Methods, devices, and storage media for monitoring motion of an imaged site under an MRI environment

Abstract

The application relates to the field of medical image processing, and provides a method, equipment and computer readable storage medium for monitoring the movement of an imaging part in an MRI environment. The method comprises the following steps: acquiring a first image of an imaging part of a subject in real time, wherein the first image is a camera point cloud image obtained by an image acquisition device shooting the imaging part of the subject; acquiring a second image of the imaging part of the subject before the image acquisition device acquires the first image of the imaging part of the subject in real time, wherein the second image is an MRI point cloud image obtained by an MRI system scanning the imaging part of the subject; transforming the point cloud coordinates in the first image to an MRI coordinate system according to a coordinate transformation matrix between a camera coordinate system and the MRI coordinate system; and calculating the spatial six-degree-of-freedom data of the imaging part of the subject in the MRI coordinate system according to a spatial transformation matrix between two adjacent first images, so as to obtain the movement information of the imaging part of the subject in the MRI coordinate system.

Description

Technical Field

[0001] This invention relates to the field of medical image processing, and in particular to a method, device, and storage medium for monitoring motion of imaging sites in an MRI environment. Background Technology

[0002] Magnetic Resonance Imaging (MRI) is a crucial tool for detecting pathological changes in human tissues. For example, MRI can detect pathological changes in important tissues such as the brain, soft tissues, and cardiovascular system, allowing for appropriate treatment. However, MRI scans are slow, taking several minutes to tens of minutes per scan, and require precise control over the movement of the imaging area. Excessive movement can lead to blurred images, affecting clinical diagnosis. Therefore, monitoring imaging area movement during MRI to provide timely alerts when movement exceeds a certain range is essential. Current methods for monitoring imaging area movement in MRI involve acquiring images of the subject's imaging area (e.g., the head) using image acquisition equipment and judging whether movement has occurred. However, these methods only qualitatively observe whether movement has occurred and the approximate extent of movement during the MRI examination; they cannot quantitatively reflect the actual movement of the imaging area. Summary of the Invention

[0003] This application provides a method, device, and computer-readable storage medium for monitoring the motion of imaging sites in an MRI environment, which can monitor the actual motion of the imaging sites of the subject.

[0004] On the one hand, this application provides a method for monitoring the motion of an imaging site in an MRI environment, including:

[0005] The first image of the imaging area of ​​the subject is acquired in real time. The first image is a camera point cloud image captured by the image acquisition device of the imaging area of ​​the subject.

[0006] Before the image acquisition device acquires the first image of the subject's imaging area in real time, a second image of the subject's imaging area is acquired. The second image is an MRI point cloud image obtained by the magnetic resonance imaging (MRI) system scanning the subject's imaging area.

[0007] Based on the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system, the point cloud coordinates in the first image are transformed to the MRI coordinate system;

[0008] Based on the spatial transformation matrix between two adjacent frames of the first image, the spatial six degrees of freedom data of the imaging part of the subject are calculated in the MRI coordinate system to obtain the motion information of the imaging part of the subject in the MRI coordinate system.

[0009] On the other hand, this application provides a device for monitoring the motion of an imaging site in an MRI environment, comprising:

[0010] The first acquisition module is used to acquire a first image of the imaging part of the subject in real time. The first image is a camera point cloud image captured by the image acquisition device of the imaging part of the subject.

[0011] The second acquisition module is used to acquire a second image of the imaging area of ​​the subject before the image acquisition device acquires the first image of the imaging area of ​​the subject in real time. The second image is an MRI point cloud image obtained by the magnetic resonance imaging (MRI) system scanning the imaging area of ​​the subject.

[0012] The first calculation module is used to transform the point cloud coordinates in the first image to the MRI coordinate system according to the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system.

[0013] The second calculation module is used to calculate the spatial six degrees of freedom data of the imaging part of the subject in the MRI coordinate system based on the spatial transformation matrix between two adjacent frames of the first image, so as to obtain the motion information of the imaging part of the subject in the MRI coordinate system.

[0014] Thirdly, this application provides an apparatus comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the technical solution of the above-described method for monitoring motion of imaging sites in an MRI environment.

[0015] Fourthly, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the technical solution of the above-described method for monitoring motion of an imaging site in an MRI environment.

[0016] As can be seen from the technical solution provided in this application, after acquiring the first and second images of the subject's imaging area in real time, the point cloud coordinates in the first image are transformed to the MRI coordinate system according to the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system. Finally, based on the spatial transformation matrix between two adjacent frames of the first image, the six degrees of freedom data of the subject's imaging area are calculated in the MRI coordinate system. Unlike existing technologies that mainly obtain the motion information of the subject's imaging area in the two-dimensional direction and cannot reflect the true motion of the subject's imaging area, this application can determine the true information of the subject's imaging area by acquiring the six degrees of freedom data of the subject's imaging area, thereby providing timely reminders and corrections when the motion range of the subject's imaging area exceeds a preset threshold. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a method for monitoring motion of an imaging site in an MRI environment, as provided in an embodiment of this application.

[0019] Figure 2 This is a schematic diagram of the surface information of the subject's face obtained in real time by an image acquisition device, as provided in an embodiment of this application.

[0020] Figure 3 This is a schematic diagram of the surface information of the subject's face obtained when the MRI system provided in this application scans the subject's head;

[0021] Figure 4 This is a schematic diagram illustrating the cross-calibration result obtained by cross-calibrating the first image and the second image according to an embodiment of this application.

[0022] Figure 5 This is a schematic diagram of the six degrees of freedom of the imaging site of the subject in the MRI coordinate system provided in the embodiments of this application;

[0023] Figure 6 This is a schematic diagram of the spatial six degrees of freedom data change curves of the subject's head over a period of time when the imaging site is the subject's head, as provided in the embodiments of this application;

[0024] Figure 7 This is a schematic diagram of the structure of the monitoring device for the motion of the imaging part in an MRI environment provided in the embodiments of this application;

[0025] Figure 8 This is a schematic diagram of the device provided in the embodiments of this application. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] In this specification, adjectives such as "first" and "second" are used only to distinguish one element or action from another, without necessarily requiring or implying any actual such relationship or order. Where circumstances permit, reference to an element, component, or step (etc.) should not be construed as limited to only one element, component, or step, but may include one or more of the elements, components, or steps, etc.

[0028] For ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn to actual scale.

[0029] This application proposes a method for monitoring motion of imaging sites in an MRI environment, as shown in the attached figure. Figure 1 As shown, the method for monitoring motion of the imaging site under MRI mainly includes steps S101 to S104, which are detailed below:

[0030] Step S101: Acquire the first image of the imaging area of ​​the subject in real time, wherein the first image is a camera point cloud image of the imaging area of ​​the subject captured by the image acquisition device.

[0031] In this embodiment, the subject refers to a person undergoing an MRI medical examination or a normal volunteer undergoing brain functional imaging. The imaging site is also the area scanned by the MRI system, such as the head, waist, or legs. The image acquisition device can be a 3D structured optics module, such as a 3D camera or depth camera, or it can be a binocular camera, a TOF (Time-Of-Flight) camera (including iTOF cameras and dTOF cameras), etc. This application does not limit the type of image acquisition device. In specific implementation, the subject lies on the MRI scanning table, and the imaging site, such as the head, is placed at the center of the head coil. The image acquisition device, such as the 3D structured optics module with electromagnetic shielding, is placed above the head coil or other coils (these other coils may differ in shape, size, or even material because the subject's imaging site is different from the head). The lens of the 3D structured optics module points to the part of the subject's imaging site that is not obstructed by the coils (head coil or other coils). The scanning bed is moved to the scanning position, and the monitoring system is activated to acquire the first image of the subject's imaging area in real time. This image is the camera point cloud image captured by the image acquisition device of the subject's imaging area. For example, when the imaging area is the subject's head, the first image contains surface information of the subject's face. Figure 2 The image shown is an example of surface information of a subject's face obtained in real time through an image acquisition device.

[0032] It should be noted that the aforementioned 3D structural optical modules and other image acquisition devices have undergone electromagnetic shielding treatment, which mainly includes removing ferromagnetic materials from the 3D structural optical modules and other image acquisition devices, wrapping all their components with non-magnetic metal materials, and using shielded cables.

[0033] Step S102: Before the image acquisition device acquires the first image of the subject's imaging area in real time, a second image of the subject's imaging area is acquired, wherein the second image is an MRI point cloud image obtained by the magnetic resonance imaging (MRI) system scanning the subject's imaging area.

[0034] It should be noted that step S102 in the above embodiment actually occurs before step S101; that is, a second image of the subject's imaging area is first acquired using the MRI system, and then a first image of the subject's imaging area is acquired in real time using an image acquisition device. Figure 3 The image shows an example of surface information of a subject's face obtained when an MRI system scans the subject's head.

[0035] Step S103: Transform the point cloud coordinates in the first image to the MRI coordinate system according to the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system.

[0036] The camera coordinate system refers to the coordinate system of the aforementioned image acquisition device, while the MRI coordinate system refers to the coordinate system of the MRI system. Since these two coordinate systems are independent, and for the convenience of the research, it is necessary to unify the images obtained from both coordinate systems into a single coordinate system. In this embodiment, the point cloud coordinates in the first image can be transformed to the MRI coordinate system based on the coordinate transformation matrix between the camera and MRI coordinate systems. This coordinate transformation matrix can be obtained beforehand; that is, it is acquired before transforming the point cloud coordinates in the first image to the MRI coordinate system. In practice, obtaining the coordinate transformation matrix involves cross-calibrating (or spatially registering) the first image of the subject's imaging area acquired in real-time by image acquisition devices such as 3D structural optics modules with the second image of the subject's imaging area acquired in real-time by the MRI system. The coordinate transformation matrix between the camera and MRI coordinate systems can be obtained through the cross-calibration result. Figure 4 The image shown is an example of cross-calibrating the first image (i.e., the real-world camera point cloud image in the figure) with the second image (i.e., the MRI point cloud image in the figure) to obtain the cross-calibration result.

[0037] As an embodiment of this application, the above-mentioned acquisition of the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system can be achieved through steps S1031 to S1033, as detailed below:

[0038] Step S1031: Obtain the first coordinates of multiple first reference points in the camera coordinate system from at least one target image frame, wherein at least one target image frame is at least one image frame of a first image or a second image.

[0039] Step S1032: Obtain the second coordinates of multiple first reference points in the MRI coordinate system.

[0040] In the above embodiments, the first reference point can be a marker point with distinct features in either the first or second image. During image cross-calibration, these marker points with distinct features can be used as feature points for matching.

[0041] Step S1033: Determine the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system based on the first coordinate and the second coordinate.

[0042] Specifically, as an embodiment of this application, determining the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system based on the first coordinate and the second coordinate can be as follows: dividing the first coordinate and the second coordinate into multiple coordinate pairs, each coordinate pair including a first coordinate and a second coordinate, and the first coordinate and the second coordinate in each coordinate pair belonging to the same first reference point; substituting the first coordinate and the second coordinate in each coordinate pair into a preset target matrix function to obtain multiple equations corresponding to multiple coordinate pairs; determining the parameter values ​​of the target matrix function based on the multiple equations; substituting the parameter values ​​into the target matrix function to obtain the target matrix determined by the parameter values ​​as the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system, wherein the target matrix function is a matrix with unknown parameters.

[0043] Since the determination of the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system based on the first and second coordinates is actually based on the Iterative Closest Points (ICP) algorithm, i.e., the determination of the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system is a cyclic iterative process, the method of the above embodiment further includes: before obtaining the target matrix determined by the parameter values ​​as the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system, obtaining the first coordinates of multiple second reference points in the camera coordinate system from at least one target image frame; obtaining the second coordinates of multiple second reference points in the MRI coordinate system; substituting the first coordinates of the multiple second reference points into the target matrix function respectively to obtain multiple estimated function values, each estimated function value corresponding to a second reference point; for each estimated function value, obtaining the absolute value of the difference between the estimated function value and the second coordinate of the corresponding second reference point as the error value corresponding to the estimated function value; and determining that the maximum value among the error values ​​corresponding to the multiple estimated function values ​​is less than or equal to a preset error threshold. When the parameter values ​​of the target matrix function include the rotation matrix R and translation vector T between the camera coordinate system and the MRI coordinate system, the optimal solution for the parameter values ​​of the target matrix function is actually found using the least squares method. That is, the rotation matrix R and translation vector T between the camera coordinate system and the MRI coordinate system are found to be minimized when the error value corresponding to the estimated function value is minimized using the least squares method. The image registration described above can be based not only on the ICP algorithm, but also on the Coherent Point Drift (CPD) algorithm, the Normal Distributions Transform (NDT) algorithm, and the phase correlation algorithm, etc. This application does not limit the specific algorithm; the above is merely an example based on the ICP algorithm.

[0044] Step S104: Based on the spatial transformation matrix between two adjacent first images, calculate the six degrees of freedom data of the imaging part of the subject in the MRI coordinate system to obtain the motion information of the imaging part of the subject in the MRI coordinate system.

[0045] It should be noted that the method for solving the spatial transformation matrix between two adjacent first images is similar to the method for solving the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system in the aforementioned embodiment. That is, the spatial transformation matrix between two adjacent first images can also be solved based on the Iterative Closest Point (ICP) algorithm. After obtaining the spatial transformation matrix between two adjacent first images, the six degrees of freedom data of the subject's imaging area can be calculated in the MRI coordinate system based on the spatial transformation matrix between the two adjacent first images, thus obtaining the motion information of the subject's imaging area in the MRI coordinate system. Specifically, if the spatial transformation matrix between two adjacent first images is represented by H, and the matrix corresponding to the previous first image between the two adjacent first images is represented by I... j This indicates that the matrix corresponding to the first image in the next frame uses I. j+1 Indicate, then I j+1 =HI j Each frame of the first image contains six degrees of freedom (DOF) spatial data of the subject's imaging area: the translations x, y, and z along the X, Y, and Z axes, and the rotations α, β, and θ around these axes. Since the six DDF data are calculated in the MRI coordinate system, the motion information of the subject's imaging area in the MRI coordinate system can be clearly obtained from the two first images; that is, the translations x, y, and z along the X, Y, and Z axes, and the rotations α, β, and θ around these axes. Figure 5 As shown, by comparing the six degrees of freedom data of the subject's imaging area in the MRI coordinate system of the first image in two consecutive frames, it can be found that the subject's imaging area was translated by 0.2839 mm, 0.9946 mm, and 0.4693 mm along the X, Y, and Z axes, respectively, and rotated by 0.9734°, 2.9278°, and 3.3842° around the X, Y, and Z axes, respectively. Figure 6 The image shown is a schematic diagram illustrating the spatial six degrees of freedom data changes of the subject's head over a period of time when the imaging site is the subject's head. Furthermore, if the motion information of the subject's imaging site in the MRI coordinate system exceeds a preset threshold, a prompt message is issued to remind the subject to keep the imaging site still or for the MRI operator to pause the MRI examination.

[0046] From the above appendix Figure 1As illustrated in the example of the MRI-based method for monitoring motion of the imaging area, after acquiring the first and second images of the subject's imaging area in real time, the point cloud coordinates in the first image are transformed to the MRI coordinate system using a coordinate transformation matrix between the camera coordinate system and the MRI coordinate system. Finally, based on the spatial transformation matrix between two adjacent frames of the first image, the six degrees of freedom spatial data of the subject's imaging area are calculated in the MRI coordinate system. Unlike existing technologies that primarily obtain two-dimensional motion information of the subject's imaging area and cannot reflect the true motion of the subject's imaging area, this application, by acquiring the six degrees of freedom spatial data of the subject's imaging area, can determine the true information of the subject's imaging area, thereby providing timely alerts and corrections when the motion range of the subject's imaging area exceeds a preset threshold.

[0047] Please see the appendix Figure 7 This application provides a device for monitoring the motion of an imaging site in an MRI environment. It may include a first acquisition module 701, a second acquisition module 702, a first calculation module 703, and a second calculation module 704, as detailed below:

[0048] The first acquisition module 701 is used to acquire a first image of the imaging part of the subject in real time, wherein the first image is a camera point cloud image captured by the image acquisition device of the imaging part of the subject.

[0049] The second acquisition module 702 is used to acquire a second image of the imaging part of the subject before the image acquisition device acquires the first image of the imaging part of the subject in real time. The second image is an MRI point cloud image obtained by the magnetic resonance imaging (MRI) system scanning the imaging part of the subject.

[0050] The first calculation module 703 is used to transform the point cloud coordinates in the first image to the MRI coordinate system according to the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system.

[0051] The second calculation module 704 is used to calculate the spatial six degrees of freedom data of the imaging part of the subject in the MRI coordinate system based on the spatial transformation matrix between two adjacent frames of the first image, so as to obtain the motion information of the imaging part of the subject in the MRI coordinate system.

[0052] Optionally, Figure 7 The example MRI-based motion monitoring device may further include a third acquisition module for the first calculation module 703 to acquire the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system before transforming the point cloud coordinates in the first image to the MRI coordinate system.

[0053] Optionally, the third acquisition module in the above example may include a first coordinate acquisition unit, a second coordinate acquisition unit, and a first determination unit, wherein:

[0054] The first coordinate acquisition unit is used to acquire the first coordinates of a plurality of first reference points in the camera coordinate system from at least one target image frame, wherein the at least one target image frame is at least one image frame of a first image or a second image;

[0055] The second coordinate acquisition unit is used to acquire the second coordinates of multiple first reference points in the MRI coordinate system;

[0056] The first determining unit is used to determine the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system based on the first coordinates of multiple first reference points in the camera coordinate system and the second coordinates of multiple first reference points in the MRI coordinate system.

[0057] Optionally, the first determining unit in the above example may include a partitioning unit, a substitution unit, a second determining unit, and a third determining unit, wherein:

[0058] The dividing unit is used to divide the first coordinate and the second coordinate into multiple coordinate pairs. Each coordinate pair includes a first coordinate and a second coordinate, and the first coordinate and the second coordinate in each coordinate pair belong to the same first reference point.

[0059] The substitution unit is used to substitute the first and second coordinates of each coordinate pair into a preset target matrix function, where the target matrix function is a matrix with unknown parameters, to obtain multiple equations corresponding to multiple coordinate pairs.

[0060] The second determining unit is used to determine the parameter values ​​of the target matrix function based on multiple equations;

[0061] The third determining unit is used to substitute the parameter values ​​into the target matrix function to obtain the target matrix determined by the parameter values ​​as the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system.

[0062] Optionally, Figure 7 The example MRI-based device for monitoring motion of the imaging site may further include a fourth acquisition module, a fifth acquisition module, a sixth acquisition module, a seventh acquisition module, and an error value determination module, wherein:

[0063] The fourth acquisition module is used to acquire the first coordinates of multiple second reference points in the camera coordinate system from at least one target image frame before the third determining unit obtains the target matrix determined by the parameter values ​​as the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system.

[0064] The fifth acquisition module is used to acquire the second coordinates of multiple second reference points in the MRI coordinate system;

[0065] The sixth acquisition module is used to substitute the first coordinates of multiple second reference points into the target matrix function to obtain multiple estimated function values, each of which corresponds to a second reference point;

[0066] The seventh acquisition module is used to obtain, for each estimated function value, the absolute value of the difference between the estimated function value and the second coordinate of the corresponding second reference point as the error value corresponding to the estimated function value;

[0067] The error value determination module is used to determine whether the maximum value among the error values ​​corresponding to multiple estimated function values ​​is less than or equal to a preset error threshold.

[0068] Optionally, the parameter values ​​of the target matrix function in the above example include the rotation matrix and translation vector between the camera coordinate system and the MRI coordinate system.

[0069] Optionally, Figure 7 The example MRI-based motion monitoring device may also include a prompting module, which issues a prompt if the motion information of the subject's imaging area in the MRI coordinate system exceeds a preset threshold.

[0070] As illustrated in the attached figures, the monitoring device for motion monitoring of the imaging area in an MRI environment, after acquiring the first and second images of the subject's imaging area in real time, transforms the point cloud coordinates in the first image to the MRI coordinate system using the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system. Finally, based on the spatial transformation matrix between two adjacent frames of the first image, the six degrees of freedom spatial data of the subject's imaging area are calculated in the MRI coordinate system. Unlike existing technologies that primarily obtain two-dimensional motion information of the subject's imaging area and cannot reflect the true motion of the subject's imaging area, this application, by acquiring the six degrees of freedom spatial data of the subject's imaging area, can determine the true information of the subject's imaging area, thereby providing timely alerts and corrections when the motion range of the subject's imaging area exceeds a preset threshold.

[0071] Figure 8 This is a schematic diagram of the structure of a device provided in one embodiment of this application. For example... Figure 8 As shown, the device 8 in this embodiment mainly includes: a processor 80, a memory 81, and a computer program 82 stored in the memory 81 and executable on the processor 80, such as a program for a method of monitoring motion of an imaging site in an MRI environment. When the processor 80 executes the computer program 82, it implements the steps in the above-described embodiment of the method for monitoring motion of an imaging site in an MRI environment, for example... Figure 1 The steps S101 to S102 are shown. Alternatively, when the processor 80 executes the computer program 82, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 7The functions of the first acquisition module 701, the second acquisition module 702, the first calculation module 703, and the second calculation module 704 are shown.

[0072] For example, the computer program 82 of the method for monitoring the motion of an imaging site in an MRI environment mainly includes: acquiring a first image of the imaging site of the subject in real time, wherein the first image is a camera point cloud image captured by an image acquisition device of the imaging site of the subject; acquiring a second image of the imaging site of the subject before the image acquisition device acquires the first image of the imaging site of the subject in real time, wherein the second image is an MRI point cloud image obtained by scanning the imaging site of the subject by a magnetic resonance imaging (MRI) system; transforming the point cloud coordinates in the first image to the MRI coordinate system according to the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system; calculating the six degrees of freedom data of the imaging site of the subject in the MRI coordinate system according to the spatial transformation matrix between two adjacent frames of the first image, thereby obtaining the motion information of the imaging site of the subject in the MRI coordinate system. The computer program 82 can be divided into one or more modules / units, one or more modules / units are stored in the memory 81 and executed by the processor 80 to complete this application. One or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 82 in the device 8. For example, computer program 82 can be divided into the functions of a first acquisition module 701, a second acquisition module 702, a first calculation module 703, and a second calculation module 704 (modules in the virtual device). The specific functions of each module are as follows: The first acquisition module 701 is used to acquire a first image of the imaging area of ​​the subject in real time, wherein the first image is a camera point cloud image obtained by the image acquisition device of the imaging area of ​​the subject; the second acquisition module 702 is used to acquire a second image of the imaging area of ​​the subject before the image acquisition device acquires the first image of the imaging area of ​​the subject in real time, wherein the second image is an MRI point cloud image obtained by the magnetic resonance imaging (MRI) system scanning the imaging area of ​​the subject; the first calculation module 703 is used to transform the point cloud coordinates in the first image to the MRI coordinate system according to the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system; the second calculation module 704 is used to calculate the spatial six degrees of freedom data of the imaging area of ​​the subject in the MRI coordinate system according to the spatial transformation matrix between two adjacent frames of the first image, and obtain the motion information of the imaging area of ​​the subject in the MRI coordinate system.

[0073] Device 8 may include, but is not limited to, processor 80 and memory 81. Those skilled in the art will understand that... Figure 2This is merely an example of device 8 and does not constitute a limitation on device 8. It may include more or fewer components than shown, or combine certain components, or different components. For example, a computing device may also include input / output devices, network access devices, buses, etc.

[0074] The processor 80 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0075] The memory 81 can be an internal storage unit of the device 8, such as a hard disk or RAM of the device 8. The memory 81 can also be an external storage device of the device 8, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the device 8. Furthermore, the memory 81 can include both internal and external storage units of the device 8. The memory 81 is used to store computer programs and other programs and data required by the device. The memory 81 can also be used to temporarily store data that has been output or will be output.

[0076] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed. That is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above-described device can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0077] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0078] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0079] In the embodiments provided in this application, it should be understood that the disclosed apparatus / device and method can be implemented in other ways. For example, the apparatus / device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0080] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0081] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0082] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a non-transitory computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments of this application can also be implemented by a computer program instructing related hardware. The computer program for the method of monitoring the motion of the imaging part in an MRI environment can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above-described method embodiments, namely, acquiring a first image of the imaging part of the subject in real time, wherein the first image is a camera point cloud image captured by an image acquisition device of the imaging part of the subject; acquiring a second image of the imaging part of the subject before the image acquisition device acquires the first image of the imaging part of the subject in real time, wherein the second image is an MRI point cloud image obtained by scanning the imaging part of the subject by a magnetic resonance imaging (MRI) system; transforming the point cloud coordinates in the first image to the MRI coordinate system according to the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system; calculating the six degrees of freedom data of the imaging part of the subject in the MRI coordinate system according to the spatial transformation matrix between two adjacent frames of the first image, thereby obtaining the motion information of the imaging part of the subject in the MRI coordinate system. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. Non-transitory computer-readable media may include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in non-transitory computer-readable media may be appropriately added to or subtracted from the requirements of legislation and patent practice in different jurisdictions. For example, in some jurisdictions, according to legislation and patent practice, non-transitory computer-readable media do not include electrical carrier signals and telecommunication signals. The above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above description is only a specific embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this invention.

Claims

1. A method for monitoring motion of an imaging site in an MRI environment, characterized in that, The method includes: The first image of the imaging area of ​​the subject is acquired in real time. The first image is a camera point cloud image captured by the image acquisition device of the imaging area of ​​the subject. The image acquisition device is a 3D structure optical module that has undergone electromagnetic shielding. Before the image acquisition device acquires the first image of the subject's imaging area in real time, a second image of the subject's imaging area is acquired. The second image is an MRI point cloud image obtained by the magnetic resonance imaging (MRI) system scanning the subject's imaging area. The point cloud coordinates in the first image are transformed to the MRI coordinate system based on the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system. Based on the spatial transformation matrix between two adjacent frames of the first image, the spatial six degrees of freedom data of the imaging part of the subject are calculated in the MRI coordinate system to obtain the motion information of the imaging part of the subject in the MRI coordinate system. Before obtaining the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system, the first coordinates of multiple second reference points in the camera coordinate system are obtained from at least one target image frame; Obtain the second coordinates of the plurality of second reference points in the MRI coordinate system; Substitute the first coordinates of the plurality of second reference points into the preset target matrix function to obtain a plurality of estimated function values, each of which corresponds to a second reference point. For each estimated function value, the absolute value of the difference between the estimated function value and the second coordinate of the corresponding second reference point is obtained as the error value corresponding to the estimated function value; The maximum value among the error values ​​corresponding to the plurality of estimated function values ​​is determined to be less than or equal to a preset error threshold.

2. The method for monitoring motion of an imaging site in an MRI environment as described in claim 1, characterized in that, The method further includes: Before transforming the point cloud coordinates in the first image to the MRI coordinate system, obtain the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system.

3. The method for monitoring motion of an imaging site in an MRI environment as described in claim 2, characterized in that, The step of obtaining the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system includes: Obtain the first coordinates of multiple first reference points in the camera coordinate system from at least one target image frame, wherein the at least one target image frame is at least one image frame of the first image or the second image; Obtain the second coordinates of the plurality of first reference points in the MRI coordinate system; Based on the first coordinate and the second coordinate, determine the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system.

4. The method for monitoring motion of an imaging site in an MRI environment as described in claim 3, characterized in that, Determining the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system based on the first coordinate and the second coordinate includes: The first coordinate and the second coordinate are divided into multiple coordinate pairs. Each coordinate pair includes a first coordinate and a second coordinate, and the first coordinate and the second coordinate in each coordinate pair belong to the same first reference point. Substituting the first and second coordinates of each coordinate pair into the preset target matrix function yields multiple equations corresponding to the multiple coordinate pairs. The preset target matrix function is a matrix with unknown parameters. Based on the multiple equations, determine the parameter values ​​of the target matrix function; Substituting the parameter values ​​into the target matrix function yields a target matrix determined by the parameter values, which serves as the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system.

5. The method for monitoring motion of an imaging site in an MRI environment as described in claim 4, characterized in that, The parameter values ​​of the target matrix function include the rotation matrix and translation vector between the camera coordinate system and the MRI coordinate system.

6. The method for monitoring motion of an imaging site in an MRI environment as described in any one of claims 1 to 5, characterized in that, The method further includes: If the motion information of the imaging area of ​​the subject in the MRI coordinate system exceeds a preset threshold, a prompt message will be issued.

7. A device for monitoring motion of an imaging site in an MRI environment, characterized in that, The device includes: The first acquisition module is used to acquire a first image of the imaging part of the subject in real time. The first image is a camera point cloud image captured by the image acquisition device of the imaging part of the subject. The image acquisition device is a 3D structure optical module that has undergone electromagnetic shielding. The second acquisition module is used to acquire a second image of the imaging area of ​​the subject before the image acquisition device acquires the first image of the imaging area of ​​the subject in real time. The second image is an MRI point cloud image obtained by the magnetic resonance imaging (MRI) system scanning the imaging area of ​​the subject. The first calculation module is used to transform the point cloud coordinates in the first image to the MRI coordinate system according to the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system. The second calculation module is used to calculate the spatial six degrees of freedom data of the imaging part of the subject in the MRI coordinate system based on the spatial transformation matrix between two adjacent frames of the first image, so as to obtain the motion information of the imaging part of the subject in the MRI coordinate system. The fourth acquisition module is used to acquire the first coordinates of multiple second reference points in the camera coordinate system from at least one target image frame before obtaining the coordinate transformation matrix between the camera coordinate system and the MRI coordinate system. The fifth acquisition module is used to acquire the second coordinates of multiple second reference points in the MRI coordinate system; The sixth acquisition module is used to substitute the first coordinates of the plurality of second reference points into a preset target matrix function to obtain a plurality of estimated function values, each estimated function value corresponding to a second reference point; The seventh acquisition module is used to obtain, for each estimated function value, the absolute value of the difference between the estimated function value and the second coordinate of the corresponding second reference point as the error value corresponding to the estimated function value; The error value determination module is used to determine whether the maximum value among the error values ​​corresponding to multiple estimated function values ​​is less than or equal to a preset error threshold.

8. An apparatus comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6.

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