Method for determining model axis and electronic equipment

Abstract

The invention discloses a method for determining a model axis and electronic equipment. The method comprises the following steps: acquiring a first model; calculating a first calculation point based on the coordinates of all vertexes of the first model; generating a connecting line between each vertex of the first model and the first calculation point to obtain a plurality of connecting lines; selecting target vertexes on the inner layer surface of the first model based on all intersection points of each connecting line and the first model to obtain a plurality of target vertexes; and determining an axis of the first model based on all the target vertexes. The method comprises the following steps: selecting a plurality of target vertexes on the inner layer surface of a first model based on all intersection points of each connecting line and the first model; and the axis of the first model is determined based on all the target vertexes, so that compared with a mode of determining the axis of the first model based on a directed bounding box, the interference of a local structure of an outer layer surface on the determined axis can be effectively avoided, and the situation that the axis is judged wrongly when the width of the first model is greater than the length of the first model can be avoided; and the axis accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the field of medical technologies, and particularly relates to a method for determining the axis of a model and an electronic device. Background Art

[0002] With the wide application of digital technologies in the field of oral implantology, navigated implant surgery has become an important technical means to improve the implant accuracy. After performing navigated implant surgery, it is often necessary to determine the actual implantation pose of the oral implant to evaluate the surgical outcome. To determine the actual implantation pose of the oral implant, generally, it is necessary to first obtain the oral implant model, then determine the axis of the oral implant model, and then perform further calculations based on the axis.

[0003] Currently, the mainstream method for determining the axis of an oral implant model relies on the oriented bounding box algorithm. For an oral implant model with a regular cylindrical shape and a prominent major axis, the oriented bounding box algorithm can effectively determine the axis in the major axis direction by calculating the spatial distribution of the model vertices.

[0004] However, in clinical applications, the outer surface of some oral implants is designed with deep threads, grooves or asymmetric structures, and such features will significantly change the vertex distribution characteristics of the model. When calculating the axis of this kind of oral implant model using the oriented bounding box algorithm, it is vulnerable to interference from local geometric mutations such as threads. Especially when the width of the oral implant model exceeds its length due to thread expansion, the oriented bounding box algorithm may misidentify the axis in the thread expansion direction (at this time, the thread expansion direction is the major axis direction) as the axis of the model, and thus obtain an incorrect axis. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present application provides a method for determining the axis of a model and an electronic device. By selecting target vertices on the inner surface of the first model based on all the intersection points of each connection line with the first model, a plurality of target vertices are obtained; and based on all the target vertices, the axis of the first model is determined. Compared with the method of determining its axis based on the oriented bounding box of the first model, it can effectively avoid the interference of local structures such as threads on the outer surface to the determination of the axis, and further avoid the situation of misjudging the axis when the width of the first model is greater than the length of the first model, thereby improving the accuracy of the axis.

[0006] To solve the above problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present application provides a method for determining the axis of a model, including: obtaining a first model, where the first model is an oral implant model and is a mesh model composed of a plurality of vertices, and the surface of the first model includes an inner surface, and the inner surface is used to represent the surface where the oral implant is in direct contact with the abutment;

[0008] Calculate a first calculation point based on the coordinates of all vertices of the first model;

[0009] Generate a connection line between each vertex of the first model and the first calculation point to obtain multiple connection lines;

[0010] Select target vertices on the inner surface of the first model based on all intersection points of each connection line and the first model to obtain multiple target vertices;

[0011] Determine the axis of the first model based on all the target vertices.

[0012] In some embodiments, the step of selecting target vertices on the inner surface of the first model based on all intersection points of each connection line and the first model to obtain multiple target vertices includes:

[0013] For each connection line, determine all intersection points of the connection line and the first model;

[0014] Based on all intersection points of the connection line and the first model, determine whether the vertex on the connection line is located on the inner surface of the first model;

[0015] When it is determined that the vertex on the connection line is located on the inner surface of the first model, determine the vertex on the connection line as the target vertex, and thus obtain multiple target vertices.

[0016] In some embodiments, the step of determining whether the vertex on the connection line is located on the inner surface of the first model based on all intersection points of the connection line and the first model for each connection line includes:

[0017] For each connection line, determine whether there is a distance between two intersection points greater than a first preset value among all intersection points of the connection line and the first model;

[0018] When there is a distance between two intersection points greater than the first preset value among all intersection points of the connection line and the first model, determine that the vertex on the connection line is not located on the inner surface, otherwise determine that the vertex on the connection line is located on the inner surface.

[0019] In some embodiments, the step of determining whether there is a distance between two intersection points greater than a first preset value among all intersection points of the connection line and the first model for each connection line includes:

[0020] For each connection line, use the vertex on the connection line as the first intersection point of the connection line and the first model;

[0021] Calculate the first distance between the first intersection point and each other intersection point on the connection line to obtain a plurality of the first distances;

[0022] When at least one of the first distances is greater than the first preset value, it is determined that among all the intersection points of the connection line and the first model, the distance between two intersection points is greater than the first preset value.

[0023] In some embodiments, for each connection line, determining whether the vertex on the connection line is located on the inner surface of the first model based on all the intersection points of the connection line and the first model includes:

[0024] For each connection line, when the number of all the intersection points of the connection line and the first model is one, it is determined that the vertex on the connection line is located on the inner surface, otherwise it is determined that the vertex on the connection line is not located on the inner surface.

[0025] In some embodiments, determining the axis of the first model based on all the target vertices includes:

[0026] Calculate the average coordinate point of all the target vertices and use it as the second calculation point;

[0027] Calculate the covariance matrix based on the coordinates of all the target vertices;

[0028] Calculate all the eigenvalues of the covariance matrix and the eigenvector corresponding to each eigenvalue;

[0029] Select the eigenvector corresponding to the largest eigenvalue of the covariance matrix as the axis direction vector of the first model;

[0030] Generate a straight line passing through the second calculation point and parallel to the axis direction vector and determine it as the axis of the first model.

[0031] In some embodiments, the method further includes:

[0032] Perform a hole filling process on the first model to obtain the first planar region of the first model;

[0033] Determine the intersection point of the axis of the first model and the first planar region as the implantation point;

[0034] Determine the intersection point where the axis of the first model intersects the outer surface of the first model as the root apex point, and the outer surface is the surface of the first model other than the inner surface.

[0035] In some embodiments, the first model is an oral implant model obtained based on the postoperative oral medical image model of the target object, and the method further includes:

[0036] Obtain a second model, where the second model is an oral implant model obtained based on a preoperative planned oral medical image model of a target object;

[0037] Determine the apical point and the implantation point of the second model;

[0038] Calculate a plurality of implantation accuracy indicators based on the coordinates of the apical point and the implantation point of the first model, and the coordinates of the apical point and the implantation point of the second model.

[0039] In some embodiments, the method further includes:

[0040] Register the preoperative planned oral medical image model of the target object with the postoperative oral medical image model to move the first model to a position close to the second model;

[0041] Generate a first bounding space unit that encloses the second model;

[0042] Determine all pixel points within the first bounding space unit and having pixel values greater than a preset pixel value in the postoperative oral medical image model as a target pixel point set;

[0043] Perform three-dimensional reconstruction based on the target pixel point set and extract connected regions to obtain at least one candidate model;

[0044] Generate a third bounding unit that encloses each of the candidate models to obtain at least one of the third bounding units;

[0045] Determine the candidate model in the third bounding unit with the smallest size difference from a preset bounding unit among all the third bounding units as the first model.

[0046] In a second aspect, an embodiment of the present application provides an electronic device, where the electronic device includes:

[0047] At least one processor; and,

[0048] A memory communicatively connected to the at least one processor; wherein,

[0049] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for determining the model axis as described in the first aspect.

[0050] The present application provides a method for determining the axis of a model and an electronic device. By selecting target vertices on the inner surface of the first model based on all the intersection points of each connection line with the first model, multiple target vertices are obtained; and based on all the target vertices, the axis of the first model is determined. Compared with the method of determining its axis based on the oriented bounding box of the first model, it can effectively avoid the interference of local structures such as threads on the outer surface on determining the axis, and thus can avoid the situation of misjudging the axis when the width of the first model is greater than the length of the first model, improving the accuracy of the axis. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 FIG. is a schematic flowchart of the first implementation manner of the method for determining the axis of a model provided by an embodiment of the present application.

[0052] Figure 2 FIG. is a schematic diagram of the first model provided by an embodiment of the present application.

[0053] Figure 3 is Figure 1 a detailed flowchart of step S400 in

[0054] Figure 4A FIG. is a schematic diagram in which the vertex on the connection line is not located on the inner surface.

[0055] Figure 4B FIG. is a schematic diagram in which the vertex on the connection line is located on the inner surface.

[0056] Figure 5A FIG. is a schematic diagram in which the target vertices and the connection lines are displayed simultaneously provided by an embodiment of the present application.

[0057] Figure 5B FIG. is a schematic diagram of all the target vertices provided by an embodiment of the present application.

[0058] Figure 6 FIG. is a schematic diagram of the axis of the first model provided by an embodiment of the present application.

[0059] Figure 7 FIG. is a schematic flowchart of the second implementation manner of the method for determining the axis of a model provided by an embodiment of the present application.

[0060] Figure 8 FIG. is a schematic diagram of the first model after hole filling processing provided by an embodiment of the present application.

[0061] Figure 9 FIG. is a schematic flowchart of the third implementation manner of the method for determining the axis of a model provided by an embodiment of the present application.

[0062] Figure 10 FIG. is a schematic diagram in which the first model and the second model are displayed simultaneously provided by an embodiment of the present application.

[0063] Figure 11 It is a schematic structural diagram of a device for determining the axis of a model provided by an embodiment of the present application.

[0064] Figure 12 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0065] Figure 13 It is a structural block diagram of a computer-readable storage medium provided by an embodiment of the present application. Detailed implementation manners

[0066] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0067] In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality of" means two or more, unless otherwise specifically defined.

[0068] The present application provides a method and an electronic device for determining the axis of a model. By selecting target vertices on the inner surface of the first model based on all the intersection points of each connection line with the first model, a plurality of target vertices are obtained; and based on all the target vertices, the axis of the first model is determined. Compared with the method of determining its axis based on the oriented bounding box of the first model, it can effectively avoid the interference of local structures such as threads on the outer surface on determining the axis, and further can avoid the situation of misjudging the axis when the width of the first model is greater than the length of the first model, improving the accuracy of the axis. And without generating the oriented bounding box of the first model, the speed of determining the axis is also accelerated.

[0069] Next, the method for determining the axis of a model provided by the present application will be specifically described in conjunction with the accompanying drawings.

[0070] Please refer to Figure 1 , Figure 1 It is a schematic flowchart of the first implementation manner of the method for determining the axis of a model provided by an embodiment of the present application. As Figure 1 shown, the method for determining the axis of a model includes: step S100 to step S500.

[0071] Step S100: Obtain the first model.

[0072] Among them, the first model is an oral implant model and is a mesh model composed of multiple vertices. The oral implant model is a three-dimensional model of an oral implant. An oral implant is an artificial tooth root made of artificial materials (such as titanium metal or ceramics, etc.), which is implanted into the jawbone of the toothless area of the target object through a dental implantation surgery and undergoes osseointegration with the surrounding bone tissue. Then, the oral implant serves as a stable foundation and is connected to a dental prosthesis (such as a dental crown, fixed bridge, or removable denture, etc.) through an abutment, thereby jointly realizing the function of repairing missing teeth.

[0073] Please refer to Figure 2 , Figure 2 which is a schematic diagram of the first model provided by the embodiment of the present application. As Figure 2 shown, the surface of the first model 1 includes an inner surface A, and the inner surface A is used to represent the surface where the oral implant is in direct contact with the abutment. The surface of the first model 1 further includes an outer surface B, and the outer surface B is the surface other than the inner surface A. As Figure 2 shown, a thread structure is formed on the outer surface B.

[0074] In some embodiments, the first model is an oral implant model obtained based on the postoperative oral medical image model of the target object.

[0075] Optionally, the medical image model is a CBCT (Cone Beam Computed Tomography) image model, and the CBCT image model is a three-dimensional image model generated by cone beam X-ray scanning and combined with computer reconstruction technology. The postoperative oral medical image model of the target object is a medical image model obtained by scanning the oral part of the target object after the target object has undergone a dental implantation surgery.

[0076] Step S200: Calculate a first calculation point based on the coordinates of all vertices of the first model.

[0077] In some embodiments, the first calculation point is the centroid of the first model, and the average coordinates of the coordinates of all vertices of the first model are calculated and used as the coordinates of the first calculation point.

[0078] In some embodiments, the first calculation point can also be the geometric center point of the first model, or a pre-specified point.

[0079] In some embodiments, a mesh data toolkit is used to model and process all models in this method.

[0080] Optionally, the mesh data toolkit includes VTK (Visualization Toolkit), Meshmixer, CloudCompare, ParaView, MeshLab, etc.

[0081] Optionally, when using the VTK toolkit, the surface mesh data type of all models is vtkPolyData.

[0082] In some embodiments, when using the VTK toolkit, the vtkCenterOfMass function therein can be called to calculate the first calculation point based on the coordinates of all vertices of the first model.

[0083] Step S300: Generate the connection lines between each vertex of the first model and the first calculation point to obtain multiple connection lines.

[0084] Step S400: Select target vertices on the inner surface of the first model based on all intersection points of each connection line with the first model to obtain multiple target vertices.

[0085] Please refer to Figure 3 , Figure 3 is Figure 1 the detailed flowchart of step S400 in Figure 3 As shown in

[0086] Step S410: For each connection line, determine all intersection points of the connection line with the first model.

[0087] In some embodiments, when using the VTK toolkit, construct an oriented bounding box tree (vtkOBBTree) of the first model, and then call the IntersectWithLine function in the vtkOBBTree class. The IntersectWithLine function will establish a straight line based on the two input points (the currently traversed vertex and the first calculation point), and return the coordinates of all intersection points of the straight line with the surface of the first model.

[0088] In some embodiments, after establishing a straight line based on the currently traversed vertex and the first calculation point, a line segment connecting the currently traversed vertex and the first calculation point can be obtained based on the straight line, and the coordinates of all intersection points on the line segment can be determined based on the coordinates of all intersection points of the straight line with the surface of the first model.

[0089] Step S420: Determine whether the vertices on the connection line are located on the inner surface of the first model based on all intersection points of the connection line with the first model.

[0090] In some embodiments, step S420 includes steps S421 to S422.

[0091] Step S421: For each connection line, determine whether there is a distance greater than a first preset value between two intersection points among all intersection points of the connection line with the first model.

[0092] Optionally, the first preset value is a value not less than 0.

[0093] Preferably, the first preset value is a value greater than 0 and close to 0. For example, the first preset value is 0.01 mm (millimeter) or 0.1 mm, etc. In this way, the algorithm can be made compatible with cases where there are some calculation errors.

[0094] In some embodiments, step S421 includes steps (421.1) to (421.3).

[0095] (421.1) For each connection line, use the vertex on the connection line as the first intersection point of the connection line and the first model.

[0096] (421.2) Calculate the first distance between the first intersection point and each other intersection point on the connection line to obtain a plurality of first distances.

[0097] (421.3) When at least one first distance is greater than the first preset value, determine that among all the intersection points of the connection line and the first model, the distance between two intersection points is greater than the first preset value.

[0098] Step S422: When among all the intersection points of the connection line and the first model, the distance between two intersection points is greater than the first preset value, determine that the vertex on the connection line is not located on the inner surface; otherwise, determine that the vertex on the connection line is located on the inner surface.

[0099] Please refer to Figure 4A and Figure 4B , Figure 4A is a schematic diagram where the vertex on the connection line is not located on the inner surface, Figure 4B is a schematic diagram where the vertex on the connection line is located on the inner surface. As Figure 4A and Figure 4B shown, the cross-sectional profile of the first model includes the inner surface cross-sectional profile A1 and the outer surface cross-sectional profile B1. The cross-sectional profile within the region P is the inner surface cross-sectional profile A1.

[0100] As Figure 4A shown, in some embodiments, the connection line L1 between the vertex C and the first calculation point O and all the intersection points of the first model include the vertex C (i.e., the first intersection point) and the intersection point D (i.e., the second intersection point). At this time, the calculated distance between the vertex C and the intersection point D is greater than the first preset value, and the vertex C is not located on the inner surface but on the outer surface.

[0101] As Figure 4BAs shown, in some embodiments, the connection line L2 between vertex E and the first calculation point O and all intersections of the first model include vertex E (i.e., the first intersection point). At this time, there is only 1 intersection point between the connection line L2 and the first model, and there is no distance between two intersection points greater than the first preset value, and vertex E is located on the inner surface.

[0102] In some embodiments, step S400 includes: for each connection line, when the number of all intersection points of the connection line and the first model is one, it is determined that the vertex on the connection line is located on the inner surface, otherwise it is determined that the vertex on the connection line is not located on the inner surface.

[0103] As Figure 4A shown, in some embodiments, when the number of all intersection points of the connection line L1 and the first model is not one, the vertex C on the connection line L1 is not located on the inner surface. As Figure 4B shown, in some embodiments, when the number of all intersection points of the connection line L2 and the first model is one, the vertex E on the connection line L2 is located on the inner surface.

[0104] Step S430: When it is determined that the vertex on the connection line is located on the inner surface of the first model, the vertex on the connection line is determined as the target vertex, and then multiple target vertices are obtained.

[0105] Please refer to Figure 5A , Figure 5A which is a schematic diagram showing the simultaneous display of the target vertices and the connection lines provided by the embodiments of the present application. As Figure 5A shown, in some embodiments, there are multiple connection lines L, and a target vertex F is located on one connection line L.

[0106] In some embodiments, after obtaining multiple target vertices, the coordinates of all target vertices are stored and all connection lines are deleted.

[0107] Please refer to Figure 5B , Figure 5B which is a schematic diagram of all target vertices provided by the embodiments of the present application. As Figure 5B shown, in some embodiments, all target vertices F are located on the inner surface A of the first model 1.

[0108] Step S500: Determine the axis of the first model based on all target vertices.

[0109] As Figure 4A and Figure 4BAs shown, the cross-sectional profile A1 of the inner surface is approximately axisymmetric, while the cross-sectional profile B1 of the outer surface has a thread structure and is clearly not axisymmetric. And, as described above, the inner surface A is used to represent the surface where the oral implant is in direct contact with the abutment. Therefore, by determining the axis of the first model based on all the target vertices on the inner surface, the interference of local structures such as the threads on the outer surface to the determination of the axis can be effectively avoided, and further, the situation of misjudging the axis when the width of the first model is greater than the length of the first model can be avoided, improving the accuracy of the axis. Also, it can make the determined axis as close as possible to the straight line where the movement direction vector of the abutment is located when the abutment is inserted into the oral implant in reality, facilitating the subsequent further determination of the implantation point and the apical point.

[0110] In some embodiments, the least squares method is used to determine the axis of the first model based on all the target vertices. In this way, compared with the method of determining the axis by rotating the first model in the oriented bounding box algorithm, without calculating the rotation matrix, the axis of the first model can be directly determined according to the target vertices, reducing the calculation error; compared with the method of determining the axis using the PCA (Principal Component Analysis) algorithm, the accuracy of calculating for small-scale data can be improved.

[0111] In some embodiments, when using the least squares method to determine the axis of the first model based on all the target vertices, step S500 includes steps S510 to S550.

[0112] Step S510: Calculate the average coordinate point of all the target vertices and use it as the second calculation point.

[0113] Step S520: Calculate the covariance matrix based on the coordinates of all the target vertices.

[0114] In some embodiments, calculate the average coordinate value of the coordinates of all the target vertices on each coordinate axis, and then calculate the covariance matrix based on the coordinates of each target vertex and the average coordinate value on each coordinate axis.

[0115] Step S530: Calculate all the eigenvalues of the covariance matrix and the eigenvector corresponding to each eigenvalue.

[0116] Step S540: Select the eigenvector corresponding to the largest eigenvalue of the covariance matrix as the axis direction vector of the first model.

[0117] Step S550: Generate a straight line passing through the second calculation point and parallel to the axis direction vector and determine it as the axis of the first model.

[0118] In some embodiments, the PCA algorithm can also be used to determine the axis of the first model based on all the target vertices.

[0119] Please refer to Figure 6 , Figure 6 which is a schematic diagram of the axis of the first model provided by an embodiment of the present application. As Figure 6 shown, the axis Z of the first model 1 is very close to the geometric center line of the first model 1, indicating that the axis Z is very accurate.

[0120] Please refer to Figure 7 , Figure 7 which is a schematic flowchart of the second implementation manner of the method for determining the axis of the model provided by an embodiment of the present application. As Figure 7 shown, the method for determining the axis of the model includes steps S100 to step S600.

[0121] The content of steps S100 to S500 refers to the above description.

[0122] Step S600: Determine the root apex point and the implantation point of the first model based on the axis of the first model.

[0123] In some embodiments, step S600 includes steps S610 to S630.

[0124] Step S610: Perform hole filling on the first model to obtain the first planar region of the first model.

[0125] As Figure 2 and Figure 4A shown, in some embodiments, an inner surface of the first model 1 forms a space for accommodating a part of the abutment. Therefore, it can be considered that there is a hole in the middle of the first model 1 for accommodating a part of the abutment, and the bottom of the first model 1 is empty.

[0126] As described above, the first model is a mesh model composed of multiple vertices. In the mesh model, multiple vertices form a face, multiple faces form the mesh model, and each face has a normal vector and multiple edges. Since the normal vectors of some types of oral implant models in the part between the inner surface and the outer surface at the edge of the hole will have a large difference from the normal vector of the edge, in order to avoid the situation of failed hole filling, it is necessary to preprocess the first model before hole filling to make the inner surface and the outer surface transition smoothly.

[0127] In some embodiments, when using the VTK toolkit, the FlipNormalsOn function in the vtkPolyDataNormals algorithm is used to reverse the normal vectors of the first model, and then the SplittingOn function is used to split the normal vectors of sharp edges. A sharp edge refers to an edge where the angle between two adjacent patches in the mesh exceeds a certain threshold (default is 30°). At the sharp edge, the vtkPolyDataNormals algorithm generates independent normal vectors for each adjacent patch instead of sharing the same normal vector. In this way, the rendering effect at the sharp edge can be made sharper, facilitating subsequent hole filling processing for the first model.

[0128] Next, the vtkFillHolesFilter algorithm is used to perform hole filling processing on the first model. Specifically, all the edges in the first model are traversed to identify the boundary edges (i.e., the edges shared by one patch), and then all the boundary edges are connected to form a closed boundary loop. Finally, polygon patches are generated within the boundary loop to fill the holes.

[0129] Please refer to Figure 8 , Figure 8 is a schematic diagram of the first model after hole filling processing provided by the embodiments of the present application. As Figure 8 shown, hole filling processing is performed on the first model 1 to obtain the first planar region G. At this time, the axis of the first model 1 will definitely have an intersection point with the first planar region G. And, as Figure 2 and Figure 8 shown, after the sharp edge normal vector splitting processing, the rendering effect of the first model 1 at the sharp edge is sharper.

[0130] Step S620: Determine the intersection point of the axis of the first model and the first planar region as the implantation point.

[0131] Step S630: Determine the intersection point where the axis of the first model intersects the outer surface of the first model as the apical point.

[0132] In some embodiments, after obtaining the coordinates of the implantation point and the apical point, the first planar region can be deleted.

[0133] As Figure 6 shown, the intersection point of the axis Z of the first model 1 and the first planar region is determined as the implantation point N1, and the intersection point where the axis Z intersects the outer surface B is determined as the apical point N2. The direction vector pointing from the implantation point N1 to the apical point N2 is approximately the movement direction vector of the abutment when embedding the oral implant in reality.

[0134] By the method of patching the first model and then determining the root apex point and the implantation point of the first model as described above, compared with the method using the oriented bounding box algorithm, it is not necessary to move the first model when calculating the root apex point and the implantation point, and the root apex point and the implantation point of the first model can be determined at any time, improving the flexibility of the method; compared with the method of calculating the transformation matrix before and after the first model is rotated to the correct orientation by using the axis-angle method and then determining the root apex point and the implantation point, there is no need to calculate the transformation matrix, reducing the calculation error.

[0135] As described above, in some embodiments, the first model is an oral implant model obtained based on the postoperative oral medical image model of the target object.

[0136] In some embodiments, after the navigated dental implant surgery, it is necessary to evaluate the surgical result according to the first model and the second model obtained based on the preoperative planned oral medical image model of the target object. The preoperative planned oral medical image model of the target object is a medical image model obtained by scanning the oral part of the target object before the dental implant surgery to obtain an initial medical image model, and the positions of the oral implants are planned on the initial medical image model.

[0137] Please refer to Figure 9 , Figure 9 which is a schematic flowchart of the 3rd embodiment of the method for determining the model axis provided by the embodiment of the present application. As Figure 9 shown, the method for determining the model axis includes steps S100 to step S900.

[0138] The content of steps S100 to S600 refers to the above description.

[0139] Step S700: Obtain the second model.

[0140] Among them, the second model is an oral implant model obtained based on the preoperative planned oral medical image model of the target object. The second model is a mesh model composed of multiple vertices.

[0141] Step S800: Determine the root apex point and the implantation point of the second model.

[0142] The method for determining the root apex point and the implantation point of the second model refers to the method for determining the root apex point and the implantation point of the first model in steps S100 to S600.

[0143] Step S900: Calculate a plurality of implantation accuracy indicators based on the coordinates of the root apex point and the implantation point of the first model and the coordinates of the root apex point and the implantation point of the second model.

[0144] In some embodiments, the coordinates of the root apex point and the implantation point of the first model are multiplied by the registration matrix of the image model to obtain the updated coordinates of the root apex point and the implantation point of the first model for subsequent calculations. The registration matrix of the image model is used to register the postoperative planning oral medical image model of the target object with the preoperative oral medical image model.

[0145] Please refer to Figure 10 , Figure 10 which is a schematic diagram showing the simultaneous display of the first model and the second model provided by the embodiments of the present application. As Figure 10 shown, at this time, the coordinates of the root apex point and the implantation point of the updated first model have been determined. Without considering calculation errors, Figure 10 the relative positional relationship between the first model 1 and the second model 2 in

[0146] is the relative positional relationship between the preoperatively planned oral implant and the actually implanted oral implant of the target object.

[0147] In some embodiments, the multiple implantation accuracy indicators include total implantation point error, implantation point depth error, implantation point lateral error, total root apex point error, root apex point depth error, root apex point lateral error, and angular error, etc.

[0148]

[0149] where d 1 represents the total implantation point error, x N3 represents the X-axis coordinate value of implantation point N3, x N1 represents the X-axis coordinate value of implantation point N1, y N3 represents the Y-axis coordinate value of implantation point N3, y N1 represents the Y-axis coordinate value of implantation point N1, z N3 represents the Z-axis coordinate value of implantation point N3, z N1 represents the Z-axis coordinate value of implantation point N1.

[0150] In some embodiments, the formula for calculating the implantation point depth error is:

[0151]

[0152] where v 1 represents the implantation point depth error, represents the direction vector from implantation point N3 to implantation point N1, represents the direction vector from implantation point N3 to root apex point N4, and |N3N4| represents the Euclidean distance between implantation point N3 and root apex point N4.

[0153] In some embodiments, the calculation formula for the lateral error of the implantation point is:

[0154]

[0155] where h 1 represents the lateral error of the implantation point.

[0156] In some embodiments, the calculation formula for the total error of the root tip point is:

[0157]

[0158] where d 2 represents the total error of the root tip point, x N4 represents the X-axis coordinate value of the root tip point N4, x N2 represents the X-axis coordinate value of the root tip point N2, y N4 represents the Y-axis coordinate value of the root tip point N4, y N2 represents the Y-axis coordinate value of the root tip point N2, z N4 represents the Z-axis coordinate value of the root tip point N4, z N2 represents the Z-axis coordinate value of the root tip point N2.

[0159] In some embodiments, the calculation formula for the depth error of the root tip point is:

[0160]

[0161] where v 2 represents the depth error of the root tip point, represents the direction vector from the implantation point N3 to the root tip point N2.

[0162] In some embodiments, the calculation formula for the lateral error of the root tip point is:

[0163]

[0164] where h 2 represents the lateral error of the root tip point.

[0165] In some embodiments, the calculation formula for the angle error is:

[0166]

[0167] where θ represents the angle error, represents the direction vector from the implantation point N1 to the root tip point N2.

[0168] In some embodiments, the method further includes: displaying the numerical values of multiple implantation accuracy indicators.

[0169] In some embodiments, the method further includes: determining whether the value of each implantation accuracy index is within the corresponding preset value range; when the values of all implantation accuracy indexes are within the corresponding preset value ranges, determining that the surgery is successful; otherwise, determining that the surgery is a failure.

[0170] In some embodiments, before step S100, the method further includes: pre-determining a first model. At this time, the method further includes steps S101 to S106.

[0171] Step S101: Register the preoperative planned oral medical image model of the target object with the postoperative oral medical image model to move the first model to a position close to the second model.

[0172] In some embodiments, an image registration framework is used to register the preoperative planned oral medical image model of the target object with the postoperative oral medical image model to move the first model to a position close to the second model and obtain a registration matrix of the image models. Among them, the image registration framework is a modular tool set.

[0173] Optionally, the image registration framework includes an ITK (Insight Segmentation and Registration Toolkit) image registration framework.

[0174] Step S1021: Generate a first bounding space unit that encloses the second model.

[0175] As described above, the second model is a mesh model composed of multiple vertices. In some embodiments, step S102 includes steps S1021 to S1025.

[0176] Step S1021: Traverse the coordinates of all vertices of the second model, and record the maximum X-axis coordinate value x_max, the maximum Y-axis coordinate value y_max, the maximum Z-axis coordinate value z_max, the minimum X-axis coordinate value x_min, the minimum Y-axis coordinate value y_min, and the minimum Z-axis coordinate value z_min among the coordinates of all vertices.

[0177] Step S1022: Generate a second bounding space unit based on the maximum X-axis coordinate value x_max, the maximum Y-axis coordinate value y_max, the maximum Z-axis coordinate value z_max, the minimum X-axis coordinate value x_min, the minimum Y-axis coordinate value y_min, and the minimum Z-axis coordinate value z_min.

[0178] Specifically, from the point (x_max, y_max, z_max), the point (x_min, y_max, z_max), the point

[0179] The enclosed space formed by the eight points (x_max, y_min, z_max), (x_max, y_max, z_min), (x_min, y_min, z_max), (x_min, y_max, z_min), (x_max, y_min, z_min), and (x_min, y_min, z_min) is the second enclosed space unit of the second model.

[0180] Step S1023: Calculate the midpoint (x_Center, y_Center, z_Center) of the second enclosed space unit.

[0181] Where x_Center represents the X-axis coordinate value of the midpoint of the second enclosed space unit, y_Center represents the Y-axis coordinate value of the midpoint of the second enclosed space unit, and z_Center represents the Z-axis coordinate value of the midpoint of the second enclosed space unit.

[0182] In some embodiments, the calculation formulas for the coordinate values of the midpoint of the second enclosed space unit on each axis are respectively:

[0183] x_Center = (x_max + (x_min)) / 2.0;

[0184] y_Center = (y_max + (y_min)) / 2.0;

[0185] z_Center = (z_max + (z_min)) / 2.0.

[0186] Step S1024: Expand the second enclosed space unit by a preset multiple to calculate the eight vertices of the first enclosed space unit.

[0187] Optionally, the preset multiple is 1.5 times, 2 times, etc.

[0188] In some embodiments, calculate the maximum X-axis coordinate value x_max_new, maximum Y-axis coordinate value y_max_new, maximum Z-axis coordinate value z_max_new, minimum X-axis coordinate value x_min_new, minimum Y-axis coordinate value y_min_new, and minimum Z-axis coordinate value z_min_new of the first enclosed space unit. Then, based on the maximum X-axis coordinate value x_max_new, maximum Y-axis coordinate value y_max_new, maximum Z-axis coordinate value z_max_new, minimum X-axis coordinate value x_min_new, minimum Y-axis coordinate value y_min_new, and minimum Z-axis coordinate value z_min_new, obtain the eight vertices of the first enclosed space unit. The method is referred to the above description.

[0189] In some embodiments, when the preset multiple is 1.5 times, the formulas for calculating the coordinate values are respectively:

[0190] x_min_new = x_Center - (x_max - x_Center) × 1.5;

[0191] x_max_new = x_Center + (x_max - x_Center) × 1.5;

[0192] y_min_new = y_Center - (y_max - y_Center) × 1.5;

[0193] y_max_new = y_Center + (y_max - y_Center) × 1.5;

[0194] z_min_new = z_Center - (z_max - z_Center) × 1.5;

[0195] z_max_new = z_Center + (z_max - z_Center) × 1.5.

[0196] Step S1025: Generate the first bounding space unit based on the eight vertices of the first bounding space unit.

[0197] The spatial closed figure formed by the eight vertices of the first bounding space unit is the first bounding space unit.

[0198] Step S103: Determine all the pixel points within the first bounding space unit and with pixel values greater than the preset pixel value in the postoperative oral medical image model as the target pixel point set.

[0199] In some embodiments, when using the VTK tool library, the vtkExtractVOI function is used to set the first bounding space unit as the region of interest (ROI), and then all the pixel points within the first bounding space unit and with pixel values greater than the preset pixel value in the postoperative oral medical image model are determined as the target pixel point set.

[0200] Because the density of the dental implant material is relatively large, the pixel values of the pixel points presented in the postoperative oral medical image model are relatively high and higher than the bone gray value, and the pixel points representing the dental implant can be screened out by setting the preset pixel value.

[0201] Optionally, the preset pixel value is above 3000.

[0202] Step S104: Perform three-dimensional reconstruction based on the target pixel point set and extract the connected regions to obtain at least one candidate model.

[0203] In some embodiments, when using the VTK toolkit, the vtkMarchingCube algorithm is used to perform three-dimensional reconstruction on the set of target pixel points within the ROI, and the SetExtractionModeToAllRegions function is used to extract the connected regions, obtaining at least one candidate model.

[0204] Step S105: Generate a third bounding unit that encloses each candidate model, obtaining at least one third bounding unit.

[0205] In some embodiments, the third bounding unit is a bounding box.

[0206] Step S106: Determine the candidate model in the third bounding unit with the smallest size difference degree from the preset bounding unit among all the third bounding units as the first model.

[0207] In some embodiments, calculate the length xSize of each third bounding unit on the X-axis, the length ySize on the Y-axis, and the length zSize on the Z-axis, and then calculate the size difference degree between each third bounding unit and the preset bounding unit based on the length avgxSize of the preset bounding unit on the X-axis, the length avgySize on the Y-axis, and the length avgzSize on the Z-axis.

[0208] In some embodiments, the formula for calculating the size difference degree is:

[0209] Sizedifferent = |xSize - avgxSize| + |ySize - avgySize| + |zSize - avgzSize|.

[0210] Optionally, set the size of the preset bounding unit according to the general size of the oral implant. Since the length of a general oral implant is between 8 mm and 16 mm and the diameter is about 6 mm, the length avgxSize of the preset bounding unit on the X-axis can be set to 6 mm, the length avgySize on the Y-axis to 6 mm, and the length avgzSize on the Z-axis to 12 mm.

[0211] In summary, the method for determining the model axis provided by the embodiments of the present application has the following advantages:

[0212] 1. By selecting target vertices on the inner surface of the first model based on all the intersection points of each connection line with the first model, multiple target vertices are obtained; and based on all the target vertices, the axis of the first model is determined. Compared with the method of determining its axis based on the oriented bounding box of the first model, it can effectively avoid the interference of local structures such as threads on the outer surface on determining the axis, and thus can avoid the situation of misjudging the axis when the width of the first model is greater than the length of the first model, improving the accuracy of the axis. Moreover, without generating the oriented bounding box of the first model, the speed of determining the axis is also accelerated.

[0213] 2. By using the least squares method to determine the axis of the first model based on all the target vertices, compared with the method of determining the axis by performing a rotation transformation on the first model in the oriented bounding box algorithm, without calculating the rotation matrix, the axis of the first model can be directly determined according to the target vertices, reducing the calculation error; compared with the method of using the PCA (Principal Component Analysis) algorithm to determine the axis, it can improve the accuracy of calculating for small-scale data.

[0214] 3. By performing hole filling on the first model and then determining the apical point and the implantation point of the first model, compared with the method using the oriented bounding box algorithm, there is no need to move the first model when calculating the apical point and the implantation point, and the apical point and the implantation point of the first model can be determined at any time, improving the flexibility of the method; compared with the method of calculating the transformation matrix before and after the first model is rotated to the correct position by using the axis-angle method and then determining the apical point and the implantation point, there is no need to calculate the transformation matrix, reducing the calculation error.

[0215] Please refer to Figure 11 , Figure 11 which is a schematic structural diagram of the device for determining the axis of the model provided by the embodiment of the present application. As Figure 11 shown, the device 300 for determining the axis of the model includes an acquisition module 310 and a processing module 320.

[0216] In some embodiments, the acquisition module 310 is used to acquire a first model, the first model is an oral implant model and is a mesh model composed of multiple vertices, and the surface of the first model includes an inner surface, and the inner surface is used to represent the surface where the oral implant is in direct contact with the abutment.

[0217] In some embodiments, the processing module 320 is used to calculate a first calculation point based on the coordinates of all the vertices of the first model; generate connection lines between each vertex of the first model and the first calculation point to obtain multiple connection lines; select target vertices on the inner surface of the first model based on all the intersection points of each connection line with the first model to obtain multiple target vertices; and determine the axis of the first model based on all the target vertices.

[0218] Please refer to Figure 12 , Figure 12 which is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 12 shown, the electronic device 400 includes: one or more processors 410 and a memory 420, Figure 12 and a single processor 410 is taken as an example herein.

[0219] In some embodiments, the processor 410 and the memory 420 may be connected by a bus or other means, Figure 12 and being connected by a bus is taken as an example herein.

[0220] In some embodiments, the processor 410 is configured to obtain a first model, where the first model is an oral implant model and is a mesh model composed of multiple vertices. The surface of the first model includes an inner surface, and the inner surface is used to represent the surface where the oral implant is in direct contact with the abutment; calculate a first calculation point based on the coordinates of all vertices of the first model; generate connections between each vertex of the first model and the first calculation point to obtain multiple connections; select target vertices on the inner surface of the first model based on all intersections of each connection and the first model to obtain multiple target vertices; and determine the axis of the first model based on all the target vertices.

[0221] In some embodiments, the memory 420, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions / modules for the method of determining the axis of the model in the embodiments of the present application. The processor 410 executes various functional applications and data processing of the electronic device 400 by running the non-volatile software programs, instructions, and modules stored in the memory 420, that is, implements the method of determining the axis of the model in the above method embodiments.

[0222] In some embodiments, the memory 420 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the electronic device 400, etc. In addition, the memory 420 may include a high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory 420 may optionally include a memory remotely set relative to the processor 410, and these remote memories can be connected to the controller through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0223] In some embodiments, one or more modules are stored in the memory 420 and, when executed by one or more processors 410, perform the method for determining the model axis in any of the above method embodiments. For example, perform the Figure 1 method steps S100 to S500 described above.

[0224] In some embodiments, the electronic device may be a chip, such as a Data Processing Unit (DPU) chip applied to a data center. Alternatively, the electronic device may also be a network interface card including a chip and multiple interfaces (such as PCI / PCIE interfaces, UART interfaces, USB interfaces, etc.). Alternatively, the electronic device may also be a traditional server, or may also be a server including a network interface card or a chip. The server includes a host and a data processor. The data processor is configured to schedule packets to the host or process them by itself, and the host is configured to process the packets scheduled by the data processor.

[0225] Please refer to Figure 13 , Figure 13 which is a structural block diagram of a computer-readable storage medium provided by an embodiment of the present application. Program code 510 is stored in the computer-readable storage medium 500, and the program code 510 can be called by a processor to perform the method for determining the model axis described in the above method embodiments.

[0226] The computer-readable storage medium 500 may be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk, or a ROM. Optionally, the computer-readable storage medium includes a non-transitory computer-readable storage medium. The computer-readable storage medium 500 has a storage space for program code that performs any of the method steps in the above method for determining the model axis. These program codes may be read from or written to one or more computer program products. The program codes may be compressed in a suitable form, for example.

[0227] In some embodiments, an embodiment of the present application further provides a computer program product, including a computer program that, when executed by a processor, implements the above method for determining the model axis.

[0228] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium 500. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the various embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the various embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., and are not limited thereto.

[0229] In summary, the present application provides a method and an electronic device for determining the axis of a model. The method for determining the axis of a model includes: obtaining a first model, where the first model is an oral implant model and is a mesh model composed of multiple vertices, and the surface of the first model includes an inner surface, and the inner surface is used to represent the surface where the oral implant is in direct contact with the abutment; calculating a first calculation point based on the coordinates of all vertices of the first model; generating a connection line between each vertex of the first model and the first calculation point to obtain multiple connection lines; selecting target vertices on the inner surface of the first model based on all intersection points of each connection line and the first model to obtain multiple target vertices; and determining the axis of the first model based on all the target vertices. By selecting target vertices on the inner surface of the first model based on all intersection points of each connection line and the first model to obtain multiple target vertices, and determining the axis of the first model based on all the target vertices, the present application can effectively avoid the interference of local structures such as threads on the outer surface on axis determination compared with the method of determining the axis based on the oriented bounding box of the first model, and thus can avoid the situation of misjudging the axis when the width of the first model is greater than the length of the first model, improving the accuracy of the axis.

[0230] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims

1. A method for determining a model axis, characterized in that: include: Acquire a first model, wherein the first model is an oral implant model and is a mesh model composed of a plurality of vertices, wherein a surface of the first model includes an inner surface, and the inner surface is used to represent a surface where the oral implant directly contacts the abutment; Calculating a first calculation point based on coordinates of all vertices of the first model; Generate a line connecting each vertex of the first model and the first calculation point to obtain a plurality of lines; Selecting a target vertex on the inner surface of the first model based on all intersections of each of the connecting lines and the first model to obtain a plurality of the target vertices; An axis of the first model is determined based on all of the target vertices.

2. The method for determining the model axis according to claim 1, characterized in that: The step of selecting a target vertex on the inner surface of the first model based on all intersections of each of the connecting lines with the first model to obtain a plurality of the target vertices includes: For each of the connecting lines, determining all intersection points between the connecting line and the first model; Determining whether a vertex on the connecting line is located on an inner surface of the first model based on all intersections of the connecting line and the first model; When it is determined that the vertex on the connecting line is located on the inner surface of the first model, the vertex on the connecting line is determined as the target vertex, and then a plurality of the target vertices are obtained.

3. The method for determining the model axis according to claim 2, characterized in that: For each of the connecting lines, judging whether a vertex on the connecting line is located on an inner surface of the first model based on all intersections of the connecting line with the first model includes: For each of the connecting lines, determining whether, among all the intersections of the connecting line and the first model, a distance between two intersections is greater than a first preset value; When, among all the intersection points of the connecting line and the first model, the distance between two intersection points is greater than the first preset value, it is determined that the vertex on the connecting line is not located on the inner surface; otherwise, it is determined that the vertex on the connecting line is located on the inner surface.

4. The method for determining the model axis according to claim 3, characterized in that: The step of determining, for each of the connecting lines, whether a distance between two intersection points of all the intersection points of the connecting line and the first model is greater than a first preset value comprises: For each of the connecting lines, taking the vertex on the connecting line as the first intersection point between the connecting line and the first model; Calculate a first distance between the first intersection point and each other intersection point on the connecting line to obtain a plurality of first distances; When at least one of the first distances exists that is greater than the first preset value, it is determined that among all the intersections of the connecting line and the first model, the distance between two intersections exists that is greater than the first preset value.

5. The method for determining the model axis according to claim 2, characterized in that: For each of the connecting lines, judging whether a vertex on the connecting line is located on an inner surface of the first model based on all intersections of the connecting line with the first model includes: For each of the connecting lines, when the number of all intersection points of the connecting line with the first model is one, it is determined that the vertex on the connecting line is located on the inner surface; otherwise, it is determined that the vertex on the connecting line is not located on the inner surface.

6. The method for determining a model axis according to claim 1, characterized in that: The determining the axis of the first model based on all the target vertices comprises: Calculate the average coordinate point of all the target vertices and use it as the second calculation point; Calculating a covariance matrix based on the coordinates of all the target vertices; Calculate all eigenvalues ​​of the covariance matrix and the eigenvector corresponding to each eigenvalue; Selecting an eigenvector corresponding to the largest eigenvalue of the covariance matrix as the axis direction vector of the first model; A straight line passing through the second calculation point and parallel to the axis direction vector is generated and determined as the axis of the first model.

7. The method for determining a model axis according to claim 1, characterized in that: The method further comprises: Performing hole filling processing on the first model to obtain a first plane region of the first model; Determine the intersection of the axis of the first model and the first plane area as the implantation point; An intersection point where the axis of the first model intersects with an outer layer surface of the first model, which is a surface of the first model excluding the inner layer surface, is determined as an apex point.

8. The method for determining the model axis according to claim 7, characterized in that: The first model is an oral implant model obtained based on a postoperative oral medical image model of the target object, and the method further includes: Acquire a second model, where the second model is an oral implant model obtained based on a preoperative planning oral medical image model of the target object; Determining the apex point and implantation point of the second model; A plurality of implantation accuracy indices are calculated based on the coordinates of the root apex point and the implantation point of the first model and the coordinates of the root apex point and the implantation point of the second model.

9. The method for determining a model axis according to claim 1, characterized in that: The method further comprises: Registering a preoperative planning oral medical image model of the target object with a postoperative oral medical image model to move the first model to a position close to the second model; generating a first enclosing space unit enclosing the second model; Determine all pixel points in the postoperative oral medical image model that are located in the first enclosing space unit and whose pixel values ​​are greater than a preset pixel value as a target pixel point set; Performing three-dimensional reconstruction based on the target pixel point set and extracting connected areas to obtain at least one model to be selected; Generate a third enclosing unit enclosing each of the to-be-selected models, and obtain at least one of the third enclosing units; The candidate model in the third enclosing unit having the smallest size difference with the preset enclosing unit among all the third enclosing units is determined as the first model.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method for determining a model axis according to any one of claims 1 to 9.

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