Head MRI registration method, navigation method, system and program product

Abstract

The invention relates to the technical field of transcranial magnetic stimulation target positioning, and provides a head MRI registration method, navigation method, system and program product, the face of a patient is scanned through a 3D scanner to obtain scanning data, and first three-dimensional model data is generated according to the scanning data; collecting a reflective ball attached to the forehead of the patient by using an optical positioning instrument, and determining the coordinate position of the reflective ball in the space of the optical positioning instrument; scanning the face of the patient according to the coordinate position and generating second three-dimensional model data; performing coarse registration according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first conversion matrix; the three-dimensional model data and the MRI three-dimensional data are registered according to the first conversion matrix, the MRI three-dimensional data and the three-dimensional model data, a second conversion matrix is obtained, then positioning navigation is conducted on movement of the mechanical arm, and the head MRI registration and navigation precision and efficiency can be improved through a 3D scanner and an optical positioning instrument.

Description

Technical Field

[0001] The present application relates to the technical field of transcranial magnetic stimulation therapy, and in particular to a head MRI registration method, a navigation method, a system and a program product. Background Art

[0002] During the transcranial magnetic stimulation treatment with the help of a robotic arm, the magnetic therapy device at the end of the robotic arm needs to be guided to the target position of the patient's treatment with the help of an optical locator. During the treatment, the patient's head may deviate, affecting the treatment effect. The optical locator will follow the patient's head deviation in real time to improve the treatment effect. Before guidance, the patient's magnetic resonance imaging (MRI) data and the patient's real physical space need to be aligned, so the patient's MRI data needs to be reconstructed in three dimensions, and then the reconstructed facial three-dimensional data is spatially aligned with the patient's real facial data during treatment.

[0003] The existing head registration process is to mark facial feature points in MRI space, and then use the marked facial feature points to collect corresponding feature points on the corresponding patient's face with a collection probe, and the doctor uses the collection probe to collect feature points on the patient's face; the MRI space coordinates and the physical space coordinates of the real patient are converted through the marked facial feature points and the feature points at the preset point positions collected by the collection probe, so as to unify the MRI data space coordinates and the real patient space coordinates.

[0004] The disadvantage of this registration process is that when the doctor uses the acquisition probe to collect feature points on the patient's head, it is difficult to accurately collect the points corresponding to the MRI space. In addition, the registration requires high acquisition skills from the doctor, the registration effect is not ideal, the registration time is long, and the registration efficiency is low. Summary of the invention

[0005] In order to solve or at least partially solve the above technical problems, the present application provides a head MRI registration method, navigation method, system and program product, which can avoid errors caused by human acquisition, achieve registration more accurately, and improve the head MRI registration speed and navigation speed.

[0006] In a first aspect, the present application provides a head MRI registration method, comprising: Acquire MRI three-dimensional data of the patient; Scanning the patient's face with a 3D scanner to obtain scan data, and generating first three-dimensional model data according to the scan data; Using an optical locator to collect the reflective ball attached to the patient's forehead, and determine the coordinate position of the reflective ball in the optical locator space; Scanning the patient's face according to the coordinate position of the reflective ball in the optical locator space and generating second three-dimensional model data; Performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; The second three-dimensional model data and the MRI three-dimensional data are registered according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix.

[0007] In a second aspect, the present application provides a head MRI navigation method, comprising: Acquire MRI three-dimensional data of the patient; Scanning the patient's face with a 3D scanner to obtain scan data, and generating first three-dimensional model data according to the scan data; Using an optical locator to collect the reflective ball attached to the patient's forehead, and determine the coordinate position of the reflective ball in the optical locator space; Scanning the patient's face according to the coordinate position of the reflective ball in the optical locator space and generating second three-dimensional model data; Performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; registering the second three-dimensional model data with the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix; According to the position of the reflective ball in the optical locator space and the second conversion matrix, the movement of the robotic arm is positioned and navigated to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment.

[0008] In a third aspect, the present application provides a head MRI registration system, comprising: An acquisition module, used for acquiring MRI three-dimensional data of a patient; The acquisition module is further used to perform a facial scan on the patient using a 3D scanner to obtain scan data, and generate first three-dimensional model data according to the scan data; A collection module, used to collect the reflective ball attached to the patient's forehead using an optical locator, and determine the coordinate position of the reflective ball in the optical locator space; The acquisition module is further used to scan the patient's face according to the coordinate position of the reflective ball in the optical locator space and generate second three-dimensional model data; a registration module, configured to perform coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; The registration module is further used to register the second three-dimensional model data and the MRI three-dimensional data according to the first transformation matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second transformation matrix.

[0009] In a fourth aspect, the present application provides a head MRI navigation system, comprising: An acquisition module, used for acquiring MRI three-dimensional data of a patient; The acquisition module is further used to perform a facial scan on the patient using a 3D scanner to obtain scan data, and generate first three-dimensional model data according to the scan data; A collection module, used to collect the reflective ball attached to the patient's forehead using an optical locator, and determine the coordinate position of the reflective ball in the optical locator space; The acquisition module is further used to scan the patient's face according to the coordinate position of the reflective ball in the optical locator space and generate second three-dimensional model data; a registration module, configured to perform coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; The registration module is further used to register the second three-dimensional model data and the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix; The navigation module is used to locate and navigate the movement of the robotic arm according to the position of the reflective ball in the optical locator space and the second conversion matrix, so as to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment.

[0010] In a fifth aspect, an embodiment of the present application also provides a head MRI registration system, comprising a processor and a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the program including steps for the head MRI registration method as described in the first aspect.

[0011] In the sixth aspect, an embodiment of the present application also provides a head MRI navigation system, comprising a processor and a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the programs comprising steps for the head MRI navigation method as described in the second aspect.

[0012] In a seventh aspect, an embodiment of the present application further provides a computer program product, which, when executed by a computer, enables the computer to execute the head MRI registration method of the first aspect or the head MRI navigation method of the second aspect.

[0013] The head MRI registration method of the implementation mode of the present application performs a facial scan on the patient through a 3D scanner to obtain scanning data, and generates first three-dimensional model data according to the scanning data; uses an optical locator to collect a reflective ball attached to the patient's forehead, and determines the coordinate position of the reflective ball in the optical locator space; scans the patient's face according to the coordinate position of the reflective ball in the optical locator space and generates second three-dimensional model data; performs coordinate conversion on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data, and the second three-dimensional model data to obtain a first conversion matrix; aligns the three-dimensional model data and the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data, and the three-dimensional model data to obtain a second conversion matrix. Furthermore, the head MRI navigation method can position and navigate the movement of the robotic arm according to the position of the reflective ball in the optical locator space and the second conversion matrix, so as to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment. Thus, the accuracy and efficiency of the head MRI registration can be improved by the 3D scanner and the optical locator, and the accuracy and efficiency of transcranial magnetic stimulation treatment can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the implementation of the present application, the following is a brief introduction to the relevant drawings. It is understood that the drawings described below are only used to illustrate some implementations of the present application, and ordinary technicians in this field can also obtain many other technical features and connection relationships not mentioned in this article based on these drawings.

[0015] Figure 1 A schematic diagram of the structure of a head MRI registration method provided in an embodiment of the present application; Figure 2 A schematic diagram showing a method of performing face recognition on MRI three-dimensional data by using a preset face recognition model to obtain a first face feature point provided in an embodiment of the present application; Figure 3 A schematic diagram showing a demonstration of marking a first preset feature point on a first three-dimensional model corresponding to first three-dimensional model data provided in an embodiment of the present application; Figure 4 A schematic diagram showing a rectangular face area of ​​a human face captured in an RGB image provided by an embodiment of the present application; Figure 5 A schematic diagram showing a method of mapping a rectangular face area to a depth map provided in an embodiment of the present application; Figure 6 A schematic diagram showing the mapping of a rectangular face area of ​​an RGB image to MRI three-dimensional data during precise registration provided by an embodiment of the present application; Figure 7 A schematic diagram showing a method of accurately registering MRI three-dimensional data with second three-dimensional model data provided by an embodiment of the present application; Figure 8 A schematic diagram of the structure of another head MRI registration method provided in an embodiment of the present application; Fig. 9 A schematic diagram of the structure of a head MRI registration system provided in an embodiment of the present application; Fig.10 A schematic diagram of the structure of a head MRI registration system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0017] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0018] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0019] The technical solutions in the embodiments of the present application will be described in detail below in conjunction with the drawings in the embodiments of the present application.

[0020] Embodiment 1 like Figure 1 As shown, Figure 1 A schematic diagram of a head MRI registration method provided in an embodiment of the present application is provided. An embodiment of the present application proposes a head MRI registration method, the method comprising: 101. Obtain MRI three-dimensional data of the patient.

[0021] Among them, a magnetic resonance imaging device can be used to collect magnetic resonance imaging (MRI) data of the subject, and MRI three-dimensional data can be generated according to the magnetic resonance imaging data.

[0022] 102. Scan the patient's face with a 3D scanner to obtain scan data, and generate first three-dimensional model data according to the scan data.

[0023] The scanning data includes a GRB map, a depth map and a point cloud corresponding to the depth map. Specifically, the 3D scanner can be registered with the optical locator so that the origins of the 3D scanner and the optical locator are in the same coordinate system to determine the relative position relationship between the 3D scanner and the optical locator; the patient's face is scanned with a 3D scanner to obtain scanning data, and first three-dimensional model data is generated based on the scanning data to mark the first preset feature point corresponding to the MRI three-dimensional data on the first three-dimensional model corresponding to the first three-dimensional model data.

[0024] 103. Use an optical locator to collect the reflective ball attached to the patient's forehead and determine the coordinate position of the reflective ball in the optical locator space.

[0025] Among them, an optical locator is used to collect the reflective ball attached to the patient's forehead, and the coordinate position of the reflective ball in the optical locator space can be known.

[0026] 104. Scan the patient's face according to the coordinate position of the reflective ball in the optical locator space and generate second three-dimensional model data.

[0027] Among them, after using the reflective ball to determine the coordinate position of the reflective ball in the optical locator space, the second three-dimensional model data can be accurately scanned and generated.

[0028] 105. Perform coordinate transformation on MRI space coordinates and 3D scanner space coordinates according to the MRI three-dimensional data, the first three-dimensional model data, and the second three-dimensional model data to obtain a first transformation matrix.

[0029] Among them, the process of performing coordinate transformation to obtain the first transformation matrix can be understood as rough alignment, the purpose of which is to increase the overlap of the two sets of data as much as possible through the transformation matrix (rotation and translation).

[0030] Specifically, the first three-dimensional model data is used for feature point marking, and the second three-dimensional model data is used for coordinate conversion with the MRI three-dimensional data. Feature points can be marked at the locations where the two sets of data (the second three-dimensional model data and the MRI three-dimensional data) have the same features, and then the matrix transformation of the two sets of data can be obtained through the conversion of the feature points.

[0031] 106. Align the second three-dimensional model data and the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data, and the second three-dimensional model data to obtain a second conversion matrix.

[0032] The first transformation matrix is ​​used to determine the initial position for registering the MRI three-dimensional data and the three-dimensional model data of the partial area of ​​the face; the process of performing the registration to obtain the second transformation matrix can be understood as precise registration, such as Figure 7 As shown, it is a demonstration diagram of a precise registration of MRI three-dimensional data and second three-dimensional model data. In this scheme, the two sets of data (MRI three-dimensional data and second three-dimensional model data) are preliminarily aligned through coarse registration to find a rough matching relationship, so as to provide a good initial position for subsequent precise registration; further, through precise registration, the optimal transformation matrix is ​​calculated to minimize the distance between corresponding points in the two spaces (MRI space and 3D scanner space) to achieve high-precision registration.

[0033] Specifically, the initial position for aligning the MRI three-dimensional data and the three-dimensional model data of the partial facial area can be determined according to the first transformation matrix; then the second three-dimensional model data and the MRI three-dimensional data are aligned according to the initial position to obtain the second transformation matrix, thereby achieving precise alignment.

[0034] The implementation mode of the present application is a head MRI registration method, which performs a facial scan on a patient through a 3D scanner to obtain scanning data, and generates first three-dimensional model data according to the scanning data; uses an optical locator to collect a reflective ball attached to the patient's forehead, and determines the coordinate position of the reflective ball in the optical locator space; scans the patient's face according to the coordinate position of the reflective ball in the optical locator space and generates second three-dimensional model data; performs coordinate conversion on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data, and the second three-dimensional model data to obtain a first conversion matrix; aligns the three-dimensional model data and the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data, and the three-dimensional model data to obtain a second conversion matrix. Furthermore, the head MRI navigation method can position and navigate the movement of the robotic arm according to the position of the reflective ball in the optical locator space and the second conversion matrix, so as to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment, thereby improving the accuracy and efficiency of the head MRI registration through the 3D scanner and the optical locator, and improving the accuracy and efficiency of transcranial magnetic stimulation treatment.

[0035] Optionally, acquiring MRI three-dimensional data of the patient includes: acquiring magnetic resonance imaging data of the patient; The magnetic resonance imaging data is three-dimensionally reconstructed to obtain MRI three-dimensional data.

[0036] Among them, magnetic resonance brain imaging may include functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI). Three-dimensional reconstruction can be performed based on the functional magnetic resonance images and the structural magnetic resonance images to obtain MRI three-dimensional data.

[0037] Optionally, performing coordinate transformation on MRI space coordinates and 3D scanner space coordinates according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix includes: marking a first preset feature point corresponding to the MRI three-dimensional data on a first three-dimensional model corresponding to the first three-dimensional model data; Marking a second preset feature point corresponding to the first preset feature point on the second three-dimensional model; Coordinate transformation is performed on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data and the second preset feature points to obtain a first transformation matrix.

[0038] Among them, Figure 3As shown, it is a demonstration schematic diagram of marking a first preset feature point on a first three-dimensional model corresponding to the first three-dimensional model data. This solution can mark the facial feature points of the first three-dimensional model scanned by a 3D scanner by adopting a face recognition model to obtain the first preset feature point; the two sets of data (MRI three-dimensional data and second three-dimensional model data) are preliminarily aligned through coarse registration to find a rough matching relationship, thereby providing a better initial position for subsequent precise registration.

[0039] Specifically, first preset feature points corresponding to the MRI three-dimensional data are marked on the first three-dimensional model according to the MRI three-dimensional data; then, second preset feature points corresponding to the first preset feature points are marked on the second three-dimensional model, so that the second preset feature points can be used for coarse alignment to obtain a first transformation matrix.

[0040] The degree of overlap between the two sets of data is increased as much as possible through the transformation matrix (rotation and translation). The first three-dimensional model data is used for feature point marking, and the second three-dimensional model data is used for coordinate transformation with the MRI three-dimensional data. Feature points can be marked at the locations where the two sets of data (the second three-dimensional model data and the MRI three-dimensional data) have the same features. Then, the matrix transformation of the two sets of data is obtained through the transformation of the feature points to obtain the first transformation matrix.

[0041] Optionally, performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data and the second three-dimensional model data to obtain a first transformation matrix includes: Performing face recognition on the MRI three-dimensional data using a preset face recognition model to obtain a first face feature point; Coordinate transformation is performed on the MRI space coordinates and the 3D scanner space coordinates according to the first facial feature points and the second preset feature points to obtain a first transformation matrix.

[0042] Among them, Figure 2 As shown, it is a demonstration schematic diagram of performing face recognition on MRI three-dimensional data through a preset face recognition model to obtain a first face feature point; specifically, face recognition can be performed on MRI three-dimensional data through a preset face recognition model to obtain a first face feature point. By adopting a face recognition model, this solution can more accurately mark the face feature points of the MRI three-dimensional model; the face recognition model can be pre-trained, specifically, three-dimensional point cloud sample data of the face can be obtained through a 3D scanner; MRI point cloud sample data can be obtained; the three-dimensional point cloud sample data and MRI point cloud sample data are trained through a PointNet network model to obtain the preset face recognition model.

[0043] In this solution, facial feature points can be recognized through an AI model. Specifically, face recognition is performed on the MRI three-dimensional data through a preset face recognition model to obtain a first facial feature point, and then the first facial feature point is used for coarse alignment to obtain a first transformation matrix.

[0044] Optionally, the scan data includes a depth map; and registering the second three-dimensional model data with the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data, and the second three-dimensional model data to obtain a second conversion matrix includes: Cropping the face area on the depth map to obtain a partial face area; The partial face area and the MRI three-dimensional data are registered according to the first conversion matrix, the MRI three-dimensional data and the three-dimensional model data of the partial face area to obtain a second conversion matrix.

[0045] Among them, by cropping the face area on the depth map to obtain the partial face area, the partial face area is precisely registered, which can improve the registration speed and accuracy.

[0046] Optionally, registering the partial face area with the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data and the three-dimensional model data of the partial face area to obtain a second conversion matrix includes: Determine an initial position for registering the MRI three-dimensional data and the three-dimensional model data of the partial face area according to the first transformation matrix; Performing point cloud set sampling and preprocessing on the MRI three-dimensional data and the three-dimensional model data of the partial face area to obtain a preprocessed target point cloud set and an input point cloud set; the input point cloud set corresponds to the three-dimensional model data of the partial face area, and the target point cloud set corresponds to the MRI three-dimensional data; The target point cloud set and the input point cloud set are matched with each other according to the initial position, wherein the point cloud of the input point cloud set is transformed into the coordinate system corresponding to the target point cloud set by constructing a transformation matrix, and the error function between the transformed source point cloud and the target point cloud is estimated. When it is determined that the error function converges, a second transformation matrix is ​​obtained.

[0047] Among them, the target point cloud set P = {p1, p2, ..., p n} and the input point cloud set X = {x1, x2, ..., x n}Perform point cloud matching and construct the transformation matrix (R, t). The error function is: .

[0048] Among them, N is the number of point clouds of target points.

[0049] Optionally, determining an initial position for registering the MRI three-dimensional data and the three-dimensional model data of the partial face area according to the first transformation matrix includes: The MRI three-dimensional data and the three-dimensional model data of the partial face area are rotated and translated according to the first transformation matrix, so that the MRI three-dimensional data and the three-dimensional model data of the partial face area are successfully matched to obtain the initial position.

[0050] Optionally, the scan data further includes an RGB image, and the step of cropping the face area on the depth image to obtain a partial face area includes: Collect the face rectangular area of ​​the RGB image; The face rectangular area is mapped to the depth map to obtain the face partial area of ​​the depth map rectangle.

[0051] like Figure 4 As shown in FIG. 1 , a schematic diagram of collecting a rectangular face area of ​​an RGB image is shown. Figure 5 As shown in FIG. 1 , it is a demonstration diagram of mapping a rectangular face area to a depth map; Figure 6 As shown, it is a demonstration schematic diagram of mapping the rectangular face area of ​​the RGB image to the MRI three-dimensional data during precise registration. By collecting the rectangular face area of ​​the RGB image, mapping the rectangular face area to the depth map, obtaining the partial face area of ​​the depth map rectangle, and performing precise registration on the partial face area, the registration speed and accuracy can be improved.

[0052] Embodiment 2 like Figure 8 As shown, one embodiment of the present application proposes another head MRI registration method, Figure 8 A schematic flow chart of another head MRI registration method provided in an embodiment of the present application, the method comprising: 201. Obtain magnetic resonance imaging data of a patient.

[0053] 202. Perform three-dimensional reconstruction on the magnetic resonance imaging data to obtain MRI three-dimensional data.

[0054] 203. Scan the patient's face with a 3D scanner to obtain scan data, and generate first three-dimensional model data according to the scan data.

[0055] 204. Use an optical locator to collect the reflective ball attached to the patient's forehead and determine the coordinate position of the reflective ball in the optical locator space.

[0056] 205. Scan the patient's face according to the coordinate position of the reflective ball in the optical locator space and generate second three-dimensional model data.

[0057] 206. Mark a first preset feature point corresponding to the MRI three-dimensional data on a first three-dimensional model corresponding to the first three-dimensional model data.

[0058] 207. Mark a second preset feature point corresponding to the first preset feature point on the second three-dimensional model.

[0059] 208. Perform coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data and the second preset feature points to obtain a first transformation matrix.

[0060] 209. Crop the face area on the depth map to obtain a partial face area.

[0061] 210. Determine an initial position for registering the MRI three-dimensional data and the three-dimensional model data of the partial facial area according to the first transformation matrix.

[0062] 211. Perform point cloud set sampling and preprocessing on the MRI three-dimensional data and the three-dimensional model data of the partial face area to obtain a preprocessed target point cloud set and an input point cloud set.

[0063] 212. Perform point cloud matching on the target point cloud set and the input point cloud set according to the initial position, wherein the point cloud of the input point cloud set is transformed into the coordinate system corresponding to the target point cloud set by constructing a transformation matrix, and the error function between the source point cloud and the target point cloud after the transformation is estimated. When it is determined that the error function converges, a second transformation matrix is ​​obtained.

[0064] In this embodiment, a first preset feature point corresponding to the MRI three-dimensional data is marked on the first three-dimensional model corresponding to the first three-dimensional model data, and a second preset feature point corresponding to the first preset feature point is marked on the second three-dimensional model, and a coordinate transformation is performed on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data and the second preset feature point to obtain a first transformation matrix, and the face area on the depth map is cropped to obtain a partial face area, and an initial position for registering the MRI three-dimensional data and the three-dimensional model data of the partial face area is determined according to the first transformation matrix, and the M The RI three-dimensional data and the three-dimensional model data of the partial face area are sampled and preprocessed to obtain a preprocessed target point cloud set and an input point cloud set, and the target point cloud set and the input point cloud set are matched according to the initial position, wherein the point cloud of the input point cloud set is transformed into a coordinate system corresponding to the target point cloud set by constructing a transformation matrix, and the error function between the transformed source point cloud and the target point cloud is estimated. When it is determined that the error function converges, a second transformation matrix is ​​obtained, and the rectangular face area is mapped to the depth map, and the partial face area of ​​the depth map rectangle is obtained. The partial face area is precisely aligned, which can improve the alignment speed and accuracy.

[0065] Embodiment 3 One embodiment of the present application proposes a head MRI navigation method, the method comprising: Acquire MRI three-dimensional data of the patient; Scanning the patient's face with a 3D scanner to obtain scan data, and generating first three-dimensional model data according to the scan data; Using an optical locator to collect the reflective ball attached to the patient's forehead, and determine the coordinate position of the reflective ball in the optical locator space; Scanning the patient's face according to the coordinate position of the reflective ball in the optical locator space and generating second three-dimensional model data; Performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; registering the second three-dimensional model data with the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix; According to the position of the reflective ball in the optical locator space and the second conversion matrix, the movement of the robotic arm is positioned and navigated to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment.

[0066] Among them, the steps of the above method can refer to the specific implementation steps of the aforementioned head MRI registration method, which will not be repeated here.

[0067] The patient's face is scanned by a 3D scanner to obtain scanning data, and the first three-dimensional model data is generated according to the scanning data; the reflective ball attached to the patient's forehead is collected by an optical locator to determine the coordinate position of the reflective ball in the optical locator space; the patient's face is scanned according to the coordinate position of the reflective ball in the optical locator space and the second three-dimensional model data is generated; the MRI space coordinates and the space coordinates of the 3D scanner are converted according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first conversion matrix; the three-dimensional model data and the MRI three-dimensional data are converted according to the first conversion matrix, the MRI three-dimensional data and the three-dimensional model data The optical locator space and the optical locator space are aligned to obtain a second conversion matrix. Further, the head MRI navigation method can position and navigate the movement of the robotic arm according to the position of the reflective ball in the optical locator space and the second conversion matrix, so as to move the TMS coil to the patient's head magnetic stimulation point to be magnetically stimulated for treatment. By positioning and navigating the movement of the robotic arm, the TMS coil can be moved to the patient's head magnetic stimulation point to be magnetically stimulated for treatment. Therefore, the accuracy and efficiency of head MRI alignment can be improved by using a 3D scanner and an optical locator, and the accuracy and efficiency of transcranial magnetic stimulation treatment can be improved.

[0068] Embodiment 4 like Fig. 9 , Fig. 9 A head MRI registration system 300 provided in the application embodiment includes: An acquisition module 301 is used to acquire MRI three-dimensional data of a patient; The acquisition module 301 is further used to perform a facial scan on the patient using a 3D scanner to obtain scan data, and generate first three-dimensional model data according to the scan data; The acquisition module 302 is used to use the optical locator to acquire the reflective ball attached to the patient's forehead and determine the coordinate position of the reflective ball in the optical locator space; The acquisition module 301 is further used to scan the patient's face according to the coordinate position of the reflective ball in the optical locator space and generate second three-dimensional model data; A registration module 303, configured to perform coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; The registration module 303 is further used to register the second three-dimensional model data and the MRI three-dimensional data according to the first transformation matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second transformation matrix.

[0069] Optionally, in the aspect of acquiring the patient's MRI three-dimensional data, the acquisition module 301 is specifically used for: acquiring magnetic resonance imaging data of the patient; The magnetic resonance imaging data is three-dimensionally reconstructed to obtain MRI three-dimensional data.

[0070] Optionally, in the aspect of performing coordinate conversion on MRI space coordinates and space coordinates of a 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first conversion matrix, the registration module 303 is specifically used for: marking a first preset feature point corresponding to the MRI three-dimensional data on a first three-dimensional model corresponding to the first three-dimensional model data; Marking a second preset feature point corresponding to the first preset feature point on the second three-dimensional model; Coordinate transformation is performed on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data and the second preset feature points to obtain a first transformation matrix.

[0071] Optionally, in the aspect of performing coordinate conversion on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data and the second preset feature points to obtain a first conversion matrix, the registration module 303 is specifically used for: Performing face recognition on the MRI three-dimensional data using a preset face recognition model to obtain a first face feature point; Coordinate transformation is performed on the MRI space coordinates and the 3D scanner space coordinates according to the first facial feature points and the second preset feature points to obtain a first transformation matrix.

[0072] Optionally, the registration module 303 is further used for: Obtain three-dimensional point cloud sample data of the face through a 3D scanner; obtain MRI point cloud sample data; The three-dimensional point cloud sample data and the MRI point cloud sample data are trained through the PointNet network model to obtain the preset face recognition model.

[0073] Optionally, the scan data includes a depth map; in the aspect of registering the second three-dimensional model data and the MRI three-dimensional data according to the first transformation matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain the second transformation matrix, the registration module 303 is used to: Cropping the face area on the depth map to obtain a partial face area; The partial face area and the MRI three-dimensional data are registered according to the first conversion matrix, the MRI three-dimensional data and the three-dimensional model data of the partial face area to obtain a second conversion matrix.

[0074] Optionally, in the aspect of registering the partial face area with the MRI three-dimensional data according to the first transformation matrix, the MRI three-dimensional data and the three-dimensional model data of the partial face area to obtain the second transformation matrix, the registration module 303 is specifically used for: Determine an initial position for registering the MRI three-dimensional data and the three-dimensional model data of the partial face area according to the first transformation matrix; Performing point cloud set sampling and preprocessing on the MRI three-dimensional data and the three-dimensional model data of the partial face area to obtain a preprocessed target point cloud set and an input point cloud set; the input point cloud set corresponds to the three-dimensional model data of the partial face area, and the target point cloud set corresponds to the MRI three-dimensional data; The target point cloud set and the input point cloud set are matched with each other according to the initial position, wherein the point cloud of the input point cloud set is transformed into the coordinate system corresponding to the target point cloud set by constructing a transformation matrix, and the error function between the transformed source point cloud and the target point cloud is estimated. When it is determined that the error function converges, a second transformation matrix is ​​obtained.

[0075] Optionally, in determining the initial position for registering the MRI three-dimensional data and the three-dimensional model data of the partial face area according to the first transformation matrix, the registration module 303 is specifically used to: The MRI three-dimensional data and the three-dimensional model data of the partial face area are rotated and translated according to the first transformation matrix, so that the MRI three-dimensional data and the three-dimensional model data of the partial face area are successfully matched to obtain the initial position.

[0076] Optionally, the scan data further includes an RGB image. In terms of clipping the face area on the depth image to obtain a partial face area, the registration module 303 is specifically configured to: Collect the face rectangular area of ​​the RGB image; The face rectangular area is mapped to the depth map to obtain the face partial area of ​​the depth map rectangle.

[0077] The head MRI registration method of this embodiment obtains magnetic resonance brain imaging data of the subject, and the magnetic resonance brain imaging data includes functional magnetic resonance images and structural magnetic resonance images; preprocesses the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data, and preprocesses the magnetic resonance brain imaging data to eliminate noise introduced in the signal acquisition process, retain the real functional activity of the subject's brain, thereby providing a reliable basis for subsequent functional connection calculations; then, the superficial brain area is divided according to the preprocessed magnetic resonance brain imaging data to obtain multiple functional sub-areas; the individual target stimulation target of transcranial magnetic stimulation is determined according to the multiple functional sub-areas, by dividing the superficial brain area into several functional sub-areas, and then using the functional sub-areas as the minimum search unit to search for individualized optimal targets one by one. This scheme comprehensively considers the superficial cortex of the brain The spatial and temporal dual characteristics of the layer, the spatial arrangement of neurons in the brain is continuous, neurons with high functional similarity are usually closer in space, and the functional sub-regions of the superficial brain area are divided according to the temporal characteristic of the functional connection strength between voxels, which reflects the functional similarity between different voxels, and the spatial characteristic is the spatial distance between different voxels, which aims to constrain the division of functional sub-regions; by dividing the superficial brain area into functional sub-regions, the minimum unit of target search can better reflect the functional characteristics of the brain, and the voxels in each functional sub-region correspond to similar cognitive functions. This division can reduce the fluctuation of the functional connection strength between different voxels, and effectively offset the instability of resting-state functional connections within individual subjects. Even if the connection strength of some voxels changes over time, the functional characteristics of the entire functional sub-region remain relatively consistent, thereby improving the robustness of target positioning.

[0078] Embodiment 5 A head MRI navigation system provided in an embodiment of the present application includes: An acquisition module, used for acquiring MRI three-dimensional data of a patient; The acquisition module is further used to perform a facial scan on the patient using a 3D scanner to obtain scan data, and generate first three-dimensional model data according to the scan data; A collection module, used to collect the reflective ball attached to the patient's forehead using an optical locator, and determine the coordinate position of the reflective ball in the optical locator space; The acquisition module is further used to scan the patient's face according to the coordinate position of the reflective ball in the optical locator space and generate second three-dimensional model data; a registration module, configured to perform coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; The registration module is further used to register the second three-dimensional model data and the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix; The navigation module is used to locate and navigate the movement of the robotic arm according to the position of the reflective ball in the optical locator space and the second conversion matrix, so as to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment.

[0079] Among them, the specific steps of the above system can refer to the specific implementation steps of the aforementioned head MRI registration method, which will not be repeated here.

[0080] The patient's face is scanned by a 3D scanner to obtain scanning data, and the first three-dimensional model data is generated according to the scanning data; the reflective ball attached to the patient's forehead is collected by an optical locator to determine the coordinate position of the reflective ball in the optical locator space; the patient's face is scanned according to the coordinate position of the reflective ball in the optical locator space and the second three-dimensional model data is generated; the MRI space coordinates and the space coordinates of the 3D scanner are converted according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first conversion matrix; the three-dimensional model data and the MRI three-dimensional data are converted according to the first conversion matrix, the MRI three-dimensional data and the three-dimensional model data The optical locator space and the optical locator space are aligned to obtain a second conversion matrix. Further, the head MRI navigation method can position and navigate the movement of the robotic arm according to the position of the reflective ball in the optical locator space and the second conversion matrix, so as to move the TMS coil to the patient's head magnetic stimulation point to be magnetically stimulated for treatment. By positioning and navigating the movement of the robotic arm, the TMS coil can be moved to the patient's head magnetic stimulation point to be magnetically stimulated for treatment. Therefore, the accuracy and efficiency of head MRI alignment can be improved by using a 3D scanner and an optical locator, and the accuracy and efficiency of transcranial magnetic stimulation treatment can be improved.

[0081] Embodiment 6 like Fig.10 , Fig.10 The head MRI registration system provided in the application embodiment includes a processor 410 and a memory 420; and one or more programs, one or more programs are stored in the memory, the memory 420 can be a high-speed RAM memory, or a non-volatile memory (non-volatile memory), such as a disk memory. The memory 420 is used to store a set of program codes, and the processor 410 is used to call the program code stored in the memory 420 to perform the following operations: Acquire MRI three-dimensional data of the patient; Scanning the patient's face with a 3D scanner to obtain scan data, and generating first three-dimensional model data according to the scan data; Using an optical locator to collect the reflective ball attached to the patient's forehead, and determine the coordinate position of the reflective ball in the optical locator space; Scanning the patient's face according to the coordinate position of the reflective ball in the optical locator space and generating second three-dimensional model data; Performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; The second three-dimensional model data and the MRI three-dimensional data are registered according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix.

[0082] The head MRI registration system of this embodiment obtains magnetic resonance brain imaging data of the subject, and the magnetic resonance brain imaging data includes functional magnetic resonance images and structural magnetic resonance images; preprocesses the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data, and preprocesses the magnetic resonance brain imaging data to eliminate noise introduced in the signal acquisition process and retain the real functional activity of the subject's brain, thereby providing a reliable basis for subsequent functional connection calculations; then, the superficial brain area is divided according to the preprocessed magnetic resonance brain imaging data to obtain multiple functional sub-areas; the individual target stimulation target of transcranial magnetic stimulation is determined according to the multiple functional sub-areas, and the superficial brain area is divided into several functional sub-areas, and then the functional sub-areas are used as the minimum search unit to search for the individual optimal target in each functional sub-area. This scheme comprehensively considers the superficial cortex of the brain The spatial and temporal dual characteristics of the layer, the spatial arrangement of neurons in the brain is continuous, neurons with high functional similarity are usually closer in space, and the functional sub-regions of the superficial brain area are divided according to the temporal characteristic of the functional connection strength between voxels, which reflects the functional similarity between different voxels, and the spatial characteristic is the spatial distance between different voxels, which aims to constrain the division of functional sub-regions; by dividing the superficial brain area into functional sub-regions, the minimum unit of target search can better reflect the functional characteristics of the brain, and the voxels in each functional sub-region correspond to similar cognitive functions. This division can reduce the fluctuation of the functional connection strength between different voxels, and effectively offset the instability of resting-state functional connections within individual subjects. Even if the connection strength of some voxels changes over time, the functional characteristics of the entire functional sub-region remain relatively consistent, thereby improving the robustness of target positioning.

[0083] Embodiment 7 The embodiment of the present application provides a head MRI navigation system, which includes a processor 410 and a memory 420; and one or more programs, one or more programs are stored in the memory, and the memory 420 can be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as a disk memory. The memory 420 is used to store a set of program codes, and the processor 410 is used to call the program code stored in the memory 420 to perform the following operations: Acquire MRI three-dimensional data of the patient; Scanning the patient's face with a 3D scanner to obtain scan data, and generating first three-dimensional model data according to the scan data; Using an optical locator to collect the reflective ball attached to the patient's forehead, and determine the coordinate position of the reflective ball in the optical locator space; Scanning the patient's face according to the coordinate position of the reflective ball in the optical locator space and generating second three-dimensional model data; Performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; registering the second three-dimensional model data with the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix; According to the position of the reflective ball in the optical locator space and the second conversion matrix, the movement of the robotic arm is positioned and navigated to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment.

[0084] The head MRI navigation system of this embodiment performs a facial scan on the patient through a 3D scanner to obtain scanning data, and generates first three-dimensional model data according to the scanning data; uses an optical locator to collect a reflective ball attached to the patient's forehead and determines the coordinate position of the reflective ball in the optical locator space; scans the patient's face according to the coordinate position of the reflective ball in the optical locator space and generates second three-dimensional model data; performs coordinate conversion on the MRI space coordinates and the 3D scanner space coordinates according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first conversion matrix; converts the three-dimensional model data into a three-dimensional model matrix according to the first conversion matrix, the MRI three-dimensional data and the three-dimensional model data The three-dimensional data of the MRI is aligned to obtain a second conversion matrix. Furthermore, the head MRI navigation method can position and navigate the movement of the robotic arm according to the position of the reflective ball in the optical locator space and the second conversion matrix, so as to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment. By positioning and navigating the movement of the robotic arm, the TMS coil can be moved to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment. Therefore, the accuracy and efficiency of the head MRI alignment can be improved by using a 3D scanner and an optical locator, and the accuracy and efficiency of transcranial magnetic stimulation treatment can be improved.

[0085] The present application also provides a computer program product, wherein the computer program product includes a non-transitory computer-readable program product storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in any head MRI registration method or head MRI navigation method described in the present application. The computer program product may be a software installation package.

[0086] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other changes to the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple situations. A single processor or other unit may implement several functions listed in a claim. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0087] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, devices (equipment), or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The computer program is stored / distributed in a suitable medium, provided together with other hardware or as part of the hardware, or may take other distribution forms, such as through the Internet or other wired or wireless telecommunications systems.

[0088] The present application is described with reference to the flowcharts and / or block diagrams of the methods, apparatus (devices) and computer program products of the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable human-vehicle trajectory analysis device to produce a machine, so that the instructions executed by the processor of the computer or other programmable human-vehicle trajectory analysis device generate instructions for implementing the processes in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0089] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable vehicle trajectory analysis device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0090] These computer program instructions can also be loaded onto a computer or other programmable vehicle trajectory analysis device, so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0091] Although the present application has been described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the drawings are merely exemplary illustrations of the present application as defined by the appended claims, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A head MRI registration method, characterized in that: include: Acquire MRI three-dimensional data of the patient; Scanning the patient's face with a 3D scanner to obtain scan data, and generating first three-dimensional model data according to the scan data; Using an optical locator to collect the reflective ball attached to the patient's forehead, and determine the coordinate position of the reflective ball in the optical locator space; Scanning the patient's face according to the coordinate position of the reflective ball in the optical locator space and generating second three-dimensional model data; Performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; The second three-dimensional model data and the MRI three-dimensional data are registered according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix.

2. The head MRI registration method according to claim 1, characterized in that: The step of acquiring MRI three-dimensional data of a patient comprises: acquiring magnetic resonance imaging data of the patient; The magnetic resonance imaging data is three-dimensionally reconstructed to obtain MRI three-dimensional data.

3. The head MRI registration method according to claim 1, characterized in that: The step of performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data, and the second three-dimensional model data to obtain a first transformation matrix includes: marking a first preset feature point corresponding to the MRI three-dimensional data on a first three-dimensional model corresponding to the first three-dimensional model data; Marking a second preset feature point corresponding to the first preset feature point on the second three-dimensional model; Coordinate transformation is performed on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data and the second preset feature points to obtain a first transformation matrix.

4. The head MRI registration method according to claim 3, characterized in that: The step of performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data and the second preset feature points to obtain a first transformation matrix includes: Performing face recognition on the MRI three-dimensional data using a preset face recognition model to obtain a first face feature point; Coordinate transformation is performed on the MRI space coordinates and the 3D scanner space coordinates according to the first facial feature points and the second preset feature points to obtain a first transformation matrix.

5. The head MRI registration method according to any one of claims 1 to 4, characterized in that: The scanning data includes a depth map; the second three-dimensional model data and the MRI three-dimensional data are registered according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix, including: Cropping the face area on the depth map to obtain a partial face area; The partial face area and the MRI three-dimensional data are registered according to the first conversion matrix, the MRI three-dimensional data and the three-dimensional model data of the partial face area to obtain a second conversion matrix.

6. The head MRI registration method according to claim 5, characterized in that: The registering the partial face region with the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data and the three-dimensional model data of the partial face region to obtain a second conversion matrix includes: Determine an initial position for registering the MRI three-dimensional data and the three-dimensional model data of the partial face area according to the first transformation matrix; Performing point cloud set sampling and preprocessing on the MRI three-dimensional data and the three-dimensional model data of the partial face area to obtain a preprocessed target point cloud set and an input point cloud set; the input point cloud set corresponds to the three-dimensional model data of the partial face area, and the target point cloud set corresponds to the MRI three-dimensional data; The target point cloud set and the input point cloud set are matched with each other according to the initial position, wherein the point cloud of the input point cloud set is transformed into the coordinate system corresponding to the target point cloud set by constructing a transformation matrix, and the error function between the transformed source point cloud and the target point cloud is estimated. When it is determined that the error function converges, a second transformation matrix is ​​obtained.

7. The head MRI registration method according to claim 6, characterized in that: The step of determining an initial position for registering the MRI three-dimensional data and the three-dimensional model data of the partial face area according to the first transformation matrix includes: The MRI three-dimensional data and the three-dimensional model data of the partial face area are rotated and translated according to the first transformation matrix, so that the MRI three-dimensional data and the three-dimensional model data of the partial face area are successfully matched to obtain the initial position.

8. The head MRI registration method according to claim 5, characterized in that: The scan data also includes an RGB image, and the face area on the depth image is cropped to obtain a partial face area, including: Collect the face rectangular area of ​​the RGB image; The face rectangular area is mapped to the depth map to obtain the face partial area of ​​the depth map rectangle.

9. A head MRI navigation method, characterized in that: include: Acquire MRI three-dimensional data of the patient; Scanning the patient's face with a 3D scanner to obtain scan data, and generating first three-dimensional model data according to the scan data; Using an optical locator to collect the reflective ball attached to the patient's forehead, and determine the coordinate position of the reflective ball in the optical locator space; Scanning the patient's face according to the coordinate position of the reflective ball in the optical locator space and generating second three-dimensional model data; Performing coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; registering the second three-dimensional model data with the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix; According to the position of the reflective ball in the optical locator space and the second conversion matrix, the movement of the robotic arm is positioned and navigated to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment.

10. A head MRI registration system, characterized in that: include: An acquisition module, used for acquiring MRI three-dimensional data of a patient; The acquisition module is further used to perform a facial scan on the patient using a 3D scanner to obtain scan data, and generate first three-dimensional model data according to the scan data; A collection module, used to collect the reflective ball attached to the patient's forehead using an optical locator, and determine the coordinate position of the reflective ball in the optical locator space; The acquisition module is further used to scan the patient's face according to the coordinate position of the reflective ball in the optical locator space and generate second three-dimensional model data; a registration module, configured to perform coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; The registration module is further used to register the second three-dimensional model data and the MRI three-dimensional data according to the first transformation matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second transformation matrix.

11. A head MRI navigation system, characterized in that: include: An acquisition module, used for acquiring MRI three-dimensional data of a patient; The acquisition module is further used to perform a facial scan on the patient using a 3D scanner to obtain scan data, and generate first three-dimensional model data according to the scan data; A collection module, used to collect the reflective ball attached to the patient's forehead using an optical locator, and determine the coordinate position of the reflective ball in the optical locator space; The acquisition module is further used to scan the patient's face according to the coordinate position of the reflective ball in the optical locator space and generate second three-dimensional model data; a registration module, configured to perform coordinate transformation on the MRI space coordinates and the space coordinates of the 3D scanner according to the MRI three-dimensional data, the first three-dimensional model data and the second three-dimensional model data to obtain a first transformation matrix; The registration module is further used to register the second three-dimensional model data and the MRI three-dimensional data according to the first conversion matrix, the MRI three-dimensional data and the second three-dimensional model data to obtain a second conversion matrix; The navigation module is used to locate and navigate the movement of the robotic arm according to the position of the reflective ball in the optical locator space and the second conversion matrix, so as to move the TMS coil to the magnetic stimulation point on the patient's head to be magnetically stimulated for treatment.

12. A head MRI registration system, characterized in that: The invention comprises a processor and a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, wherein the programs include steps for the head MRI registration method as described in any one of claims 1 to 8.

13. A head MRI navigation system, characterized in that: The invention comprises a processor and a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, wherein the programs include steps for the head MRI registration method as described in claim 9.

14. A computer program product, characterized in that The computer program of the computer program product can implement the steps of the head MRI navigation method according to claim 9 when executed by a processor.

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