The present application claims priority from Japanese patent application JP-2022-195950 filed on Dec. 7, 2022, the content of which is hereby incorporated by reference into this application.
The present invention relates to a device that processes information regarding a subject's movement during an examination using an image diagnostic device, and particularly, to a technology for monitoring a sudden or non-steady movement during the examination.
In an examination using an image diagnostic device such as a magnetic resonance imaging device (hereinafter, referred to as an MRI device), a subject (patient) undergoes the examination in a lying-down state on a table or the like or in a gently secured state. In a case where the subject moves during this examination, an artifact is generated in an image obtained by the image diagnostic device, which may hinder the diagnosis. In addition, in a case where the subject's movement is significant and sudden, the subject deviates significantly from an examination position, or the subject falls from a bed, the examination should be interrupted, but during the examination, a technician or a doctor (referred to as a user) often has their attention focused on a monitor displaying the image and may not notice such incidents.
Conventionally, as technologies related to the image diagnostic device, a technology for reducing an influence of the subject's movement during the examination on a diagnostic image has been developed and proposed.
For example, various technologies have been proposed such as a technique of understanding in advance a period or a phase of body movements for periodic movements including respiratory movements and heart rate movements among the subject's movements and performing body movement-synchronized imaging based on the period or the phase, or a technique for correcting data obtained after imaging by using body movement information, and suppression of artifacts caused by the body movements has been realized.
As a technology applicable to non-periodic movements, for example, JP2006-346235A has proposed an MRI device in which a body movement is detected by a camera attached within or near an examination space and scanning is stopped or performed again in a case where the body movement is detected. In addition, a technology for estimating the subject's movement from data itself acquired by the image diagnostic device has also been proposed. In a technology described in JP2021-29777A, magnetic resonance data is collected through multi-shots, and presence or absence of the body movement is estimated from low-frequency region data of each shot and used for correction.
Additionally, although it is not a technology related to an image diagnosis, R. Janssen, et al. “Video-based respiration monitoring with automatic region of interest detection”, Physiological Measurement, 37 (1), 100 to 114 discloses a technology for monitoring respiratory movements by using a video image.
In the technology disclosed in JP2006-346235A, a correlation between a still image and a time-phase image acquired at a predetermined time interval is automatically determined, and scanning is stopped or rescanning is performed according to the determination, which cannot specify a position of the subject causing the movement. Therefore, there is a probability of scanning being stopped even in a case where it is not necessary to stop the scanning, for example, in a case where there is a movement in a leg part during imaging of a head part. In addition, since the nature of the movement is not determined or displayed, there is also a probability of an examination technician or a doctor going unnoticed even in a case where there is a significant change in movement that should lead to the interruption of the examination.
In the technology described in R. Janssen, et al. “Video-based respiration monitoring with automatic region of interest detection”, Physiological Measurement, 37 (1), 100 to 114, respiratory movements are separated from noise by determining an ROI of the respiratory movements, and respiratory movement signals are extracted, but movements other than respiratory movements are not considered as a target, and even in a case where this technology is applied to the examination using the image diagnostic device, the effectiveness is limited.
Since, in the technique described in JP2021-29777A, the determination is made based on the signals from an examination part, there is no concern about performing unnecessary processing for the movement of a part that does not affect the examination, but the technique is based on a multi-shot multi-echo sequence as a premise and has limitations in imaging sequences.
An object of the present invention is to provide a technology for enabling accurate understanding of a movement of a region that affects imaging, particularly, processing corresponding to a sudden or non-steady movement, and another object is to reduce an influence of the movement without limitations on an imaging method.
In order to achieve the above objects, the present invention relates to acquiring body movement information based on a signal from a measuring device that measures a movement of a subject, determining a region where the movement of the subject has occurred, calculating a body movement for this region, and determining a non-steady movement.
That is, according to an aspect of the present invention, there is provided a body movement information processing device that receives a signal from a measuring device which measures movement information of a subject disposed in an imaging device and that processes the movement information of the subject, the body movement information processing device comprising: a body movement calculation section configured to calculate a body movement of the subject by using the signal from the measuring device; a region determination section configured to determine a spatial region of a movement of the subject; and a body movement extraction section configured to extract the body movement calculated by the body movement calculation section for the region determined by the region determination section.
In addition, according to another aspect of the present invention, there is provided a magnetic resonance imaging device comprising: an imaging unit configured to measure a nuclear magnetic resonance signal generated by a subject and acquire an image of the subject; and a body movement information processing unit configured to receive a signal from a measuring device that measures information regarding a movement of the subject, and collect movement information of the subject. The body movement information processing unit comprises the same functions as those of the body movement information processing device of the aspect of the present invention and comprises a body movement calculation section configured to calculate a body movement of the subject by using the signal from the measuring device, a region determination section configured to determine a spatial region of the movement of the subject, a body movement extraction section configured to extract the body movement calculated by the body movement calculation section for the region determined by the region determination section.
The magnetic resonance imaging device of the aspect of the present invention also includes a magnetic resonance imaging device including the measuring device as an accessory device.
Furthermore, according to still another aspect of the present invention, there is provided a body movement information processing method of receiving a signal from a measuring device that measures movement information of a subject disposed in an imaging device and processing the movement information of the subject. In the body movement information processing method, a body movement of the subject is calculated using the signal from the measuring device, and a mask for selecting a spatial region of a movement of the subject is used to extract at least one of a periodic movement or a non-steady movement of the subject from the calculated body movement.
According to the aspects of the present invention, by determining the region where the movement of the subject has occurred and extracting the body movement for that region, it is possible to appropriately take measures such as interruption of the examination or re-imaging. By appropriately setting the region, it is possible to present the respiratory movement and other movements by discriminating between the respiratory movement and other movements. Further, according to the aspects of the present invention, the body movement information is acquired by processing the signal from the measuring device, so that the present invention can be applied to any imaging technique.
Hereinafter, embodiments of an imaging system and a body movement information processing device according to the present invention will be described.
As shown in
The medical imaging device 20 is an image diagnostic device such as an MRI device, a CT device, an X-ray diagnostic device, or a PET, comprises the examination space in which the subject is placed, and comprises an imaging unit 21 that performs, for example, operations such as irradiation and reception of high frequency magnetic fields, X-ray irradiation, and detection of transmitted X-rays in order to generate an image of the subject, and a signal processing unit 23 that generates an image such as a tomographic image by using a signal collected by the imaging unit 21 or performs a control or the like necessary for the operations of the imaging unit 21. In addition, a UI unit 25 that includes a display device for displaying the generated image or displaying a GUI for receiving a command from a user (an examination technician or a doctor) is provided.
In the present embodiment, as an example, a case where the medical imaging device 20 is an MRI device will be described. An MRI device 20A has the same configuration as that of a general MRI device, and as shown in
In the MRI device, k-space data necessary for image reconstruction is collected by operating the gradient magnetic field generation system, the transmission system, and the reception system in accordance with a predetermined pulse sequence. The signal processing unit 23 performs image reconstruction operations such as Fourier transformation and sequential reconstruction processing on the k-space data collected by the reception system to generate an MR image. In addition, the signal processing unit 23 performs body movement correction by using the body movement information sent from the body movement information processing device 10, which will be described below, or sends a command to the imaging unit 21 as necessary to stop imaging, perform re-imaging, or the like. The MR image generated by the signal processing unit 23, a GUI for the user to input a command, and the like are displayed on a display device of a console (UI unit) 25 provided with a display device or an input device.
The measuring device 30 consists of one or a plurality of devices that use direct or indirect means to collect the biological information such as respirations, heart rate, and body movements of the subject disposed in the examination space of the imaging device 20, and in the shown example, a respiration monitor 31 such as a balloon attached to the subject, a heart rate monitor 32 such as an electrocardiogram or a heart rate meter, and a body movement monitor 33 are shown. However, in the present invention, the respiration monitor and the heart rate monitor are not essential. The body movement monitor 33 is a device for detecting movements of the subject including respiratory movements, particularly non-steady movements, sudden movements, and the like that are difficult to capture with the respiration monitor or the heart rate monitor, and for example, a camera (including a stereo camera, an infrared camera, or the like) can be used. In the following description, a case where the body movement monitor 33 is a camera will be described as an example.
The biological information measured by the measuring device 30 is presented to the user via a display unit provided in each monitor or the display device of the console 25. The video of the camera 33A is sent to the body movement information processing device 10.
The body movement information processing device 10 uses the video from the camera 33A to detect the movement of the subject, calculate the body movement (a displacement amount and a direction), and present information regarding the time or amount of the body movement that has occurred to the user or transfers this information to the imaging device 20. In this case, a region to be monitored is determined, and information about the determined region is provided. The region to be monitored may be, for example, a region that includes an imaging target part of the subject, or a relatively wide region that includes the imaging target part and other regions. For example, in order to realize a function of performing body movement correction using the body movement information on the image generated by the imaging device 20 (hereinafter, referred to as a body movement correction function), the region including the imaging target part of the subject need only be monitored, and it is preferable to monitor the relatively wide region in order to realize a function of watching a state of the subject, such as in a case where the subject has convulsions or falls from the table (hereinafter, referred to as a watching function).
In order to perform these functions, the body movement information processing device 10 of the present embodiment comprises a region determination section 11, a body movement calculation section 13, a body movement extraction section 15, and a movement information presentation section 17. The body movement information processing device 10 can be configured by, for example, a computer provided with a memory and a CPU/GPU, and a function of each unit of the body movement information processing device 10 can be realized by the CPU or the like through the reading of a program for realizing this function. In addition, some of the functions may be realized by a programmable IC such as ASIC or FPGA. Note that
Hereinafter, an embodiment of processing of the body movement information processing device 10 will be described using a case where the imaging device 20 is an MRI device as an example. An outline of the processing is shown in
First, in a case where an image is read from the camera 33A (S1), the body movement calculation section 13 calculates a movement vector (S2). The movement vector can be calculated using, for example, a known computer vision technology such as optical flow, and the movement vector is calculated for each pixel of the image.
Next, the body movement is calculated using the movement vector (S3). In a case where the camera 33A is a stereo camera, the body movement is obtained as an absolute value because the distance from the camera is obtained, but in a case of one camera, the body movement is calculated as a relative value. The body movement is calculated as a value for each small region obtained by dividing the image into a plurality of regions. In addition, in the calculation of the body movement, in order to distinguish between respiratory movements in which vertical movements of the abdomen are predominant and non-periodic body movements (also simply referred to as a body movement) in which the direction of the movement is not regular, different calculation equations may be used. Details of the calculation technique will be described in the embodiment to be described below.
The body movement extraction section 15 extracts a region that should be monitored by using a mask for extracting the region that should be monitored for body movements (S4). The region determination section 11 determines the region that should be monitored for body movements and sets a mask. The region that should be monitored for body movements differs depending on whether it is the body movement correction function or the watching function, and either one may be used exclusively, but both functions can also be concurrently performed. In such a case, the region determination section 11 determines at least two regions.
The movement information presentation section 17 determines, regarding the body movement of a predetermined region extracted by the body movement extraction section 15, whether the body movement correction is necessary or an alert needs to be issued by using a threshold value of a magnitude or a duration time of the body movement, and sends the obtained body movement information to the imaging device 20 (S5) and presents the obtained body movement information as the alert as necessary (S6).
The body movement information processing device 10 continuously executes the above-described processing S1 to S6 for the video continuously sent from the camera 33A, and provides the body movement information to the imaging device and the user who operates the imaging device.
According to the present embodiment, by determining the region that should be monitored and monitoring the body movement of that region, it is possible to avoid a problem of over-detection such as stopping imaging due to movements of a part that does not affect the imaging. In addition, since an alert is issued even in a case where there is a significant movement that should lead to the interruption of the examination in a part other than the part to be imaged, this alerts the user and allows for a safe examination. Further, according to the present embodiment, since the movement of the subject is detected and processed using only the information from the biological information measuring device independent of the imaging technique of the imaging device, the body movement correction or the watching of the subject can be realized without imposing limitations on the imaging method.
Hereinafter, a more detailed embodiment of the function of the body movement information processing device will be described.
In the present embodiment, a case where both the body movement correction function and the watching function are realized, that is, a case where the respiratory movements and other non-steady body movements are processed will be described.
The body movement calculation section 13 reads a camera image. The image is resized and the original image size is downsized, as necessary (S11). For example, the original size of the camera image is reduced to about ½ to 1/10. By reducing the size of the image in this way, it is possible to reduce the computational load for subsequent processing such as the movement vector calculation, which allows for computational acceleration (real-time presentation). Further, in the succeeding processing, in order to divide one image into a plurality of regions having the same pixel size, image end parts of the resized image, which are remainders, are cut such that both the height and the width are divisible by the number of divisions.
Next, the movement of each pixel is calculated using a computer vision technology such as optical flow (S12). As an optical flow algorithm, for example, a Ferneback method, a Lucas-Kanade method, and the like are known, and any of these methods may be employed. The calculated result represents a change in the pixel positions between frames for each pixel as a velocity vector, and in a case where the height and the width of the image are denoted by an x direction and a y direction, these changes are calculated as a velocity in the x direction (Vx) and a velocity in the y direction (Vy), respectively (S13).
The body movements are calculated using the following equations using the velocity vectors Vx and Vy (S21, S14). In this case, calculations using different calculation equations are performed by taking into consideration the difference in the characteristics between both the movements. The respiratory movements are mainly characterized by predominant vertical movements with respect to a horizontal plane (a table surface) in a case where the subject is in a lying posture on the table, whereas the body movements exhibit movements in irregular directions. In a case where the main direction of the respiratory movement is the y direction, and the respiratory movement is denoted by Vresp, Vresp is represented by Equation (1).
Vresp=Vy (1)
The body movement is denoted by Vbody and is set as follows, for example.
Vbody=Vx
Vbody can take positive and negative values depending on the direction of the body movement. However, in a case where it is desired to obtain the magnitude of the body movement as an absolute value, for example, Equation (2) may be calculated.
Abody=(Vx)2 (2)
Depending on the attachment angle of the camera, the main direction of the respiratory movement may be different from Vx or Vy. In that case, for example, Vresp is calculated by using Equation (3) using 0.
Vresp=Vx cos θ−Vy sin θ (3)
For example, in a case where it is desired to detect other body movements such that the respiratory movement is not included as much as possible by considering that the direction of the body movement is random, the other movements are calculated using Equation (4) by taking into consideration the movement in a direction orthogonal to Vresp.
Vbody=Vx sin θ+Vy cos θ (4)
In a case where it is desired to obtain the magnitude of the body movement as an absolute value, the magnitude is calculated as Abody by using, for example, Equation (5) or Equation (6).
Abody=(Vbody)2 (5)
Abody=(Vx sin θ)2+(Vy cos θ)2 (6)
In the equation, the method of determining θ differs depending on, for example, a positional relationship with the camera, which is an angle of an XY plane with respect to the horizontal plane, and the like. In addition, θ may be determined after analyzing the direction of the respiratory movement for each patient. θ can be appropriately set such that the respiratory movements and the body movements can be detected with high sensitivity, and different values may be used for each position (pixel).
The resized image is divided into small regions, and average values of velocity vectors Vx2 and body movement vectors Ay2 obtained for each pixel within the small region are calculated for each of the divided small regions (S22, S15). As an example, in a case where the pixel size of the camera image, after resizing and removing the remainders, is 360 in width×270 in height, the size of one small region obtained by dividing the camera image into 60 regions is 36×45 pixels, and the average values of the velocity vectors and the body movement vectors are calculated for each small region having such a size.
After the calculation of the body movement, the region determination section 11 determines the region that should be monitored, and the body movement of the region is extracted.
The determination of the region that should be monitored is performed according to, for example, whether it is a region centered on the imaging range (mainly monitoring for the body movement correction function) or a region including the imaging range and other ranges (mainly monitoring for the watching function), and a predetermined region is extracted using a mask. The mask is generated in advance by, for example, a mask generation section 12.
An example of the mask for extracting two regions is shown in
Meanwhile, since the mask 620B is used to extract a region that includes the imaging region and that is wider than the imaging region, and a mask in which the region, in which the subject is present, is set to 1 and other regions are set to 0 can be used.
By monitoring the body movement of the region extracted with the mask 620A, it is possible to detect the body movement that directly affects the imaging, and it is possible to feed back the information to the imaging. In addition, by monitoring the body movement of the region extracted with the mask 620B, it is possible to detect a significant movement of the subject during the examination even in a case where the movement does not directly affect the imaging, and it is possible to achieve the watching function such as issuing an alert.
However, the region determined by the region determination section 11, that is, the mask generated by the mask generation section 12, is not limited to the above-described example, and one or a plurality of (two or more) regions may be set by taking into consideration the examination part, the ease of a subject movement (children or the like), or the like. For example, in a case of a receive coil in which a plurality of small coils are connected, a region where the receive coil is mounted may be divided into a plurality of regions, or may be divided into a region on a head part side including the receive coil, a region on a leg part side including the receive coil, and the like.
Further, the mask need not be a 1/0 binary mask, and may be weighted with a predetermined weight in consideration of a positional relationship with the camera, a sensitivity distribution of the receive coil, and the like. For example, as in a mask 620C shown on the upper side of
In the above description, an example of a spatial mask has been described, but a temporal element and the magnitude of the body movement may further be added. The temporal element is, for example, a temporal mask indicating whether it is at the time of imaging or during the examination including before and after the imaging. One or a plurality of threshold values are set depending on whether or not the magnitude of the body movement affects the image and whether or not the magnitude of the body movement can be processed with the body movement correction. Regarding the threshold value of the magnitude of the body movement, the magnitude of the body movement that affects the image may be obtained in advance through imaging or simulation using a phantom.
Instead of the three-dimensional mask, there may be cases where a mask in which the spatial element and the temporal element are combined or a mask in which the spatial element and the magnitude of the body movement are combined is used.
The body movement information processing device 10 (movement information presentation section 17) monitors the body movement for the region extracted with the above-described mask (S17).
An example of the detected body movement information is shown in
The movement information presentation section 17 generates an alert based on the obtained body movement information. Therefore, the movement information presentation section 17 (monitoring window generation section 16) sets a window for conditions for issuing an alert regarding the body movement, determines whether the body movement corresponds to any of the conditions, and issues an alert. The window may be a window having only a threshold value of the magnitude of the body movement as shown in the graph of
The setting of the windows for monitoring is not limited to the above example and is arbitrary. For example, an alert may be issued in a case where the amplitude of the body movement exceeds a predetermined threshold value regardless of the length of the duration time. Further, a window for watching function and a window for body movement correction may be prepared. In a case where the window for body movement correction is set, it is possible to reflect the fact that there is a body movement that, while not triggering an alert, still affects the imaging, and the time thereof in the operation of the imaging unit 21. For example, the imaging unit 21 can perform processing such as discarding measurement data of the time when the body movement has occurred, regaining the measurement data, and correcting the measurement data at that time based on the body movement information.
The method of issuing the alert is not particularly limited, and for example, the alert may be issued in the form of a speech bubble 1020 as shown in
By issuing such an alert, it is possible to inform the user who is focused on other work that there has been an abnormal movement. In addition, by setting an appropriate window, it is possible to continue imaging as it is for movements that do not require an alert to be issued from the viewpoint of subject safety, such as in a case where the subject sneezes or coughs temporarily, and it is possible to avoid unnecessary interruptions in imaging.
In the watching function, in addition to non-steady body movements, steady respiratory movements are simultaneously detected and displayed for watching. In that case, processing for calculating the respiratory rate is further performed on the respiratory movements.
In this processing, first, the velocity vector Vresp is used to perform an integration in a time direction from a certain past time t1 to a current time t2 according to Equation (7), and a displacement x is calculated for each region (S24).
x=Σ
t=t1
t2
Vresp(t) (7)
In determining a region that should be detected for the respiratory movements, for example, a region of the chest or abdomen is extracted using a mask. The mask is generated in advance by, for example, the mask generation section 12.
Regarding the method of determining the region that should be detected for the respiratory movements, the region that should be detected may be determined after calculating the respiratory movements for all the small regions within the camera image. For example, band power (BP) is calculated as a respiratory index (S25). BP is calculated by using Equation (8) to calculate a power spectral density P (f) for a frequency band that sufficiently includes respiratory components, for example, a frequency band of 0.1 to 0.5 Hz (equivalent to 6 to 30 breaths per minute when converted into the respiratory rate), and then calculating an average power within this frequency band as BP (Equation (8)).
In the equation, Δt is a sampling interval, and N is the number of sampling points.
The BP is calculated for all the small regions for which the velocity vectors are calculated, and for example, a region where BP is maximized is set as a respiratory detection ROI (S26). A respiratory waveform is obtained from displacement information (calculated in S24) obtained for the region set as the respiratory detection ROI, and the respiratory rate (per minute) is calculated (S27). The respiratory rate for one minute may be obtained by applying FFT to the respiratory waveform, calculating a peak frequency (Hz), and calculating 60 (sec)/peak frequency (Hz). In addition, the respiratory rate for one minute may be obtained from the time interval between the maximum value and the minimum value of the respiratory waveform. Further, a respiratory phase may be calculated together with the respiratory rate.
The movement information presentation section 17 sends the obtained respiratory rate to the imaging device 20 and displays the obtained respiratory rate on the display device (S28). The respiratory waveform may be displayed together with the respiratory rate. This information can be used not only for the user to understand the respiratory state of the subject but also for respiratory-synchronized imaging or the like by using the respiratory phase.
For example, as shown in
A part of the k-space data is thinned out to perform image reconstruction, and the body movement is corrected (S7). As a technique for correcting the body movement, for example, parallel imaging reconstruction, sequential reconstruction in which iterative computational operations are performed while maintaining consistency of the measurement data, and the like have been developed, and these techniques can be used. In addition, in a case where there is a large amount of data at the time when the body movement has occurred, in a case where the data is low-frequency region data of the k-space by which image contrast is determined, or the like, the imaging unit 21 may be controlled and re-imaging may be performed to collect data when the body movement has occurred.
As described above, according to the present embodiment, by extracting and monitoring body movements of a predetermined region using a plurality of masks, it is possible to appropriately utilize the body movement information obtained from the extraction and monitoring for the body movement correction or the watching, which makes it possible to reduce unnecessary processing caused by over-detection.
Further, as the mask, by adding the magnitude of the body movement and the temporal element in addition to the spatial element, it is possible to allocate more appropriate functions.
In the above embodiment, in order to perform both the body movement correction function and the watching function, two body movement monitoring regions are set, and the body movements of the two regions are monitored using a mask corresponding to each region, but it is also possible to realize the body movement correction function and the watching function by setting only one region and using the body movement information extracted for that region. In addition, although a case where two functions are realized has been described in the present embodiment, the present invention also includes an imaging system that realizes only the watching function of monitoring body movements other than respiratory movements or only the body movement correction function.
Further, although the embodiment has been described using a case where the imaging device is an MRI device as an example, the present invention is not limited to the MRI device, and the present invention can be applied to various image diagnostic devices in which body movements are a problem, and the same effect can be obtained. For example, even in a case where the imaging device is an X-ray CT device, it is possible to measure the body movement of the subject, which has occurred during the rotation of a scanner, with a camera installed near the scanner, detect the body movement from the camera image, and extract the body movement of a predetermined region with a predetermined mask, and it is possible to understand at which point in time (angle) during the scanning the body movement that affects the examination or the imaging has occurred.
Next, an embodiment of the MRI device will be described. The MRI device of the present embodiment is characterized in that a known MRI device is provided with the functions of the body movement information processing device described above, and comprises, as shown in
The configuration of the imaging unit 21 is the same as the configuration shown in
Similar to the body movement information processing device 10 shown in
The body movement information processing unit 270 acquires the body movement information detected by the measuring device 30 and performs processing necessary for the body movement correction and the watching and information presentation. Specifically, the processing as shown in
The movement information presentation section 277 determines, regarding the body movement of a predetermined region extracted by the body movement extraction section 275, whether the body movement correction is necessary or an alert needs to be issued by using the threshold value of the magnitude or the duration time of the body movement, and transfers the obtained body movement information to the imaging unit 21 (S5) and presents the obtained body movement information as the alert as necessary (S6).
According to the present embodiment, by adding a function (body movement information processing) of processing information from the measuring device as a signal processing function of the MRI device, it is possible to use the detected body movement to perform prompt responses to the subject or reflection in imaging operations.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2022-195950 | Dec 2022 | JP | national |
