Mapping method and device from grey matter target spot to scalp and electronic equipment

Abstract

The invention relates to a method and device for mapping grey matter target spots to scalp and electronic equipment. The method comprises the following steps: performing three-dimensional reconstruction on a scalp medical image to obtain a scalp three-dimensional model; obtaining a first nearest point location of a grey matter target spot in a scalp layer of the scalp three-dimensional model, wherein the grey matter target spot is a preset target spot on grey matter in the medical image; in the scalp layer, a plurality of search points around the first nearest point location are obtained, and the distance between each search point and the nearest point location is smaller than or equal to a preset distance; performing spherical fitting on each search point in the scalp layer to obtain a normal vector straight line of each search point; and determining a mapping point from the grey matter target spot to the scalp layer from the plurality of search points according to the linear distance between the grey matter target spot and each normal vector straight line. By means of the method, the problem of how to accurately find the target spot, mapped to the scalp, of the grey matter target spot in the transcranial magnetic treatment process is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of computer graphics, and in particular to a method, device and electronic equipment for mapping a gray matter target point to a scalp. Background Art

[0002] Transcranial Magnetic Stimulation (TMS) technology is a non-invasive neuromodulation technology that is non-invasive and painless, and is often used in the treatment of neuropsychiatric diseases in clinical practice. In today's existing medical equipment field, devices that combine patient images with navigation systems for transcranial magnetic stimulation treatment are also relatively common. However, since the target of transcranial magnetic therapy is on the gray matter, and transcranial magnetic therapy involves placing the coil on the scalp, relevant studies have shown that during transcranial magnetic therapy, for every 1 mm off-target, the dose loss can reach 40%. Therefore, it is particularly important to accurately find the gray matter target and map it to the target on the scalp. Summary of the invention

[0003] The present invention provides a method, device and electronic device for mapping gray matter target points to scalp, so as to solve the problem of how to accurately find the target points on the scalp from which gray matter target points are mapped during transcranial magnetic therapy.

[0004] The present invention provides a method for mapping gray matter target points to scalp, comprising:

[0005] Performing three-dimensional reconstruction on the medical image of the scalp to obtain a three-dimensional scalp model; and obtaining the first closest point of a gray matter target point in the scalp layer of the three-dimensional scalp model, wherein the gray matter target point is a preset target point on the gray matter in the medical image;

[0006] In the scalp layer, a plurality of search points around the first closest point are obtained, and the distance between each search point and the closest point is less than or equal to a preset distance;

[0007] Performing spherical fitting on each search point in the scalp layer to obtain a normal vector straight line of each search point;

[0008] According to the straight-line distance between the gray matter target point and each normal vector straight line, a mapping point from the gray matter target point to the scalp layer is determined from a plurality of search points.

[0009] According to the method for mapping gray matter target points to scalp provided by the present invention, the spherical fitting is performed on each search point in the scalp layer to obtain a normal vector straight line of each search point, including:

[0010] Taking each search point as the center, obtaining a plurality of vertices within a preset range in the scalp layer;

[0011] Perform spherical fitting according to the point cloud composed of multiple vertices, and obtain the spherical center point obtained after the spherical fitting;

[0012] According to each search point and the corresponding sphere center point, the normal vector line of each search point is obtained.

[0013] According to the method for mapping gray matter target points to scalp provided by the present invention, obtaining a plurality of search points around the first closest point in the scalp layer includes:

[0014] A search range and a search step are set according to the coordinates of the first closest point to obtain a plurality of search points in the scalp layer.

[0015] According to the method for mapping gray matter target points to scalp provided by the present invention, the step of setting the search range and the search step size according to the coordinates of the first closest point to obtain multiple search points in the scalp layer includes:

[0016] According to the search range and the search step length, setting the search step number and the search coordinates in three-dimensional coordinates;

[0017] The second closest point position of each search coordinate in the scalp layer is obtained, and the second closest point position is determined as the search point.

[0018] According to the method for mapping gray matter target points to scalp provided by the present invention, the three-dimensional reconstruction of the medical image of the scalp to obtain a three-dimensional scalp model includes:

[0019] Segment the medical image to obtain the medical image of the scalp;

[0020] The Marching Cubes algorithm is used to perform three-dimensional reconstruction of the medical images of the scalp to obtain a three-dimensional scalp model.

[0021] According to any one of the above-mentioned gray matter target point to scalp mapping methods provided by the present invention, the three-dimensional scalp model is a triangular mesh model.

[0022] The present invention also provides a mapping device from a gray matter target point to a scalp, comprising:

[0023] A first point acquisition unit is used to perform three-dimensional reconstruction on the medical image of the scalp to obtain a three-dimensional scalp model; and obtain the first closest point of a gray matter target point in the scalp layer of the three-dimensional scalp model, wherein the gray matter target point is a preset target point on the gray matter in the medical image;

[0024] A second point acquisition unit, in the scalp layer, acquires a plurality of search points around the first closest point, wherein the distance between each search point and the closest point is less than or equal to a preset distance;

[0025] A spherical fitting unit performs spherical fitting on each search point in the scalp layer to obtain a normal vector straight line of each search point;

[0026] A mapping point acquisition unit is used to determine a mapping point from the gray matter target point to the scalp layer from a plurality of search points according to a straight-line distance between the gray matter target point and each normal vector straight line.

[0027] The present invention also provides an electronic 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 program, the method for mapping a gray matter target point to a scalp as described in any one of the above is implemented.

[0028] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described methods for mapping gray matter targets to scalp.

[0029] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for mapping a gray matter target point to a scalp as described in any one of the above is implemented.

[0030] The gray matter target to scalp mapping method, system and electronic device provided by the present invention obtain a scalp three-dimensional model by processing the medical image of the scalp, then find the nearest point of the gray matter target on the scalp, perform step search based on the nearest point and calculate the fitting spherical surface normal vector of the search point, and calculate the distance between the straight line where the fitting spherical surface normal vector is located and the gray matter target. The search point corresponding to the minimum distance finally obtained is the target point mapped from the gray matter target to the scalp. The mapping error of the gray matter target to the scalp target is reduced, the TMS coil positioning is more accurate, and the therapeutic effect of transcranial magnetic stimulation is guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 It is a schematic diagram of the principle of the mapping method of gray matter target points to scalp in the related art provided by the present invention.

[0033] Figure 2 It is a schematic diagram of the process of the mapping method from gray matter target points to scalp provided by the present invention.

[0034] Figure 3It is a schematic diagram of the principle of the method for mapping gray matter target points to scalp provided by the present invention.

[0035] Figure 4 It is a schematic diagram of the structure of the mapping device from gray matter target point to scalp provided by the present invention.

[0036] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the descriptions used in this way can be interchanged where appropriate, so that the embodiments can be implemented in a sequence other than that illustrated or described in the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The naming or numbering of the steps that appear in the present application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The process steps that have been named or numbered can change the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved. The division of modules in this application is a logical division. There may be other division methods when it is implemented in actual applications. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection between units can be electrical or other similar forms, which are not limited in this application. In addition, the modules or submodules described as separate components may or may not be physically separated, may or may not be physical units, or may be distributed in multiple circuit units, and some or all of the units may be selected according to actual needs to achieve the purpose of the present application.

[0039] In the related technology of the present invention, the target point is mapped from the gray matter to the scalp according to the intersection of the point normal vector of the target point on the gray matter and the scalp or the nearest point of the gray matter target point on the scalp, thereby determining the target point of the coil on the scalp. The inventors found that, since the gray matter and the scalp are both curved surfaces with different curvatures, the point normal vector of the target point on the gray matter and the point normal vector of the corresponding scalp target point on the scalp are not on the same straight line, and the coil surface needs to be tangent to the scalp when the coil is positioned on the scalp. When the coil is working, the magnetic field generated by the coil acts on the gray matter perpendicular to the coil surface. Using the above method for target mapping will result in the coil being unable to accurately stimulate the gray matter target point after being positioned on the scalp target point, thereby greatly reducing the therapeutic effect on the patient. Figure 1 shown.

[0040] In an embodiment of the present invention, the head medical image data of the subject is segmented to obtain the medical image data of the scalp and the medical image data of the gray matter; the scalp image data is three-dimensionally reconstructed to obtain a three-dimensional model of the scalp. In an embodiment of the present invention, the gray matter target is a target planned in the image physical space of the gray matter, and the coordinates of the gray matter target are the coordinates of the image physical space. The coordinate system of the image physical space coincides with the coordinate system of the space where the scalp three-dimensional model is located.

[0041] The present invention provides a method, device and electronic device for mapping gray matter target points to scalp, so as to solve the problem of how to accurately find the target points on the scalp from which gray matter target points are mapped during transcranial magnetic therapy.

[0042] Combine the following Figure 2-Figure 5 The specific contents of the present invention are described.

[0043] Figure 2 is a flow chart of a method for mapping gray matter target points to scalp provided by the present invention, such as Figure 2 As shown, steps S201-S204 are included.

[0044] Step S201, three-dimensionally reconstruct the medical image of the scalp to obtain a three-dimensional scalp model; and obtain the first closest point of the gray matter target point in the scalp layer of the three-dimensional scalp model, where the gray matter target point is a preset target point on the gray matter in the medical image.

[0045] In a possible implementation manner, the three-dimensional scalp model is a triangular mesh model.

[0046] In the embodiment of the present invention, a triangle mesh model is a data structure used in computer graphics to build models for various irregular objects. It is mainly composed of a series of triangular facets, which are connected to each other through shared vertices to form a continuous mesh structure for simulating the surface of objects in the real world. In the present invention, a triangle mesh model corresponding to the scalp of the patient to be treated is established by simulation, which is used for the subsequent search for the first closest point of the gray matter target in the scalp layer.

[0047] In the embodiment of the present invention, the first closest point is used to represent the point closest to the gray matter target point in the scalp three-dimensional model. The gray matter target point in the embodiment of the present invention is the target point on the gray matter that the TMS coil needs to map when performing transcranial magnetic therapy.

[0048] In a possible implementation, performing three-dimensional reconstruction on a medical image of the scalp to obtain a three-dimensional scalp model includes:

[0049] Segment the medical image to obtain the medical image of the scalp;

[0050] The Marching Cubes algorithm is used to perform three-dimensional reconstruction of the medical images of the scalp to obtain a three-dimensional scalp model.

[0051] Exemplarily, the present invention finds the first closest point N of the gray matter target M on the scalp three-dimensional model by using the FindClosestPoint algorithm in VTK. VTK (Visualization Toolkit) is a powerful open source software system designed for three-dimensional computer graphics, image processing and visualization. It provides a wide range of tools and libraries, supporting everything from basic three-dimensional data rendering to complex image processing and interactive functions, and is widely used in many fields such as medical imaging, scientific computing, geographic information systems, and virtual reality.

[0052] In the embodiment of the present invention, the first closest point of the gray matter target point M on the scalp three-dimensional model may also be obtained by other methods.

[0053] Exemplarily, the surface of the scalp three-dimensional model is meshed, and then the vertex or edge closest to the gray matter target point M is searched on the mesh. Specifically, it includes:

[0054] The surface of the scalp 3D model is meshed to obtain a series of vertices and top edges. All vertices on the mesh are traversed to calculate their distances from the gray matter target M. For each edge on the mesh, the point closest to the gray matter target M can be found by linear interpolation. The vertex or interpolation point on the edge closest to the gray matter target M is determined as the first closest point.

[0055] Step S202: acquiring multiple search points around the first closest point in the scalp layer, wherein the distance between each search point and the closest point is less than or equal to a preset distance.

[0056] In a possible implementation, step S202, in the scalp layer, obtains multiple search points around the first closest point, including: setting a search range and a search step according to the coordinates of the first closest point to obtain multiple search points in the scalp layer.

[0057] In a possible implementation, the search range and the search step are set according to the coordinates of the first closest point to obtain multiple search points in the scalp layer, including:

[0058] According to the search range and the search step length, the search steps and the search coordinates are set in the three-dimensional coordinates; the second closest point position of each search coordinate in the scalp layer is obtained, and the second closest point position is determined as the search point.

[0059] For example, the search range is L, the search step is S, and the coordinates of the first closest point N are (x N ,y N ,z N ), let the coordinates of point H0 be (x N -L,y N -L,z N -L). According to the search range and search step length, the number of search steps K = 2L / S, so the coordinates of the new point H i is (x N -L+n x S,y N -L+n y S,z N -L+n z S), where n x 、n y 、n z is an integer in the range [0, K]. Use the FindClosestPoint algorithm in VTK to find H i The closest point on the 3D scalp model is the search point P. i , and finally get multiple search points

[0060] Step S203: performing spherical fitting on each search point in the scalp layer to obtain a normal vector line of each search point.

[0061] In a possible implementation, step S203, performing spherical fitting on each search point in the scalp layer to obtain a normal vector line for each search point, including: taking each search point as the center, obtaining multiple vertices within a preset range in the scalp layer; performing spherical fitting based on a point cloud composed of multiple vertices, and obtaining a sphere center point obtained after spherical fitting; and obtaining a normal vector line for each search point based on each search point and the corresponding sphere center point.

[0062] Specifically, in the present invention, for each search point, on the scalp layer, the coordinates of multiple vertices within a preset range are obtained. In order to make the fitting result of the spherical fitting closest to the actual scalp situation, the number of vertex coordinates obtained should be as many as possible when the preset range is fixed. In the embodiment of the present invention, the size of the preset range is 10-15mm. .

[0063] For example, the search point P i The FindPointsWithinRadius algorithm in VTK is used to obtain all vertices within the radius of the scalp 3D model to obtain the point cloud G. i ; For point cloud G i Perform spherical fitting to obtain the sphere center C i , since the line connecting a point on the sphere and the center of the sphere is perpendicular to the tangent plane of the sphere where the point is located, then P i C i The line and point P i The normal vectors of the points on the scalp are collinear, and then the normal vector line of each search point is obtained.

[0064] Step S204, determining a mapping point from the gray matter target point to the scalp layer from a plurality of search points according to the straight-line distance between the gray matter target point and each normal vector straight line.

[0065] For example, Figure 3 As shown, the calculation point M and the normal vector line P i C i The distance d i ;d i The smaller it is, the closer point M is to point P. i The normal vector of the point, after the search is completed, d i The smallest search point is the required mapping point from the gray matter target to the scalp.

[0066] Exemplarily, 10 target points are taken on the gray matter, and the gray matter target point to scalp mapping method of the present invention is used to find the target point mapped to the scalp. The search range L = 5 mm and the search step S = 0.5 mm are set. The distance between the point normal vector of the scalp target point and the gray matter target point is calculated as the mapping error. The method of directly finding the nearest point on the scalp as the mapping point is compared. The results are shown in Table 1.

[0067] Table 1

[0068]

[0069]

[0070] It can be seen from Table 1 that, by comparing the mapping errors of the conventional method and the method of the present invention, the optimization method of the present invention can effectively reduce the mapping error.

[0071] By adopting the above method, the present invention can achieve at least one of the following beneficial effects:

[0072] 1. The scalp medical image is processed to obtain a 3D model of the scalp, and then the nearest point of the gray matter target is found on the scalp. Based on the nearest point, a step search is performed while calculating the fitting spherical normal vector of the search point, and the distance between the straight line where the fitting spherical normal vector is located and the gray matter target point is calculated. The search point corresponding to the minimum distance finally obtained is the target point mapped from the gray matter target point to the scalp. The mapping error from the gray matter target point to the scalp target point is reduced, making the TMS coil positioning more accurate and ensuring the therapeutic effect of transcranial magnetic stimulation.

[0073] 2. The scalp surface is full of interlaced grooves, overlapping folds and complex shapes. The triangular mesh model can adapt to this complex curved surface shape well due to its simple topological relationship, ensuring high precision and accuracy of the scalp three-dimensional model. At the same time, the triangular mesh model is easy to divide and refine the mesh, and the density of the mesh can be adjusted as needed to meet the modeling needs of different precisions.

[0074] The gray matter target point to scalp mapping device provided by the present invention is described below. The gray matter target point to scalp mapping device described below and the gray matter target point to scalp mapping method described above can be referred to each other.

[0075] like Figure 4 As shown, the present invention also provides a mapping device from a gray matter target point to a scalp, comprising:

[0076] The first point acquisition unit 410 is used to perform three-dimensional reconstruction on the medical image of the scalp to obtain a three-dimensional scalp model; and obtain the first closest point of the gray matter target point in the scalp layer of the three-dimensional scalp model, where the gray matter target point is a preset target point on the gray matter in the medical image;

[0077] The second point acquisition unit 420 acquires a plurality of search points around the first closest point in the scalp layer, wherein the distance between each search point and the closest point is less than or equal to a preset distance;

[0078] A spherical fitting unit 430 performs spherical fitting on each search point in the scalp layer to obtain a normal vector line of each search point;

[0079] The mapping point acquisition unit 440 is used to determine the mapping point from the gray matter target point to the scalp layer from the multiple search points according to the straight-line distance between the gray matter target point and each normal vector straight line.

[0080] In a possible implementation, the spherical fitting unit 430 is specifically used to obtain multiple vertices within a preset range in the scalp layer with each search point as the center; perform spherical fitting based on the point cloud composed of the multiple vertices to obtain the center point of the sphere obtained after the spherical fitting; and obtain the normal vector straight line of each search point based on each search point and the corresponding center point of the sphere.

[0081] In a possible implementation, the second point acquisition unit 420 is configured to set a search range and a search step according to the coordinates of the first closest point, so as to obtain a plurality of search points in the scalp layer.

[0082] In a possible implementation, the second point acquisition unit 420 is specifically used to set the search steps and search coordinates in three-dimensional coordinates according to the search range and the search step length; obtain the second closest point of each search coordinate in the scalp layer, and determine the second closest point as the search point.

[0083] In a possible implementation, the first point acquisition unit 410 is specifically configured to segment the medical image to obtain a medical image of the scalp; and to perform three-dimensional reconstruction of the medical image of the scalp using a Marching Cubes algorithm to obtain a three-dimensional model of the scalp.

[0084] Figure 5 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 5 As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute a method for mapping a gray matter target point to a scalp, the method comprising:

[0085] Performing three-dimensional reconstruction on the medical image of the scalp to obtain a three-dimensional scalp model; and obtaining the first closest point of the gray matter target in the scalp layer of the three-dimensional scalp model, where the gray matter target is a preset target on the gray matter in the medical image;

[0086] In the scalp layer, a plurality of search points around the first closest point are obtained, wherein the distance between each search point and the closest point is less than or equal to a preset distance;

[0087] Perform spherical fitting on each search point in the scalp layer to obtain a normal vector line of each search point;

[0088] According to the straight-line distance between the gray matter target point and each normal vector straight line, a mapping point from the gray matter target point to the scalp layer is determined from multiple search points.

[0089] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0090] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program can be stored on a non-transitory computer-readable storage medium, when the computer program is executed by a processor, the computer can execute a gray matter target point to scalp mapping method provided by the above methods, the method comprising:

[0091] Performing three-dimensional reconstruction on the medical image of the scalp to obtain a three-dimensional scalp model; and obtaining the first closest point of the gray matter target in the scalp layer of the three-dimensional scalp model, where the gray matter target is a preset target on the gray matter in the medical image;

[0092] In the scalp layer, a plurality of search points around the first closest point are obtained, wherein the distance between each search point and the closest point is less than or equal to a preset distance;

[0093] Perform spherical fitting on each search point in the scalp layer to obtain a normal vector line of each search point;

[0094] According to the straight-line distance between the gray matter target point and each normal vector straight line, a mapping point from the gray matter target point to the scalp layer is determined from multiple search points.

[0095] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to perform a method for mapping a gray matter target point to a scalp provided by the above methods, the method comprising:

[0096] Performing three-dimensional reconstruction on the medical image of the scalp to obtain a three-dimensional scalp model; and obtaining the first closest point of the gray matter target in the scalp layer of the three-dimensional scalp model, where the gray matter target is a preset target on the gray matter in the medical image;

[0097] In the scalp layer, a plurality of search points around the first closest point are obtained, wherein the distance between each search point and the closest point is less than or equal to a preset distance;

[0098] Perform spherical fitting on each search point in the scalp layer to obtain a normal vector line of each search point;

[0099] According to the straight-line distance between the gray matter target point and each normal vector straight line, a mapping point from the gray matter target point to the scalp layer is determined from multiple search points.

[0100] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0101] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these 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 invention.

Claims

1. A method for mapping gray matter targets to scalp, characterized in that: include: Perform three-dimensional reconstruction on the medical image of the scalp to obtain a three-dimensional scalp model; and obtaining a first closest point of a gray matter target point in the scalp layer of the scalp three-dimensional model, wherein the gray matter target point is a preset target point on the gray matter in the medical image; In the scalp layer, a plurality of search points around the first closest point are obtained, and the distance between each search point and the closest point is less than or equal to a preset distance; Performing spherical fitting on each search point in the scalp layer to obtain a normal vector straight line of each search point; According to the straight-line distance between the gray matter target point and each normal vector straight line, a mapping point from the gray matter target point to the scalp layer is determined from a plurality of search points.

2. The method for mapping gray matter target points to scalp according to claim 1, characterized in that: The step of performing spherical fitting on each search point in the scalp layer to obtain a normal vector straight line of each search point includes: Taking each search point as the center, obtaining a plurality of vertices within a preset range in the scalp layer; Perform spherical fitting according to the point cloud composed of multiple vertices, and obtain the spherical center point obtained after the spherical fitting; According to each search point and the corresponding sphere center point, the normal vector line of each search point is obtained.

3. The method for mapping gray matter target points to scalp according to claim 1, characterized in that: The step of acquiring a plurality of search points around the first closest point in the scalp layer includes: A search range and a search step are set according to the coordinates of the first closest point to obtain a plurality of search points in the scalp layer.

4. The method for mapping gray matter target points to scalp according to claim 3, characterized in that: The step of setting a search range and a search step according to the coordinates of the first closest point to obtain a plurality of search points in the scalp layer includes: According to the search range and the search step length, setting the search step number and the search coordinates in three-dimensional coordinates; The second closest point position of each search coordinate in the scalp layer is obtained, and the second closest point position is determined as the search point.

5. The method according to claim 1, characterized in that The three-dimensional reconstruction of the medical image of the scalp to obtain a three-dimensional scalp model includes: Segment the medical image to obtain the medical image of the scalp; The Marching Cubes algorithm is used to perform three-dimensional reconstruction of the medical images of the scalp to obtain a three-dimensional scalp model.

6. The method for mapping gray matter target points to scalp according to any one of claims 1 to 5, characterized in that: The scalp three-dimensional model is a triangular mesh model.

7. A mapping device for gray matter target points to scalp, characterized in that: include: The first point acquisition unit is used to perform three-dimensional reconstruction on the medical image of the scalp to obtain a three-dimensional model of the scalp; and obtaining a first closest point of a gray matter target point in the scalp layer of the scalp three-dimensional model, wherein the gray matter target point is a preset target point on the gray matter in the medical image; A second point acquisition unit, in the scalp layer, acquires a plurality of search points around the first closest point, wherein the distance between each search point and the closest point is less than or equal to a preset distance; A spherical fitting unit, performing spherical fitting on each search point in the scalp layer to obtain a normal vector straight line of each search point; A mapping point acquisition unit is used to determine a mapping point from the gray matter target point to the scalp layer from a plurality of search points according to a straight-line distance between the gray matter target point and each normal vector straight line.

8. An electronic 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 program, the method for mapping the gray matter target point to the scalp as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for mapping gray matter target points to scalp according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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