Robot registration method and device, control equipment and storage medium

Abstract

The invention is suitable for the technical field of magnetic resonance, and provides a robot registration method and device, control equipment and a storage medium, and the method comprises the steps: obtaining a target magnetic resonance image of a development marker installed on a to-be-registered robot; performing image segmentation processing based on an adaptive threshold algorithm on the target magnetic resonance image to obtain target point cloud data of the development marker; according to the target point cloud data, determining position information of the developing marker in a magnetic resonance coordinate system corresponding to the magnetic resonance equipment; according to the position information, determining a target homogeneous transformation matrix of an end tool coordinate system of the robot under a magnetic resonance coordinate system; and the registration operation of the robot is completed by using the target homogeneous transformation matrix. According to the method, robot registration in a magnetic resonance environment is realized, noise reduction processing of the magnetic resonance image is realized in combination with an adaptive threshold algorithm, the determination accuracy of the point cloud data of the developing marker is improved, and the registration accuracy of the robot is further improved.

Description

Technical Field

[0001] The present application belongs to the field of magnetic resonance technology, and in particular, relates to a robot registration method, device, control equipment and storage medium. Background Art

[0002] With the continuous development of medical technology, it is becoming more and more common to use surgical robots for assisted surgery. For example, surgical robots are used to assist puncture surgery. In order to improve the accuracy of the above-mentioned surgeries, it is usually necessary to align the coordinates of the surgical robot and the operating table.

[0003] However, due to the particularity of the magnetic resonance environment, traditional robot alignment methods, such as optical alignment, magnetic navigation alignment, etc., which align the coordinates of the robot and the operating table, cannot be used in the magnetic resonance environment. Summary of the invention

[0004] The embodiments of the present application provide a robot registration method, apparatus, control device and storage medium, which realize robot registration in a magnetic resonance environment and improve the registration accuracy of the robot.

[0005] In a first aspect, an embodiment of the present application provides a robot registration method, comprising:

[0006] acquiring a target magnetic resonance image of a developed marker mounted on a robot to be registered, the robot being placed on a designated component of a magnetic resonance device for generating magnetic resonance images;

[0007] Performing image segmentation processing based on an adaptive threshold algorithm on the target magnetic resonance image to obtain target point cloud data of the development marker;

[0008] Determine the position information of the imaging marker in the magnetic resonance coordinate system corresponding to the magnetic resonance device according to the target point cloud data;

[0009] According to the position information, a target homogeneous transformation matrix of the robot's end tool coordinate system in the magnetic resonance coordinate system is determined;

[0010] The target homogeneous transformation matrix is ​​used to complete the robot registration operation.

[0011] The embodiment of the present application provides a robot registration method, which obtains a target magnetic resonance image of a development marker installed on a robot to be registered; performs image segmentation processing based on an adaptive threshold algorithm on the target magnetic resonance image to obtain target point cloud data of the development marker; determines the position information of the development marker in the magnetic resonance coordinate system corresponding to the magnetic resonance device according to the target point cloud data; determines the target homogeneous transformation matrix of the robot's end tool coordinate system in the magnetic resonance coordinate system according to the position information; and uses the target homogeneous transformation matrix to complete the robot registration operation. The method provided by the present application realizes robot registration in a magnetic resonance environment, and at the same time, realizes noise reduction processing of magnetic resonance images in combination with an adaptive threshold algorithm, improves the accuracy of determining the point cloud data of the development marker, and thus improves the accuracy of robot registration.

[0012] In a possible implementation of the first aspect, acquiring a target magnetic resonance image of a development marker mounted on a robot to be registered includes:

[0013] Controlling the robot to move the imaging marker into the magnetic resonance coil of the magnetic resonance device;

[0014] Acquiring a plurality of initial magnetic resonance images generated by performing magnetic resonance scanning on the developing marker through a magnetic resonance device;

[0015] From the multiple initial magnetic resonance images, an image in which the development marker is located in the central area is selected as a target magnetic resonance image.

[0016] In the above implementation, since the display marker is located in the central area of ​​the target magnetic resonance image, the subsequent control device only needs to use an adaptive threshold algorithm to perform image segmentation processing on the central area of ​​the target magnetic resonance image, thereby improving processing efficiency.

[0017] In an implementation of the first aspect, determining position information of the imaging marker in a magnetic resonance coordinate system corresponding to the magnetic resonance device according to the target point cloud data includes:

[0018] Determine the first centroid point of the target point cloud data;

[0019] Subtract the coordinates of the first centroid point from the coordinates of each point included in the target point cloud data to obtain first point cloud data;

[0020] The position information is calculated based on the first point cloud data and the second point cloud data; the second point cloud data is the point cloud data obtained by subtracting the coordinates of the second center of mass point from the coordinates of each point contained in the benchmark point cloud data, the benchmark point cloud data is the point cloud data of the development marker obtained in advance in the magnetic resonance coordinate system, and the second center of mass point is the center of mass point of the benchmark point cloud data in the magnetic resonance coordinate system.

[0021] In the above embodiment, the final position information of the development marker is determined by combining the first point cloud data obtained from the target point cloud data and the second point cloud data obtained from the reference point cloud data, thereby improving the accuracy of determining the position information of the development marker.

[0022] In one implementation of the first aspect, determining a target homogeneous transformation matrix of an end tool coordinate system of the robot in a magnetic resonance coordinate system according to the position information includes:

[0023] Get the scene information of the robot;

[0024] Determine the calculation method of the target homogeneous transformation matrix according to the scene information;

[0025] According to the position information, the target homogeneous transformation matrix is ​​calculated by a calculation method.

[0026] In the above implementation, the calculation method of the target homogeneous transformation matrix is ​​flexibly determined in combination with the scene information of the robot, thereby improving the accuracy of determining the target homogeneous transformation matrix, so as to subsequently achieve robot registration that matches the scene information.

[0027] In an implementation of the first aspect, determining a calculation method of a target homogeneous transformation matrix according to scene information includes:

[0028] Based on the scene information, determine whether the robot is placed on the specified component for a long time;

[0029] If the robot is placed on the designated component for a long time, the calculation method is determined to be the first method of performing multiple magnetic resonance scans on the development marker;

[0030] If the robot is not placed on the designated component for a long time, the calculation method is determined as the second method of performing a single magnetic resonance scan on the development marker.

[0031] In the above implementation, the calculation method of the target homogeneous transformation matrix is ​​flexibly determined according to whether the robot is placed on a designated component of the magnetic resonance device for a long time, thereby further improving the accuracy of determining the target homogeneous transformation matrix.

[0032] In an implementation of the first aspect, a target homogeneous transformation matrix is ​​calculated according to the position information by using a calculation method, including:

[0033] If the calculation method is the first method, the number of magnetic resonance scans of the imaging marker is counted;

[0034] If the number of magnetic resonance scans is greater than the set number, the first homogeneous transformation matrix of the robot's base coordinate system in the magnetic resonance coordinate system is calculated based on the position information obtained by the last magnetic resonance scan of the development marker;

[0035] Based on the robot's forward kinematics, the first homogeneous transformation matrix is ​​subjected to coordinate transformation to obtain the target homogeneous transformation matrix.

[0036] In the above embodiment, when the robot needs to be placed on a designated component for a long time, the control device can control the magnetic resonance device to scan the development marker multiple times to improve the registration accuracy of the robot.

[0037] In an implementation of the first aspect, a target homogeneous transformation matrix is ​​calculated according to the position information by using a calculation method, including:

[0038] If the calculation method is the second method, obtaining the posture information of the development marker;

[0039] Determine the second homogeneous transformation matrix of the imaging marker in the magnetic resonance coordinate system according to the position information and the posture information;

[0040] Based on the robot's forward kinematics, the second homogeneous transformation matrix is ​​subjected to coordinate transformation to obtain the target homogeneous transformation matrix.

[0041] In the above embodiment, when the robot does not need to be placed on the designated component for a long time, the control device can control the magnetic resonance device to perform a single scan on the imaging marker to increase the registration rate of the robot.

[0042] In a second aspect, an embodiment of the present application provides a robot registration device, comprising:

[0043] a first acquisition unit for acquiring a target magnetic resonance image of a development marker mounted on a robot to be registered, the robot being placed on a designated component of a magnetic resonance device for generating magnetic resonance images;

[0044] A processing unit, used for performing image segmentation processing on the target magnetic resonance image based on an adaptive threshold algorithm to obtain target point cloud data of the development marker;

[0045] A first position determination unit, configured to determine position information of the imaging marker in a magnetic resonance coordinate system corresponding to the magnetic resonance device according to the target point cloud data;

[0046] A first matrix determination unit is used to determine a target homogeneous transformation matrix of the robot's end tool coordinate system in the magnetic resonance coordinate system according to the position information;

[0047] The registration unit is used to complete the registration operation of the robot using the target homogeneous transformation matrix.

[0048] In an implementation of the second aspect, the first acquisition unit specifically includes:

[0049] A control unit, used for controlling the robot to move the imaging marker into the magnetic resonance coil of the magnetic resonance device;

[0050] A second acquisition unit is used to acquire a plurality of initial magnetic resonance images generated by performing magnetic resonance scanning on the development marker by a magnetic resonance device;

[0051] The selection unit is used to select an image in which the development marker is located in the central area from the multiple initial magnetic resonance images as a target magnetic resonance image.

[0052] In an implementation of the second aspect, the first position determination unit specifically includes:

[0053] A centroid determination unit, used to determine a first centroid of the target point cloud data;

[0054] a subtraction unit, used for subtracting the coordinates of the first centroid point from the coordinates of each point included in the target point cloud data to obtain the first point cloud data;

[0055] The second position determination unit is used to calculate the position information based on the first point cloud data and the second point cloud data; the second point cloud data is the point cloud data obtained by subtracting the coordinates of the second centroid point from the coordinates of each point contained in the reference point cloud data, the reference point cloud data is the point cloud data of the development marker obtained by pre-calibration in the magnetic resonance coordinate system, and the second centroid point is the centroid point of the reference point cloud data in the magnetic resonance coordinate system.

[0056] In an implementation of the second aspect, the first matrix determination unit specifically includes:

[0057] A third acquisition unit is used to acquire scene information where the robot is located;

[0058] A first mode determination unit, used to determine a calculation mode of a target homogeneous transformation matrix according to scene information;

[0059] The second matrix determination unit is used to calculate the target homogeneous transformation matrix according to the position information.

[0060] In an implementation of the second aspect, the first mode determination unit specifically includes:

[0061] A robot determination unit, used to determine whether the robot is placed on a designated component for a long time according to scene information;

[0062] A second mode determination unit is used to determine the calculation mode as the first mode of performing multiple magnetic resonance scans on the development marker if the robot is placed on the designated component for a long time;

[0063] The third mode determination unit is used to determine the calculation mode as the second mode of performing a single magnetic resonance scan on the development marker if the robot is not placed on the designated component for a long time.

[0064] In an implementation manner of the second aspect, the second matrix determination unit specifically includes:

[0065] A statistical unit, for counting the number of magnetic resonance scans of the imaging marker if the calculation method is the first method;

[0066] A calculation unit, for calculating the first homogeneous transformation matrix of the robot's base coordinate system in the magnetic resonance coordinate system according to the position information obtained by the last magnetic resonance scan of the development marker if the number of magnetic resonance scans is greater than the set number;

[0067] The first conversion unit is used to perform coordinate conversion processing on the first homogeneous transformation matrix based on the forward kinematics of the robot to obtain a target homogeneous transformation matrix.

[0068] In an implementation manner of the second aspect, the second matrix determination unit specifically includes:

[0069] a fourth acquiring unit, configured to acquire the posture information of the development marker if the calculation method is the second method;

[0070] A third matrix determination unit is used to determine a second homogeneous transformation matrix of the imaging marker in the magnetic resonance coordinate system according to the position information and the posture information;

[0071] The second conversion unit is used to perform coordinate conversion processing on the second homogeneous transformation matrix based on the forward kinematics of the robot to obtain a target homogeneous transformation matrix.

[0072] In a third aspect, an embodiment of the present application provides a control device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the robot alignment method as described in any one of the first aspects above is implemented.

[0073] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the robot registration method as described in any one of the first aspects above is implemented.

[0074] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed on a control device, enables the control device to execute the robot registration method described in any one of the first aspects above. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0076] Figure 1 is a schematic diagram of the structure of a robot registration system provided in one embodiment of the present application;

[0077] Figure 2 This is a schematic diagram of the installation of a development marker provided by an embodiment of the present application;

[0078] Figure 3 is a schematic diagram of the structure of a development marker provided by an embodiment of the present application;

[0079] Figure 4 is a flowchart of an implementation of a robot registration method provided in an embodiment of the present application;

[0080] Figure 5 is a flowchart of an implementation of a robot registration method provided by another embodiment of the present application;

[0081] Figure 6 is a flowchart of a robot registration method provided in yet another embodiment of the present application;

[0082] Figure 7 is a flowchart of a robot registration method provided in another embodiment of the present application;

[0083] Figure 8 is a flowchart of a robot registration method provided in another embodiment of the present application;

[0084] Fig. 9 It is an overall implementation flow chart of the robot registration method provided by an embodiment of the present application;

[0085] Fig.10 is a schematic diagram of the structure of a robot registration device provided in one embodiment of the present application;

[0086] Fig.11 It is a structural diagram of a control device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0087] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0088] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0089] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0090] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0091] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0092] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0093] In practical applications, with the continuous development of medical technology, the use of surgical robots for assisted surgery is becoming more and more common. For example, assisted puncture surgery is performed by surgical robots. In order to improve the accuracy of the above-mentioned operations, it is usually necessary to align the coordinates of the surgical robot and the operating table. However, due to the particularity of the magnetic resonance environment, traditional robot alignment methods, such as optical alignment, magnetic navigation alignment, etc., which align the coordinates of the robot and the operating table, cannot be used in a magnetic resonance environment. Therefore, in order to achieve robot alignment in a magnetic resonance environment, in all embodiments of the present application, the control device can obtain a target magnetic resonance image of a developing marker installed on the robot to be aligned, and achieve robot alignment based on the target magnetic resonance image of the display marker.

[0094] It should be noted that how the control device specifically realizes robot alignment through the target magnetic resonance image of the display marker can be found in the specific description of the robot alignment method shown in the figure below, which will not be elaborated here.

[0095] See also Figure 1 , Figure 1 1 is a schematic diagram of the structure of a robot registration system provided by an embodiment of the present application. For ease of explanation, only the parts related to the embodiment of the present application are shown. Figure 1 As shown, the robot registration system 1 includes a robot 10, a registration base 20, a plurality of display markers 30 (only four are shown in the figure), a magnetic resonance device 40, and a control device 50. The control device 50 is respectively connected to the robot 10 and the magnetic resonance device 40 for communication. The above communication connection mode can be a wired communication connection or a wireless communication connection. The control device 50 includes a central processing unit (CPU).

[0096] In the embodiment of the present application, the robot 10 is installed on a designated component in the magnetic resonance device 40. The designated component includes but is not limited to a magnetic resonance bed plate or a main magnet.

[0097] It should be noted that in order to avoid movement of the robot after registration, which would lead to deviation in the registration of the robot, the robot needs to be fixed on the above-mentioned designated components.

[0098] The registration base 20 is provided with a plurality of mounting holes and a plurality of mounting positions. Each mounting hole is used to connect with the mounting position of the set area of ​​the robot 10, that is, the registration base 20 is installed to the set area of ​​the robot through the plurality of mounting holes. The set area can be determined according to actual needs and is not limited here. For example, the set area can be the joint base of the robot 10.

[0099] Each mounting position is used to mount a development marker 30 .

[0100] In the embodiment of the present application, the control device 50 is used to control the robot 10 to extend a set number of development markers 30 installed on the registration base 20 into the magnetic resonance coil of the magnetic resonance device 40, so as to realize the magnetic resonance scanning of the set number of development markers 30 by the magnetic resonance device 40, and obtain a target magnetic resonance image containing the development markers 30. The set number can be determined according to actual needs and is not limited here.

[0101] In some possible embodiments, in order to improve the registration accuracy of the robot, the set number may be four.

[0102] Afterwards, the control device 50 may implement registration of the robot in the magnetic resonance environment according to the target magnetic resonance image acquired as described above.

[0103] See also Figure 2 , Figure 2 FIG. 1 is a schematic diagram of the installation of a development marker provided in one embodiment of the present application. Figure 2 As shown, the registration base 20 includes a plurality of mounting holes 21 (only six are shown in the figure) and a plurality of mounting positions 22 (only eight are shown in the figure). Figure 2 There are four mounting positions 22 on the back of the registration base 20. The back of the registration base 20 refers to the side opposite to the front of the registration base 20, and the front of the registration base 20 refers to the side opposite to the front of the registration base 20. Figure 2 The middle registration base 20 has a surface with a plurality of mounting holes 21 .

[0104] In one embodiment of the present application, in order to further improve the registration accuracy of the robot, the multiple development markers 30 installed on the registration base 20 need to form a cubic structure (such as Figure 2 As shown), the plurality of development markers 30 need to be on at least two planes.

[0105] See also Figure 3 , Figure 3 Schematic diagram of the structure of the imaging marker provided by one embodiment of the present application. Figure 3 As shown, the development marker 30 includes: a bottle cap 31 , a sealing ring 32 and a ball bottle 33 .

[0106] In the embodiment of the present application, the bottle cap 31 includes a first structure 311 and a second structure 312 , wherein the diameter of the first structure 311 is greater than the diameter of the second structure 312 .

[0107] The first structure 311 is provided with a first external thread 3111 for screwing into a mounting hole on the registration base 20 .

[0108] The second structure 312 is provided with a second external thread 312 for being screwed into the opening of the ball pin 33 .

[0109] In practical applications, the bottle cap 31 may be a bottle cap made of plastic.

[0110] The sealing ring 32 is located between the bottle cap 31 and the ball pin 33, and is used to seal the bottle cap 31 and the ball pin 33 to prevent the fluid or solidified fluid in the ball pin 33 from leaking out.

[0111] In practical applications, the sealing ring 32 may be a sealing ring made of rubber.

[0112] The ball bottle 33 is used to contain a fluid or solidified fluid that can be clearly seen under magnetic resonance imaging, so that the imaging marker 30 can form a spherical bright area in the magnetic resonance imaging for robot registration. The fluid or solidified fluid includes but is not limited to water, hydrolyzed salt solution such as copper sulfate, silicone oil or gel, etc.

[0113] In practical applications, the ball bottle 33 can be a hollow spherical container made of plastic material.

[0114] In one embodiment of the present application, the outer surface of the pin 33 is provided with a reflective coating, so that the control device 50 can obtain an image containing the developing marker 30 through a photographic device wirelessly connected thereto, and assist in locating the developing marker 30 according to the image. The photographic device includes but is not limited to a camera, etc.

[0115] See also Figure 4 , Figure 4 1 is a flowchart of the implementation of the robot registration method provided in one embodiment of the present application. In the embodiment of the present application, the execution subject of the robot registration method is a control device 50. The control device can be a device with a central processing unit such as a desktop computer or a computer.

[0116] like Figure 4 As shown, the robot registration method provided in one embodiment of the present application may include S101 to S105, which are described in detail as follows:

[0117] In S101 , a target magnetic resonance image of a visualization marker mounted on a robot to be registered is acquired, and the robot is placed on a designated component of a magnetic resonance apparatus for generating magnetic resonance images.

[0118] In practical applications, it is becoming more and more common to use surgical robots for assisted surgery. For example, assisted puncture surgery is performed by surgical robots. Therefore, in a magnetic resonance environment, before performing a surgical deployment, the user can trigger a robot registration instruction for the control device. The robot registration instruction is used to instruct the control device to register the robot installed on a specified component of the magnetic resonance device.

[0119] In an embodiment of the present application, the control device detecting the robot registration instruction may include: detecting that a preset operation is executed. The preset operation may be determined according to actual needs and is not limited here. Exemplarily, the preset operation may be: a preset control in the control device is clicked, that is, if the control device detects that the preset control on itself is clicked, it is considered that the preset operation is detected to be executed. Of course, the preset operation can also be a time-triggered operation. The control device can be registered with a corresponding workflow during operation. The workflow contains trigger nodes for multiple key events. The above-mentioned key events include events for registering the robot. In this case, if the control device detects that the trigger node associated with the event for registering the robot is reached, the operations of steps S101 to S105 are executed to perform the registration operation for the robot.

[0120] Based on this, after detecting the robot registration instruction, the control device can obtain a target magnetic resonance image of the development marker installed on the robot to be registered.

[0121] It should be noted that the target magnetic resonance image may be a magnetic resonance image including all the imaging markers installed on the registration base.

[0122] In one embodiment of the present application, the control device can acquire the target magnetic resonance image of the development marker in real time through the magnetic resonance device connected to the control device for communication.

[0123] In another embodiment of the present application, in order to improve the processing efficiency of the subsequent control device for image segmentation of the target magnetic resonance image, the control device may specifically obtain the target magnetic resonance image according to the following steps, which are described in detail as follows:

[0124] Controlling the robot to move the imaging marker into the magnetic resonance coil of the magnetic resonance device;

[0125] Acquiring a plurality of initial magnetic resonance images generated by performing magnetic resonance scanning on the developing marker through a magnetic resonance device;

[0126] From the multiple initial magnetic resonance images, an image in which the development marker is located in the central area is selected as a target magnetic resonance image.

[0127] In this embodiment, in order to ensure that the development marker is completely scanned and developed by the magnetic resonance imaging, the control device can control the robot to move the development marker into the magnetic resonance coil of the magnetic resonance device.

[0128] Afterwards, the control device may acquire a plurality of initial magnetic resonance images containing the development markers.

[0129] In practical applications, when the high signal image of the development marker is concentrated in the central area of ​​the magnetic resonance image, the control device can directly discard the pixels in the magnetic resonance image except the central area, and directly use the adaptive threshold algorithm to segment the image of the central area to improve processing efficiency. Therefore, in this embodiment, the control device can select the image in which the development marker is in the central area from multiple initial magnetic resonance images as the target magnetic resonance image.

[0130] It should be noted that the target magnetic resonance image may be one image or multiple images.

[0131] In S102, the target magnetic resonance image is subjected to image segmentation processing based on an adaptive threshold algorithm to obtain target point cloud data of the development marker.

[0132] In the embodiment of the present application, after obtaining the target magnetic resonance image, the control device can perform image segmentation processing on the target magnetic resonance image based on an adaptive threshold algorithm to obtain target point cloud data of the development marker.

[0133] In practical applications, the adaptive threshold algorithm can automatically adjust the threshold according to the characteristics of the image, thereby realizing the binarization of the image.

[0134] Specifically, after obtaining the target magnetic resonance image, the control device may perform linear conversion on all pixel values ​​in the target magnetic resonance image, that is, convert all pixel values ​​in the target magnetic resonance image into a pixel value array of 0-255, so as to subsequently determine the threshold of each pixel value.

[0135] After the control device normalizes the pixel value array, the development marker in the target magnetic resonance image is located in the central area of ​​the image. Therefore, the control device can discard the outermost pixels in the target magnetic resonance image and directly determine the threshold value of each pixel value in the central area through multiple pixel values ​​around each pixel value in the central area.

[0136] Exemplarily, assuming that the pixel matrix has m rows and n columns, the pixel array is P(i,j), i∈(0,m), j∈(0,n), and the threshold array is T(i,j), i∈(0,m), j∈(0,n). Since all areas except the central area in the target magnetic resonance image are low signal areas, the control device can determine that the thresholds of the above low signal areas are all 0, as shown below:

[0137]

[0138] In one embodiment of the present application, the control device may specifically determine the thresholds of the pixel values ​​of the central area of ​​the target magnetic resonance image according to the following formula:

[0139]

[0140] Wherein, P(i,j) represents the pixel value of the i-th row and j-th column in the target magnetic resonance image, T(i+1,j+1) represents the threshold value of the pixel value of the i+1-th row and j+1-th column in the target magnetic resonance image, and a represents a constant. The constant a can be determined according to actual needs and is not limited here.

[0141] In this embodiment, after obtaining the thresholds of each pixel value in the central area of ​​the target magnetic resonance image, the control device can segment the pixel values ​​in the central area according to the thresholds of each pixel value in the central area, and form a target pixel matrix with target pixel values ​​greater than the set threshold, and perform conversion processing on the target pixel matrix to obtain target point cloud data of the development marker. The set threshold can be determined according to actual needs and is not limited here.

[0142] In one embodiment of the present application, the control device may specifically segment the pixel values ​​of the central area according to the following formula:

[0143] P(i,j)=255,P(i,j)≥T(i,j)

[0144] P(i,j)=0,P(i,j) <T(i,j);

[0145] Wherein, P(i,j) represents the pixel value of the i-th row and j-th column in the target magnetic resonance image, and T(i,j) represents the threshold value of the pixel value of the i-th row and j-th column in the target magnetic resonance image.

[0146] Based on this, the control device can perform point cloud conversion on a target pixel matrix composed of multiple pixel values ​​equal to 255 to obtain target point cloud data of the development marker.

[0147] In S103, the position information of the development marker in the magnetic resonance coordinate system corresponding to the magnetic resonance device is determined according to the target point cloud data.

[0148] In an embodiment of the present application, after obtaining the target point cloud data, the control device can obtain the reference point cloud data, and use a point cloud registration algorithm to process the target point cloud data and the reference point cloud data to obtain the position information of the development marker in the magnetic resonance coordinate system corresponding to the magnetic resonance device.

[0149] It should be noted that the reference point cloud data is the point cloud data of the development marker obtained by pre-calibration.

[0150] In practical applications, the Point Cloud Registration (PCR) algorithm refers to inputting two sets of point cloud data Ps (source) and Pt (target), and outputting a transformation T (i.e., rotation R and translation t) so that the degree of overlap between T (Ps) and Pt is as high as possible. Among them, Ps is the target point cloud data in this embodiment, and Pt is the reference point cloud data in this embodiment. Among them, the point cloud registration algorithm includes but is not limited to the Iterative Closest Point (ICP) algorithm. The Iterative Closest Point algorithm can be solved based on the Singular Value Decomposition (SVD).

[0151] Based on this, in one embodiment of the present application, in order to improve the accuracy of determining the position information of the development marker, the control device can specifically Figure 5 Steps S201 to S203 shown determine the position information of the development marker, as described in detail as follows:

[0152] In S201 , a first centroid point of the target point cloud data is determined.

[0153] In S202, the coordinates of each point included in the target point cloud data are respectively subtracted from the coordinates of the first centroid point to obtain first point cloud data.

[0154] In S203, the position information is calculated based on the first point cloud data and the second point cloud data; the second point cloud data is the point cloud data obtained by subtracting the coordinates of the second centroid point from the coordinates of each point contained in the benchmark point cloud data, the benchmark point cloud data is the point cloud data of the development marker obtained by pre-calibration, and the second centroid point is the centroid point of the benchmark point cloud data.

[0155] In this embodiment, since each point in the target point cloud data has coordinates and a weight (usually 1), the control device can obtain the first centroid point of the target point cloud data by calculating the weighted average of all points in the target point cloud data.

[0156] In practical applications, by removing the centroid point of the point cloud data, multiple sets of point cloud data can be converted to the same coordinate system to achieve data alignment. Therefore, in this embodiment, the control device can subtract the coordinates of the first centroid point from the coordinates of each point contained in the target point cloud data to obtain the first point cloud data.

[0157] In this embodiment, the control device may further perform centroid removal processing on the reference point cloud data according to the above-mentioned method of obtaining the first point cloud data, so as to obtain second point cloud data corresponding to the reference point cloud data.

[0158] Based on this, the control device can process the first point cloud data and the second point cloud data based on an iterative closest point algorithm to obtain the position information of the development marker.

[0159] Specifically, the control device may calculate a first rotation matrix according to the first point cloud data and the second point cloud data, as shown below:

[0160]

[0161] You can get:

[0162]

[0163] Since the first term in the above formula is independent of the first rotation matrix, the second term is due to R T R=I, which is also independent of the first rotation matrix. Therefore, the control device can simplify the above formula to:

[0164]

[0165] Then define the matrix W as:

[0166]

[0167] Afterwards, the control device performs singular value decomposition on W and obtains:

[0168] [U, S, V] = SVD(W);

[0169] Finally, the control device calculates the first rotation matrix through the left singular matrix U and the right singular matrix V:

[0170] R1=UV T ;

[0171] Among them, R1 represents the first rotation matrix, q i represents the coordinates of the i-th point in the first point cloud data, q i ′ represents the coordinates of the i-th point of the second point cloud data.

[0172] In this embodiment, the first rotation matrix is ​​used to represent the posture information of the development marker.

[0173] Based on this, the control device can calculate the first position matrix of the development marker according to the first rotation matrix, the first center of mass point and the second center of mass point, that is, obtain the position information of the development marker.

[0174] In this embodiment, the first position matrix is ​​used to represent the position information of the development marker.

[0175] In one embodiment of the present application, the control device can specifically calculate the first position matrix of the development marker according to the following formula:

[0176] t=p-R1p ′ ;

[0177] Among them, t1 represents the first position matrix, R1 represents the first rotation matrix, p represents the first centroid point, and p ′ Represents the second centroid point.

[0178] In S104, a target homogeneous transformation matrix of the robot's end tool coordinate system in the magnetic resonance coordinate system is determined according to the position information.

[0179] In an embodiment of the present application, after obtaining the position information of the development marker, the control device can determine the homogeneous transformation matrix of the robot's base coordinate system in the magnetic resonance coordinate system based on the position information, and then the homogeneous transformation matrix determines the target homogeneous transformation matrix of the robot's end tool coordinate system in the magnetic resonance coordinate system.

[0180] In one embodiment of the present application, in order to meet the registration requirements of the robot in different scenes, to obtain target homogeneous transformation matrices that match different scenes respectively, and to improve the accuracy of determining the target homogeneous transformation matrix, the control device can specifically perform the following steps: Figure 6 Steps S301 to S303 shown determine the target homogeneous transformation matrix, which is described in detail as follows:

[0181] In S301, the scene information of the robot is obtained.

[0182] In this embodiment, the scene information is used to characterize the specific usage scene that the robot is in. The specific usage scene includes, but is not limited to: a surgery scene that requires normal arrangement and a scene that requires abnormal arrangement and emergency surgery.

[0183] In one implementation of this embodiment, the control device can obtain the scene information of the robot in real time through a shooting device connected to the control device by wireless communication. The shooting device includes but is not limited to a camera and a video camera.

[0184] In S302, a calculation method of a target homogeneous transformation matrix is ​​determined according to the scene information.

[0185] In this embodiment, after obtaining the scene information of the robot, the control device can determine whether the robot needs to be placed in a designated position for a long time based on the scene information, and then determine the calculation method of the target homogeneous transformation matrix based on whether the robot needs to be placed in the designated position for a long time.

[0186] It should be noted that the calculation method includes but is not limited to a first method of performing multiple magnetic resonance scans on the imaging marker and a second method of performing a single magnetic resonance scan on the imaging marker.

[0187] Based on this, in one embodiment of the present application, in order to further improve the accuracy of determining the target homogeneous transformation matrix, the control device can specifically determine the calculation method of the target homogeneous transformation matrix according to the following steps, which are detailed as follows:

[0188] Determining, based on the scene information, whether the robot is placed on the designated component for a long period of time;

[0189] If the robot is placed on the designated component for a long time, determining the calculation method to be a first method of performing multiple magnetic resonance scans on the imaging marker;

[0190] If the robot is not placed on the designated component for a long time, the calculation method is determined to be a second method of performing a single magnetic resonance scan on the development marker.

[0191] In this embodiment, when the control device detects that the robot needs to be placed on the designated component for a long time, it indicates that the robot is in a normalized surgical scenario. That is to say, the registration requirement for the robot at this time is registration accuracy. Therefore, at this time, the control device can determine that the calculation method for the target homogeneous transformation matrix is ​​the first method.

[0192] When the control device detects that the robot does not need to be placed on the designated component for a long time, it means that the robot is in an abnormal arrangement and needs to perform emergency surgery. In other words, the registration requirement for the robot at this time is the registration rate. Therefore, at this time, the control device can determine that the calculation method for the target homogeneous transformation matrix is ​​the second method.

[0193] In S303, a target homogeneous transformation matrix is ​​calculated based on the position information.

[0194] In this embodiment, in combination with S302, based on different registration requirements for the robot, the control device can process the position information of the development marker in combination with different calculation methods to obtain a target homogeneous transformation matrix that meets different registration requirements.

[0195] In one embodiment of the present application, when the calculation method is the first method, in order to improve the registration accuracy of the robot, the control device can specifically perform the following steps: Figure 7 The steps S401 to S403 shown in the figure obtain the target homogeneous transformation matrix, which is described in detail as follows:

[0196] In S401, if the calculation method is the first method, the number of magnetic resonance scans of the development marker is counted.

[0197] In S402, if the number of magnetic resonance scans is greater than the set number, the first homogeneous transformation matrix of the robot's base coordinate system in the magnetic resonance coordinate system is calculated based on the position information obtained by the last magnetic resonance scan of the development marker.

[0198] In S403, based on the forward kinematics of the robot, coordinate transformation processing is performed on the first homogeneous transformation matrix to obtain a target homogeneous transformation matrix.

[0199] In this embodiment, when the control device determines that the calculation method is the first method, it indicates that the registration requirement for the robot is the registration accuracy. Therefore, the control device needs to count the number of magnetic resonance scans of the development marker at this time.

[0200] It should be noted that after each MRI scan of the imaging marker, the control device needs to determine the position information of the imaging marker under the MRI scan according to steps S101 to S103. The position information can be represented by Cartesian coordinates.

[0201] Based on this, after obtaining the number of magnetic resonance scans, the control device can compare the number of magnetic resonance scans with the set number of scans, wherein the set number of scans can be determined according to actual needs and is not limited here.

[0202] In one embodiment of the present application, when the control device detects that the number of magnetic resonance scans is less than or equal to the set number, it indicates that the number of magnetic resonance scans of the development marker does not meet the scanning requirements. Therefore, the control device needs to continue to control the magnetic resonance device to perform magnetic resonance scanning on the development marker, and continue to execute steps S101 to S103 until the number of magnetic resonance scans is greater than the set number.

[0203] In another embodiment of the present application, when the control device detects that the number of magnetic resonance scans is greater than the set number, it indicates that the number of magnetic resonance scans of the developing marker meets the scanning requirements. Therefore, the control device calculates the first homogeneous transformation matrix of the robot's base coordinate system in the magnetic resonance coordinate system based on the position information obtained from the last magnetic resonance scan of the developing marker.

[0204] Specifically, the control device can determine a first center of mass point of the target point cloud data and a third center of mass point of the third point cloud data of the development marker in the robot base coordinate system.

[0205] Afterwards, the control device may subtract the coordinates of the first centroid point from the coordinates of each point included in the target point cloud data to obtain the first point cloud data, and subtract the coordinates of the third centroid point from the coordinates of each point included in the third point cloud data to obtain the fourth point cloud data, and obtain the target matrix according to the first point cloud data and the fourth point cloud data:

[0206]

[0207] Where H represents the target matrix, represents the first point cloud data, Represents the third point cloud data, centroid Bed Indicates the first centroid, centroid Base Represents the third centroid point.

[0208] Afterwards, the control device can perform singular value decomposition on the target matrix H to obtain the left singular matrix U and the right singular matrix V:

[0209] [U, S, V] = SVD(H);

[0210] The control device can calculate the second rotation matrix through the matrix U and the matrix V:

[0211] R2=UV T ;

[0212] Subsequently, the control device may calculate a second position matrix according to the second rotation matrix, the first center of mass point, and the third center of mass point:

[0213] t2=-R2·centroid Base +centroid MRI ;

[0214] Subsequently, the control device may combine the second rotation matrix and the second position matrix to obtain a first homogeneous transformation matrix of the base coordinate system of the robot in the magnetic resonance coordinate system:

[0215]

[0216] Finally, the control device can perform coordinate transformation on the first homogeneous transformation matrix through the robot's forward kinematics to obtain the target homogeneous transformation matrix:

[0217]

[0218] Among them, R2 represents the second rotation matrix, t2 represents the second position matrix, represents the first homogeneous transformation matrix, Represents the third homogeneous transformation matrix of the robot's end tool coordinate system in the robot's base coordinate system, Represents the target homogeneous transformation matrix.

[0219] In another embodiment of the present application, when the calculation method is the second method, in order to improve the registration efficiency of the robot, the control device can specifically perform the following steps: Figure 8 The steps S501 to S503 shown in the figure obtain the target homogeneous transformation matrix, which is described in detail as follows:

[0220] In S501, if the calculation method is the second method, the posture information of the development marker is obtained.

[0221] In S502, a second homogeneous transformation matrix of the development marker in the magnetic resonance coordinate system is determined according to the position information and the posture information.

[0222] In S503, based on the forward kinematics of the robot, coordinate transformation processing is performed on the second homogeneous transformation matrix to obtain a target homogeneous transformation matrix.

[0223] In this embodiment, when the control device determines that the calculation method is the first method, it indicates that the registration requirement for the robot is the registration rate. Therefore, the control device can determine the second homogeneous transformation matrix of the development marker in the magnetic resonance coordinate system based on the position information of the development marker obtained after this magnetic resonance scan and the posture information of the development marker obtained.

[0224] In an implementation of this embodiment, in combination with S201 to S203, the control device can calculate the first rotation matrix of the development marker according to the first point cloud data and the second point cloud data, so as to obtain the posture information of the development marker.

[0225] In this embodiment, the first rotation matrix is ​​used to represent the posture information of the development marker.

[0226] Afterwards, the control device can calculate the second homogeneous transformation matrix of the imaging marker in the magnetic resonance coordinate system according to the following formula:

[0227]

[0228] in, represents the second homogeneous transformation matrix, R1 represents the first rotation matrix, and t1 represents the first position matrix.

[0229] Based on this, the control device can perform coordinate transformation on the second homogeneous transformation matrix through the robot's forward kinematics to obtain the target homogeneous transformation matrix:

[0230]

[0231] in, represents the target homogeneous transformation matrix, represents the first transformation matrix of the robot's base coordinate system in the magnetic resonance coordinate system, Represents the third homogeneous transformation matrix of the robot's end tool coordinate system in the robot's base coordinate system, represents the second homogeneous transformation matrix of the imaging marker in the magnetic resonance coordinate system, The fourth homogeneous transformation matrix of the robot's base coordinate system is obtained under the development marker.

[0232] In S105, the robot registration operation is completed using the target homogeneous transformation matrix.

[0233] In an embodiment of the present application, after obtaining the target homogeneous transformation matrix of the robot's end tool coordinate system in the magnetic resonance coordinate system, the control device can determine the position of the robot's end tool according to the target homogeneous transformation matrix to complete the robot's alignment operation.

[0234] From the above, it can be seen that a robot registration method provided by an embodiment of the present application obtains a target magnetic resonance image of a developing marker installed on the robot to be registered; performs image segmentation processing based on an adaptive threshold algorithm on the target magnetic resonance image to obtain target point cloud data of the developing marker; determines the position information of the developing marker in the magnetic resonance coordinate system corresponding to the magnetic resonance device according to the target point cloud data; determines the target homogeneous transformation matrix of the robot's end tool coordinate system in the magnetic resonance coordinate system according to the position information; and uses the target homogeneous transformation matrix to complete the robot registration operation. The method provided by the present application realizes robot registration in a magnetic resonance environment. At the same time, it realizes noise reduction processing of magnetic resonance images in combination with an adaptive threshold algorithm, improves the accuracy of determining the point cloud data of the developing marker, and thus improves the accuracy of robot registration.

[0235] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0236] See also Fig. 9 , Fig. 9 FIG. 1 is an overall flow chart of a robot registration method provided by an embodiment of the present application. Fig. 9 As shown, after the magnetic resonance device detects the robot registration instruction and detects that the robot has been placed on the magnetic resonance bed, that is, after executing step S601, the control device can continue to execute step S602, that is, control the robot to extend the imaging marker into the magnetic resonance coil of the magnetic resonance device, and then the control device can execute step S603, that is, control the magnetic resonance device to perform magnetic resonance scanning on the imaging marker to obtain a target magnetic resonance image. Next, the control device can execute step S603, that is, perform image segmentation processing based on an adaptive threshold algorithm on the target magnetic resonance image to obtain target point cloud data of the imaging marker. After that, the control device can continue to execute step S605, that is, use a point cloud registration algorithm (such as an ICP algorithm) to process the target point cloud data and the reference point cloud data to obtain the position information of the imaging marker.

[0237] After obtaining the position information of the development marker, the control device may execute step S606, ie, detecting whether the robot needs to be placed on the designated component for a long time.

[0238] In one embodiment of the present application, when the control device detects that the robot needs to be placed on the specified component for a long time, the control device can be based on a multiple registration method, that is, Figure 7 The illustrated embodiment corresponds to a first method for registering the robot.

[0239] Specifically, the control device may execute step S607, ie, count the number of magnetic resonance scans of the development marker; thereafter, the control device may execute step S608, ie, detect whether the number of magnetic resonance scans is greater than a set number.

[0240] On the one hand, when the control device detects that the number of magnetic resonance scans is less than or equal to the set number, the control device may return to execute steps S603 to S608 until the number of magnetic resonance scans is greater than the set number.

[0241] On the other hand, when the control device detects that the number of magnetic resonance scans is greater than the setting, the control device can execute step S609, that is, according to the position information obtained by the last magnetic resonance scan of the imaging marker, calculate the first homogeneous transformation matrix of the robot's base coordinate system in the magnetic resonance coordinate system. After that, the control device can execute step S6010, that is, based on the robot's forward kinematics, perform coordinate transformation processing on the first homogeneous transformation matrix to obtain the target homogeneous transformation matrix. Finally, the control device can execute step S6014, that is, use the target homogeneous transformation matrix to complete the robot's registration operation.

[0242] In another embodiment of the present application, when the control device detects that the robot does not need to be placed on the designated component for a long time, the control device can be based on a single registration method, that is, Figure 8 The illustrated embodiment corresponds to a second method for aligning the robot.

[0243] Specifically, the control device can execute step S6011, i.e., obtain the posture information of the development marker; then, the control device can execute step S6012, i.e., determine the second homogeneous transformation matrix of the development marker in the magnetic resonance coordinate system according to the position information and posture information of the development marker; thereafter, the control device can execute step S6013, i.e., based on the forward kinematics of the robot, perform coordinate transformation processing on the second homogeneous transformation matrix to obtain the target homogeneous transformation matrix; finally, the control device can execute step S6014, i.e., use the target homogeneous transformation matrix to complete the robot's alignment operation.

[0244] Corresponding to a robot registration method described in the above embodiment, Fig.10The schematic diagram of the structure of a robot registration device provided by an embodiment of the present application is shown. For the convenience of explanation, only the part related to the embodiment of the present application is shown. Fig.10 The robot registration device 700 includes: a first acquisition unit 71, a processing unit 72, a first position determination unit 73, a first matrix determination unit 74 and a registration unit 75. Wherein:

[0245] The first acquisition unit 71 is used to acquire a target magnetic resonance image of a development marker mounted on a robot to be registered, the robot being placed on a designated component of a magnetic resonance device for generating magnetic resonance images.

[0246] The processing unit 72 is used to perform image segmentation processing on the target magnetic resonance image based on an adaptive threshold algorithm to obtain target point cloud data of the development marker.

[0247] The first position determination unit 73 is used to determine the position information of the development marker in the magnetic resonance coordinate system corresponding to the magnetic resonance device according to the target point cloud data.

[0248] The first matrix determination unit 74 is used to determine the target homogeneous transformation matrix of the robot's end tool coordinate system in the magnetic resonance coordinate system according to the position information.

[0249] The registration unit 75 is used to complete the registration operation of the robot using the target homogeneous transformation matrix.

[0250] In one embodiment of the present application, the first acquisition unit 71 specifically includes: a control unit, a second acquisition unit and a selection unit. Among them:

[0251] The control unit is used to control the robot to move the development marker into the magnetic resonance coil of the magnetic resonance device.

[0252] The second acquisition unit is used to acquire a plurality of initial magnetic resonance images generated by performing magnetic resonance scanning on the development marker by a magnetic resonance device.

[0253] The selection unit is used to select an image in which the development marker is located in the central area from the multiple initial magnetic resonance images as a target magnetic resonance image.

[0254] In one embodiment of the present application, the first position determination unit 73 specifically includes: a centroid determination unit, a subtraction unit and a second position determination unit.

[0255] The centroid point determination unit is used to determine the first centroid point of the target point cloud data.

[0256] The subtraction unit is used to subtract the coordinates of the first centroid point from the coordinates of each point included in the target point cloud data to obtain the first point cloud data.

[0257] The second position determination unit is used to calculate the position information based on the first point cloud data and the second point cloud data; the second point cloud data is the point cloud data obtained by subtracting the coordinates of the second center of mass point from the coordinates of each point contained in the reference point cloud data, the reference point cloud data is the point cloud data of the development marker obtained in advance in the magnetic resonance coordinate system, and the second center of mass point is the center of mass point of the reference point cloud data in the magnetic resonance coordinate system.

[0258] In one embodiment of the present application, the first matrix determination unit specifically includes: a third acquisition unit, a first mode determination unit and a second matrix determination unit.

[0259] The third acquisition unit is used to acquire scene information where the robot is located.

[0260] The first method determination unit is used to determine a calculation method of the target homogeneous transformation matrix according to scene information.

[0261] The second matrix determination unit is used to obtain the target homogeneous transformation matrix by calculation according to the position information.

[0262] In one embodiment of the present application, the first mode determination unit specifically includes: a robot determination unit, a second mode determination unit and a third mode determination unit.

[0263] The robot determination unit is used to determine whether the robot is placed on a designated component for a long time according to scene information.

[0264] The second mode determination unit is used to determine the calculation mode as the first mode of performing multiple magnetic resonance scans on the development marker if the robot is placed on the designated component for a long time.

[0265] The third mode determination unit is used to determine the calculation mode as the second mode of performing a single magnetic resonance scan on the development marker if the robot is not placed on the designated component for a long time.

[0266] In one embodiment of the present application, the second matrix determination unit specifically includes: a statistical unit, a calculation unit and a first conversion unit.

[0267] The statistical unit is used for counting the number of magnetic resonance scanning of the imaging marker if the calculation method is the first method.

[0268] The calculation unit is used to calculate the first homogeneous transformation matrix of the robot's base coordinate system in the magnetic resonance coordinate system according to the position information obtained by the last magnetic resonance scan of the development marker if the number of magnetic resonance scans is greater than the set number.

[0269] The first conversion unit is used to perform coordinate conversion processing on the first homogeneous transformation matrix based on the forward kinematics of the robot to obtain a target homogeneous transformation matrix.

[0270] In one embodiment of the present application, the second matrix determination unit specifically includes: a fourth acquisition unit, a third matrix determination unit and a second conversion unit.

[0271] The fourth acquisition unit is used for acquiring the posture information of the development marker if the calculation method is the second method.

[0272] The third matrix determination unit is used to determine the second homogeneous transformation matrix of the imaging marker in the magnetic resonance coordinate system according to the position information and the posture information.

[0273] The second conversion unit is used to perform coordinate conversion processing on the second homogeneous transformation matrix based on the forward kinematics of the robot to obtain a target homogeneous transformation matrix.

[0274] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0275] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by 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 embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0276] Fig.11 This is a schematic diagram of the structure of a control device provided in one embodiment of the present application. Fig.11 As shown, the control device 8 of this embodiment includes: at least one processor 80 ( Fig.11 Only one is shown in the figure) a processor, a memory 81, and a computer program 82 stored in the memory 81 and executable on the at least one processor 80, wherein the processor 80 implements the steps of any of the above-mentioned robot alignment method embodiments when executing the computer program 82.

[0277] The control device may include, but is not limited to, a processor 80 and a memory 81. Those skilled in the art will appreciate that Fig.11 It is only an example of the control device 8 and does not constitute a limitation on the control device 8. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0278] The processor 80 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) 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, etc.

[0279] In some embodiments, the memory 81 may be an internal storage unit of the control device 8, such as the memory of the control device 8. In other embodiments, the memory 81 may also be an external storage device of the control device 8, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the control device 8. Further, the memory 81 may also include both the internal storage unit of the control device 8 and an external storage device. The memory 81 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 81 may also be used to temporarily store data that has been output or is to be output.

[0280] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0281] An embodiment of the present application provides a computer program product. When the computer program product runs on a control device, the control device can implement the steps in the above-mentioned method embodiments when the computer program product is executed.

[0282] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to the control device, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electric carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0283] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0284] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A robot registration method, characterized in that: include: acquiring a target magnetic resonance image of a visualization marker mounted on a robot to be registered, the robot being placed on a designated component of a magnetic resonance apparatus for generating magnetic resonance images; Performing image segmentation processing based on an adaptive threshold algorithm on the target magnetic resonance image to obtain target point cloud data of the development marker; Determining, according to the target point cloud data, position information of the development marker in a magnetic resonance coordinate system corresponding to the magnetic resonance device; Determine, according to the position information, a target homogeneous transformation matrix of the end tool coordinate system of the robot in the magnetic resonance coordinate system; The target homogeneous transformation matrix is ​​used to complete the registration operation of the robot.

2. The robot registration method according to claim 1, characterized in that: The step of acquiring a target magnetic resonance image of a development marker mounted on a robot to be registered comprises: Controlling the robot to move the development marker into the magnetic resonance coil of the magnetic resonance device; Acquiring a plurality of initial magnetic resonance images generated by performing magnetic resonance scanning on the imaging marker by the magnetic resonance device; From the multiple initial magnetic resonance images, an image in which the development marker is located in the central area is selected as the target magnetic resonance image.

3. The robot registration method according to claim 1, characterized in that: Determining the position information of the imaging marker in the magnetic resonance coordinate system corresponding to the magnetic resonance device according to the target point cloud data includes: Determine a first centroid point of the target point cloud data; Subtract the coordinates of the first centroid point from the coordinates of each point included in the target point cloud data to obtain first point cloud data; The position information is calculated based on the first point cloud data and the second point cloud data; the second point cloud data is the point cloud data obtained by subtracting the coordinates of the second centroid point from the coordinates of each point contained in the benchmark point cloud data, the benchmark point cloud data is the point cloud data of the development marker obtained by pre-calibration, and the second centroid point is the centroid point of the benchmark point cloud data.

4. The robot registration method according to any one of claims 1 to 3, characterized in that: Determining a target homogeneous transformation matrix of the robot's end tool coordinate system in the magnetic resonance coordinate system according to the position information includes: Obtaining scene information of the robot; Determining a calculation method of the target homogeneous transformation matrix according to the scene information; The target homogeneous transformation matrix is ​​calculated and obtained by adopting the calculation method according to the position information.

5. The robot registration method according to claim 4, characterized in that: The step of determining a calculation method of the target homogeneous transformation matrix according to the scene information includes: Determining, based on the scene information, whether the robot is placed on the designated component for a long period of time; If the robot is placed on the designated component for a long time, determining the calculation method to be a first method of performing multiple magnetic resonance scans on the imaging marker; If the robot is not placed on the designated component for a long time, the calculation method is determined to be a second method of performing a single magnetic resonance scan on the development marker.

6. The robot registration method according to claim 5, characterized in that: The step of calculating the target homogeneous transformation matrix by using the calculation method according to the position information includes: If the calculation method is the first method, then counting the number of magnetic resonance scans of the imaging marker; If the number of magnetic resonance scans is greater than the set number, the first homogeneous transformation matrix of the base coordinate system of the robot in the magnetic resonance coordinate system is calculated according to the position information obtained by the last magnetic resonance scan of the development marker; Based on the forward kinematics of the robot, coordinate transformation processing is performed on the first homogeneous transformation matrix to obtain the target homogeneous transformation matrix.

7. The robot registration method according to claim 5, characterized in that: The step of calculating the target homogeneous transformation matrix by using the calculation method according to the position information includes: If the calculation method is the second method, acquiring the posture information of the development marker; Determining a second homogeneous transformation matrix of the development marker in the magnetic resonance coordinate system according to the position information and the posture information; Based on the forward kinematics of the robot, coordinate transformation processing is performed on the second homogeneous transformation matrix to obtain the target homogeneous transformation matrix.

8. A robot registration device, characterized in that: include: a first acquisition unit for acquiring a target magnetic resonance image of a development marker mounted on a robot to be registered, the robot being placed on a designated component of a magnetic resonance device for generating the magnetic resonance image; A processing unit, configured to perform image segmentation processing on the target magnetic resonance image based on an adaptive threshold algorithm to obtain target point cloud data of the development marker; A first position determination unit, configured to determine position information of the imaging marker in a magnetic resonance coordinate system corresponding to the magnetic resonance device according to the target point cloud data; A first matrix determination unit, configured to determine a target homogeneous transformation matrix of an end tool coordinate system of the robot in the magnetic resonance coordinate system according to the position information; A registration unit is used to complete the registration operation of the robot using the target homogeneous transformation matrix.

9. A control device, 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, the robot registration method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the robot registration method according to any one of claims 1 to 7 is implemented.

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