Gum line extraction method, dental instrument manufacturing method, equipment and medium

Abstract

The present application relates to a gum line extraction method, a method for manufacturing a dental instrument, an electronic device and a storage medium. The gum line extraction method comprises: obtaining a target tooth model, wherein the target tooth model comprises a plurality of polygonal patches; determining edge categories of edges of the plurality of polygonal patches, wherein the edge categories comprise tooth edges and gum edges; and determining the gum line of the target tooth model according to the edge categories of the edges. The present application solves the technical problem that the gum line of a tooth model cannot be accurately and efficiently extracted.

Description

Technical Field

[0001] The present application relates to the technical field of dental orthodontics, and in particular to a gum line extraction method, a method for manufacturing a dental instrument, an electronic device and a storage medium. Background Art

[0002] In the current invisible orthodontic dental treatment application scenarios, all application scenarios require data processing of the tooth model, and the data preprocessing of the tooth model occupies most of the time of 3D tooth printing. Especially in the application scenario of orthodontic correction, in addition to the need for data preprocessing of the tooth model, including placement, hollowing, and Boolean operations, lamination, cutting and other operations are required after printing, and the cutting operation is based on the gum line.

[0003] Currently, the gum line is mainly obtained by manual drawing or automatic recognition. However, the applicant has found that the accuracy and efficiency of the gum line obtained based on the existing gum line obtaining methods are relatively low and difficult to meet the use requirements. Summary of the invention

[0004] The present application provides a gum line extraction method, a method for manufacturing a dental instrument, an electronic device and a storage medium to solve the technical problem in the prior art that the gum line of a tooth model cannot be accurately and efficiently extracted.

[0005] According to one aspect of an embodiment of the present application, the present application provides a gum line extraction method, including: obtaining a target tooth model, wherein the target tooth model includes multiple polygonal patches; determining edge categories of edges of the multiple polygonal patches, wherein the edge categories include tooth edges and gum edges; and determining the gum line of the target tooth model based on the edge categories of the edges.

[0006] According to another aspect of an embodiment of the present application, a method for manufacturing a dental instrument is also provided, comprising: after obtaining the gum line according to the gum line extraction method, converting the gum line into a cutting line; controlling the cutting of an initial device based on the cutting line to obtain the dental instrument; wherein the initial device is associated with the target tooth model.

[0007] According to another aspect of an embodiment of the present application, an electronic device is provided, including a memory, a processor, a communication interface and a communication bus, wherein the memory stores a computer program that can be executed on the processor, the memory and the processor communicate via the communication bus and the communication interface, and the steps of the above method are implemented when the processor executes the computer program.

[0008] According to another aspect of an embodiment of the present application, a computer-readable storage medium is further provided, wherein the computer-readable storage medium stores a computer program, and is characterized in that the computer program executes the gum line extraction method or the shell-shaped dental appliance manufacturing method when executed by a processor.

[0009] The above technical solution provided by the embodiment of the present application has the following advantages compared with the related art:

[0010] In the present application, after obtaining the target tooth model, the gum line of the target tooth model can be determined according to the edge category by determining the edge category of the polygonal patch on the target tooth model. The edge as a component of the polygonal patch can further refine the target tooth model, thereby improving the accuracy of gum line extraction of the tooth model. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0013] Figure 1 A schematic diagram of the hardware environment of an optional gum line extraction method provided according to an embodiment of the present application;

[0014] Figure 2 A flowchart of an optional gum line extraction method provided according to an embodiment of the present application;

[0015] Figure 3 A schematic diagram of a polygonal surface of an optional gum line extraction method provided according to an embodiment of the present application;

[0016] Figure 4 A recognition model diagram of an optional gum line extraction method provided according to an embodiment of the present application;

[0017] Figure 5 A schematic diagram of a convolution pooling operation based on edges in a target tooth model in an optional gum line extraction method provided according to an embodiment of the present application;

[0018] Figure 6 A flowchart of an optional method for manufacturing a dental instrument according to an embodiment of the present application;

[0019] Figure 7 A schematic diagram of downsampling of an optional gum line extraction method provided according to an embodiment of the present application;

[0020] Figure 8 A flowchart of an optional three-dimensional tooth model segmentation method provided according to an embodiment of the present application;

[0021] Fig. 9 A schematic diagram of wave crests and wave troughs of an optional three-dimensional tooth model provided according to an embodiment of the present application;

[0022] Fig.10 A schematic diagram of tooth division of an optional three-dimensional tooth model provided according to an embodiment of the present application;

[0023] Fig.11 A flowchart of an optional three-dimensional tooth model provided according to an embodiment of the present application;

[0024] Fig.12 A schematic diagram of an optional combination of wave crest points of a three-dimensional tooth model provided according to an embodiment of the present application;

[0025] Fig.13 A segmentation curve diagram of an optional three-dimensional tooth model provided according to an embodiment of the present application;

[0026] Fig.14 A flowchart of an optional three-dimensional tooth model segmentation method provided according to an embodiment of the present application;

[0027] Fig.15 A two-dimensional projection image of an optional three-dimensional tooth model segmentation method provided according to an embodiment of the present application;

[0028] Fig.16 A tooth region diagram of an optional three-dimensional tooth model segmentation method provided according to an embodiment of the present application;

[0029] Fig.17 A tooth region diagram of another optional three-dimensional tooth model segmentation method provided according to an embodiment of the present application;

[0030] Fig.18 A triangular facet diagram of an optional three-dimensional tooth model segmentation method provided according to an embodiment of the present application;

[0031] Fig.19 A smoothed boundary map of an optional three-dimensional tooth model segmentation method provided according to an embodiment of the present application;

[0032] Fig. 20 A tooth sorting diagram of an optional three-dimensional tooth model segmentation method provided according to an embodiment of the present application;

[0033] Fig.21 This is a block diagram of an optional device for performing a gum line extraction method or a dental instrument manufacturing method according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0035] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application and have no specific meaning. Therefore, "module" and "component" can be used interchangeably.

[0036] In order to solve the problems mentioned in the background technology, according to one aspect of the embodiments of the present application, an embodiment of a gum line extraction method is provided.

[0037] Optionally, in the embodiment of the present application, the gum line extraction method can be applied to Figure 1 In the hardware environment composed of the terminal 101 and the server 103 shown in FIG. Figure 1 As shown, the server 103 is connected to the terminal 101 via a network, and can be used to provide services for the terminal or a client installed on the terminal. A database 105 can be set on the server or independently of the server to provide data storage services for the server 103. The above network includes but is not limited to: a wide area network, a metropolitan area network or a local area network. The terminal 101 can be a device for obtaining a three-dimensional tooth model, such as a mouth scanning model scanner, or a terminal for receiving a three-dimensional tooth model, such as a mobile phone, a computer, etc.

[0038] The gum line extraction method in the embodiment of the present application may be executed by the server 103 , or may be executed jointly by the server 103 and the terminal 101 .

[0039] like Figure 2 As shown, the method may include the following steps:

[0040] Step S202, obtaining a target tooth model, wherein the target tooth model includes a plurality of polygonal patches;

[0041] Step S204, determining edge categories of the edges of the plurality of polygonal facets, wherein the edge categories include tooth edges and gum edges;

[0042] Step S206: Determine the gum line of the target tooth model according to the edge category of the edge.

[0043] Optionally, the gum line of the three-dimensional tooth model of the user's teeth can be determined based on the gum line extraction method in this embodiment, so that subsequent tooth separation, dental instrument cutting operations, etc. can be performed according to the gum line.

[0044] The target tooth model can be a mouth scan model, which refers to a digital three-dimensional model of the user's teeth and gums generated by scanning the inside of the user's mouth; of course, it can also be a digital three-dimensional model obtained by taking an impression, first taking an impression of the teeth and gums, and then scanning the impression. The data of the three-dimensional tooth model is stored on a computer or server, and the shape or style of the three-dimensional tooth model can be displayed on a display screen for the doctor to view.

[0045] The above-mentioned polygonal patches are patches that constitute the surface of the target tooth model (the tooth part and the non-tooth part, the surface of the entire model), which can be specifically triangles, quadrilaterals, pentagons, etc. Each polygonal patch is located on a plane, and different polygonal patches can be located on the same or different planes. The surface of the target tooth model is composed of multiple polygonal patches, each of which includes multiple edges, and two adjacent polygonal patches share an edge. The endpoints of the edges are the vertices of the corresponding polygonal patches, and a vertex can be shared by multiple polygonal patches.

[0046] It should be noted that the target tooth model includes a tooth part and a gum part, and the gum line is the boundary between the tooth part and the gum part. The edges constituting the polygonal patch can be located in the tooth part or the gum part, and thus can be classified into tooth edges and gum edges. Based on this, in this embodiment, the gum line of the target tooth model can be determined according to the edge category of the edge of the polygonal patch, and the determined gum line is used to segment the tooth part and the gum part of the target tooth model.

[0047] After the gum line is obtained, the tooth film can be cut according to the position of the gum line on the target tooth model to obtain a dental appliance, such as an invisible brace, or the gum line can be used to separate the teeth of the target tooth model.

[0048] In this embodiment, after obtaining the target tooth model, the edge category can be determined by determining the edge category of the polygonal patch on the target tooth model, and then the gum line of the target tooth model can be determined. The edge as a component of the polygonal patch can further refine the target tooth model, thereby improving the accuracy of the gum line extraction of the tooth model.

[0049] As an optional example, determining the edge categories of the edges of the plurality of polygonal patches includes: acquiring target features of the edges of the plurality of polygonal patches; and determining the edge categories of the edges of the plurality of polygonal patches according to the target features.

[0050] In this embodiment, the target feature includes a geometric feature. Of course, in other embodiments, the target feature may also include a non-geometric feature, which is not specifically limited here. In this embodiment, the edge category can be determined by extracting the target feature of the edge of the polygonal face and identifying the target feature. It should be noted that when the target feature includes a geometric feature, the topological structure relationship of the space will be considered when classifying the edge, thereby improving the accuracy of gum line recognition.

[0051] In this embodiment, the target features of all edges on the target tooth model may be extracted, or the target features of a portion of the edges may be selected, and the edge category of the edge may be determined by identifying the target features of the extracted edge.

[0052] As an optional example, the target feature of an edge includes at least one of the following: a dihedral angle between a first polygonal patch and a second polygonal patch that share the edge, a first curvature value of a first vertex of the edge, a second curvature value of a second vertex of the edge, a first distance from a vertex of the first polygonal patch away from the edge to the edge, a second distance from a vertex of the second polygonal patch away from the edge to the edge, a first opposite angle of the edge in the first polygonal patch, and a second opposite angle of the edge in the second polygonal patch. In an application scenario, the target features of an edge include the above seven items.

[0053] As another optional example, the target features of an edge may include at least two of the following features: the dihedral angle between a first polygonal patch and a second polygonal patch sharing an edge, the first curvature value of a first vertex of the edge, the second curvature value of a second vertex of the edge, the first spatial coordinate of the first vertex, the second spatial coordinate of the second vertex, the length of the edge, the angle between the edge and an adjacent edge, the first distance from a vertex of the first polygonal patch farthest from the edge to the edge, the second distance from a vertex of the second polygonal patch farthest from the edge to the edge, the first opposite angle of the edge in the first polygonal patch, the second opposite angle of the edge in the second polygonal patch, the first normal of the first vertex, the second normal of the second vertex, the normal of the first polygonal patch, and the normal of the second polygonal patch.

[0054] The dihedral angle between the first polygonal patch and the second polygonal patch of the common edge is the angle between the two polygonal patches that share a common edge. The first vertex and the second vertex are the two endpoints of the edge, and the curvature value is the value of the curvature of the patch corresponding to the vertex at the vertex. Curvature is the rotation rate of the tangent direction angle to the arc length at a point on the curve, which is defined by differentiation and indicates the degree to which the curve deviates from the straight line. A numerical value indicating the degree of curvature of the curve at a certain point. The greater the curvature, the more curved the curve at the corresponding point is at the point. The above-mentioned spatial coordinates are the coordinates in the three-dimensional rectangular coordinate system where the vertex is located. The three-dimensional rectangular coordinate system can be the coordinate system where the target tooth model is located. For example, the plane where the base plate of the target tooth model is located can be defined as the xOy plane, and the normal direction of the plane is defined as the z-axis. The direction of the coordinate axis can be predetermined. For example, the gingival surface of the target tooth model is used as the plane where the X-axis and the Y-axis are located, and the tooth direction is used as the Z-axis direction. The length of an edge is the distance between its two endpoints. Because an edge may have multiple adjacent edges, there may be multiple angles between the edges, ranging from 0 to 180 degrees. When the polygon is a quadrilateral or more, there may be more than one distance from the vertex away from the edge to the edge, and the distance from each vertex to the edge may be different. When the polygon patch is a triangle patch, there is only one vertex away from the edge, so the distance from the vertex to the edge is also only one. Similarly, the edge may have one or more diagonals in the polygon patch. When there are multiple diagonals, the angle of each diagonal may be different. For example, Figure 3 As shown, the polygonal patches are a triangular patch 302, a quadrilateral patch 304 and a pentagonal patch 306, and each edge of the three polygonal patches corresponds to at least one or at least two of the above-mentioned features.

[0055] Specifically, when extracting features, find the polygonal patch corresponding to the edge of the target tooth model; the angle between the normals of the two polygonal patches can be obtained by cross product based on the normals of the polygonal patches, and the dihedral angle between the two polygonal patches is complementary to the angle between the normals, and the dihedral angle of the two polygonal patches can be obtained by subtracting the angle between the normals from 180°; the curvature value of the two vertices can be obtained according to the curvature geometry calculation method or other methods; the distance from the vertex to the edge of the polygonal patch away from the edge can be obtained according to the distance from the point to the straight line; two vectors are obtained according to the orientation of the two edges, and the angle between the two edges at the vertex of the polygonal patch can be obtained by dot product based on the two vectors, that is, the diagonal of the edge in each polygonal patch. It should be noted that the spatial coordinates corresponding to each vertex and the proximity relationship between points, edges, and faces are all known, and each target feature can be derived based on this.

[0056] As an optional example, according to the target feature, determining the edge category of the edge includes: upgrading the target feature of the initial dimension of the edge to obtain a first feature of the first dimension; reducing the first feature to obtain a second feature of the target dimension; and determining whether the edge is a tooth edge or a gum edge according to the value of the second feature. That is, in this embodiment, the target dimension can be two-dimensional, corresponding to the tooth edge and the gum edge, respectively. Of course, in other embodiments, it can also be multi-dimensional, as long as the edge category of the corresponding edge can be determined, which is not limited here.

[0057] Optionally, in this embodiment, after extracting the target features of the edge, the initial dimension of the target features can be determined according to the type and quantity of the extracted target features. The target features are first dimensionally upgraded to the first dimension to obtain the first feature, and then the first feature is dimensionally reduced to the target dimension. However, since the dimension is first upgraded and then reduced, the first feature after dimension reduction is no longer the target feature, but the second feature of the target dimension, based on which the edge category of the corresponding edge can be obtained.

[0058] Taking the initial dimension of seven dimensions as an example, the seven-dimensional target feature of the corresponding edge is input into the edge classification network to classify the corresponding edge. Specifically, the input dimension is seven dimensions, corresponding to seven geometric features, and after one convolution operation, the dimension of the target feature increases to N dimensions. Then, after k identical convolution operations, the dimension of the target feature remains unchanged, and then the number of edges is reduced through pooling operations. Then repeat the above process, that is, one dimensionality-raising convolution + k same-dimensional convolutions + pooling, so that the dimension of the target feature becomes 2N, 4N, and 8N respectively. It should be noted that in the last dimensionality-raising cycle, after k same-dimensional convolutions, an up-pooling operation is performed to gradually restore the number of edges, and then a dimensionality-reducing convolution is performed to reduce the feature dimension to 4N. After k same-dimensional convolution operations, the feature dimension is kept unchanged, and then the above process is repeated, that is, up-pooling + one dimensionality-reducing convolution + k dimensionality-raising convolutions, so that the feature dimensions become 4N, 2N, and N respectively. It should be noted that after the last dimensionality reduction cycle, the feature dimension can be further reduced to 2 dimensions. Figure 4 The dotted arrow in the middle represents the feature fusion operation. The final values ​​of the two dimensions are the probability values ​​of the edge being a tooth edge and a gum edge. The category with a large probability value can be selected as the edge category. At this point, each edge of the model is classified as a tooth edge or a gum edge.

[0059] It should be noted that the above is only for example and not for limitation. For example, the initial dimension is not limited to 7 dimensions, and the number of cycles in the process of dimensionality increase and dimensionality decrease is not limited. N is an integer not less than 7, such as 7, 8, 9, 10, etc., which can be adjusted according to actual conditions when implementing the specific implementation plan.

[0060] It should be further explained that the convolution and pooling in this step are different from the convolution and pooling operations of the image neighborhood, such as Figure 5 As shown, the operation is performed based on the edges in the target tooth model.

[0061] In order to eliminate the influence of different edge orders (such as (a, b, c, d) and (c, d, a, b)) in the convolution operation, the original edge features are processed according to the following formula (1), where f(a) and f'(a) represent the original features and processed features of edge a respectively. The convolution operation of edge e after processing is defined as shown in formula (2), where {w k |k=0,1,2,3,4} represents the weight parameter to be trained. The pooling operation transforms 5 edges (e,a,b,c,d) into 2 edges (h,i), as defined in formula (3). The upper pooling operation is the opposite of the pooling operation, transforming 2 edges (h,i) into (e',a',b',c',d'), as defined in formula (4).

[0062] f'(a)=|f(a)-f(c)|

[0063]

[0064] f'(d)=f(b)+f(d)

[0065] C(e)=w0f'(e)+w1f'(a)+w2f'(b)+w3f'(c)+w4f'(d) (2)

[0066]

[0067]

[0068] f(a')=f(b')=f(h) (4)

[0069] f(c')=f(d')=f(i)

[0070] In addition, before edge classification, the classification network needs to be trained to obtain network weight values ​​and some hyperparameter values: such as k and N, etc. Specifically, multiple groups of geometric feature data and corresponding edge classification category values ​​(such as 0 for gums and 1 for teeth) are input into the edge classification network for training. For example, 500, 1000 or 2000 groups of classified tooth model data are input, and each group of tooth model data contains 5000, 10000 or 20000 geometric feature data and classification data corresponding to the edges, so that the classification network can classify the edges according to the geometric feature data of the edges. It should be noted that in this embodiment, the method based on edge classification can automatically identify the gum line data by combining deep learning technology, which can greatly improve the recognition accuracy and efficiency, improve the efficiency of the entire invisible orthodontic and other dental diagnosis and treatment processes, and enhance the user experience in diagnosis and treatment.

[0071] As an optional example, determining the gum line of the target tooth model according to the edge category includes: determining the patch category of the polygonal patch according to the edge category, wherein the patch category includes tooth patch and gum patch; and extracting the gum line based on the common edges of adjacent polygonal patches with different patch categories.

[0072] Optionally, in this embodiment, after the edge category is determined, the patch category of the polygonal patch can be determined according to the edge category. It can be understood that the tooth patch is a patch located in the tooth part of the tooth model, and the gum patch is a patch located in the gum part. The patch category is determined according to the edge category of the edge, and the patch category of the polygonal patch can be determined according to all the edges of the polygonal patch, or the patch category of the polygonal patch can be determined according to at least one edge of the polygonal patch.

[0073] As an optional example, determining the patch category of a polygonal patch based on the edge category includes: when the number of gingival edges in the polygonal patch is greater than the number of tooth edges, determining the polygonal patch to be a gingival patch; when the number of gingival edges in the polygonal patch is less than the number of tooth edges, determining the polygonal patch to be a tooth patch.

[0074] Optionally, in this embodiment, the patch category of the polygonal patch is determined according to the edge categories of all the edges of the polygonal patch. According to the number of tooth edges and gum edges in the polygonal patch, it is determined whether the polygonal patch is a tooth edge or a gum edge.

[0075] Traverse all edges of the target tooth model. If the two facet categories corresponding to the edge are different, the edge is marked as a common edge.

[0076] As an optional example, extracting the gum line based on the common edges of adjacent polygonal patches of different patch categories includes: determining a first feature point based on the vertices of the common edge; determining a target feature point from the first feature point based on a curvature relationship; and determining the gum line based on the target feature point.

[0077] Optionally, in this embodiment, since the face category of the polygonal face can be determined according to the edge category of the edge, after the face category is determined, the common edges of the polygonal facets of different categories are the boundaries between the tooth facet and the gum facet. Therefore, the gum line can be determined according to all the common edges of the tooth facet and the gum facet.

[0078] In this embodiment, a first feature point can be determined from the vertices of the shared edge, and then a target feature point can be determined from the first feature point, and the gum line can be determined based on the target feature point. The target feature point can be obtained by calculating the curvature.

[0079] In this embodiment, a vertex of a common edge can be used as a starting point to search for connected common edges, and the vertices of each connected common edge can be recorded in a counterclockwise or clockwise order as feature points. The first feature point can be all or part of the recorded feature point. Specifically, the first feature point is located on the initial tooth model, so that the extracted gum line has a higher accuracy. The target feature point is a feature point with specific features in part of the first feature point.

[0080] As an optional example, determining the first feature point based on the vertices of the common edge includes: when the target dental model is a model obtained by performing edge shrinkage processing on the initial dental model, determining the nearest point of the vertex on the common edge on the initial dental model as the first feature point; when the target dental model is the initial dental model, determining the vertex on the common edge as the first feature point.

[0081] Optionally, the initial tooth model is the tooth model initially acquired. The initial tooth model may be subjected to edge contraction processing to obtain a target tooth model, or the initial tooth model may be directly used as the target tooth model. Whether the initial tooth model is subjected to edge contraction processing affects whether the vertex of the common edge is directly used as the first feature point. In this embodiment, the first feature point is the vertex of the common edge, or the point on the initial tooth model that is closest to the common edge.

[0082] That is to say, in this embodiment, after taking the vertex of a shared edge as the starting point, searching for connected shared edges and recording the vertices in a counterclockwise or clockwise order as feature points, the recorded feature points can be projected back to the original model, and the point on the original model closest to the recorded feature point can be found as a new feature point.

[0083] Specifically, a KDTree can be established with the vertices of the initial tooth model. KDTree is a tree data structure that stores instance points in a k-dimensional space for quick retrieval. In this embodiment, all recorded feature points can be traversed, and the nearest point can be found in KDTree as a new feature point. The new feature point is the first feature point.

[0084] As an optional example, determining the target feature point from the first feature points according to the curvature relationship includes: determining, among the first feature points, a first feature point whose curvature is greater than that of an adjacent first feature point as the target feature point.

[0085] After the first feature point is determined based on whether the initial tooth model has been processed by edge contraction, the target feature point can be determined from the first feature point based on the curvature of the first feature point. Each first feature point corresponds to a curvature. In this embodiment, the first feature point whose curvature is greater than the curvature of the adjacent first feature point is used as the target feature point, that is, the point in the curve where the position is more curved is determined as the target feature point, which can better reflect the actual trend of the curve.

[0086] After the recorded feature points are projected back to the original model, the curvature of the discrete points can be estimated using the curvature geometry algorithm, and the feature points with large curvature can be retained as target feature points. The reason for retaining feature points with large curvature is that points with large curvature are often turning points, which are more characteristic and representative.

[0087] As an optional example, determining the gum line according to the target feature points includes: performing an interpolation operation on the target feature points to obtain interpolated target feature points; and connecting the interpolated target feature points in sequence to form the gum line.

[0088] In this embodiment, interpolation operation is performed on the target feature points to compensate for the loss of feature points caused by determining the target feature points from the first feature points, and the target feature points can be combined into a closed curve through interpolation operation. The closed curve is the gum line.

[0089] When interpolating the target feature points, B-spline curve interpolation can be performed on adjacent target feature points; all points are connected in sequence, and the resulting curve is the gum line. After obtaining the gum line, the membrane can be cut based on the gum line to obtain an invisible brace or to separate the three-dimensional tooth model. It should be noted that when interpolating the target feature points, it is not limited to the B-spline curve, and other spline curves can also be used, which is not specifically limited here.

[0090] As an optional example, obtaining a target tooth model includes: obtaining an initial tooth model, wherein the initial tooth model includes multiple polygonal patches, and the number of edges in the initial tooth model is greater than the number of edges in the target tooth model; reducing the number of edges in the initial tooth model to a preset number in a preset manner to obtain the target tooth model.

[0091] Optionally, in this embodiment, the preset mode may be a shrinking operation or a collapsing operation. The shrinking operation is performed on the initial tooth model to reduce the number of edges in the initial tooth model, thereby obtaining a target tooth model, simplifying the tooth model, and improving the recognition rate of the gum line.

[0092] There are many ways to reduce the number of edges of the initial tooth model. The number of edges can be reduced one by one or a batch of edges, such as reducing one edge at a time until it is reduced to a preset number or a preset number of times. Alternatively, the number of edges can be reduced by a batch at a time until it is reduced to a preset number or a preset number of times.

[0093] Taking the edge collapse operation as an example, the imported initial tooth model can be a tooth model in any direction. The initial tooth model is a digital three-dimensional body composed of a series of vertices and polygonal patches. After the initial tooth model is imported, the tooth model is downsampled in the way of edge collapse. After downsampling, the polygonal patches of the tooth model are sparser, the number of polygonal patches is reduced, and the number of edges is also reduced. Downsampling stops until the specified number of edges is reached.

[0094] The imported initial tooth model often has many edges and the number of edges is inconsistent. When the classification network is used for classification in the subsequent steps, the number of edges required is often specific. Therefore, the imported initial tooth model needs to be downsampled, some edges are deleted, and the specified number of edges are retained. The number of edges can be determined by considering the classification speed (the fewer the number of edges, the faster the speed) and the accuracy of the final gum line (the more the number of edges, the higher the accuracy, and the more the edges, the less the information loss of the original model). The main process is as follows:

[0095] (1) For each vertex of each edge of the initial tooth model, the sum of the distances from the vertex to the adjacent facets is recorded as the error value, with the initial value being 0; wherein the adjacent facet refers to the facet where the vertex is located; the initial error value of 0 means that, before edge contraction is performed, the sum of the distances from the vertex to its adjacent facets is 0.

[0096] (2) Calculate the error value corresponding to the vertex after deleting the edge (here refers to the sum of the distances from the vertex to the adjacent facets when the edge was not deleted), and arrange them in ascending order according to the error value. First, delete the edge with the smallest error. When an edge shrinks to become a vertex, delete the two adjacent facets, and delete one vertex and three edges. There are many situations for the position where an edge shrinks to a point. For example, the two vertices of the edge can be moved to any point on the edge for deletion. The specific position of the point is selected in this step according to the smallest error value.

[0097] (3) Repeat the above steps, continuously calculate the error value and delete the corresponding edges until the number of edges reaches the specified number of edges. At this point, the adjustment of the number of edges of the initial tooth model is completed.

[0098] As an optional example, reducing the number of edges in the initial tooth model to a preset number in a preset manner to obtain a target tooth model includes: for each edge of the tooth model to be processed, calculating the sum of distances from the vertex corresponding to each edge to the adjacent polygonal facets corresponding to the vertex of each edge in the tooth model to be processed after edge shrinkage processing is performed on each edge in each of multiple shrinkage methods; wherein, in the first processing, the tooth model to be processed is the initial tooth model; determining the edge and shrinkage method corresponding to the minimum value among the calculated sums of multiple distances; performing edge shrinkage processing on the edge corresponding to the minimum value according to the shrinkage method corresponding to the minimum value to obtain the target tooth model.

[0099] As an optional example, performing edge shrinkage processing on the edge corresponding to the minimum value according to the shrinkage method corresponding to the minimum value to obtain the target tooth model includes: after the edge shrinkage processing, if the number of edges in the obtained tooth model is not greater than the preset number, the obtained tooth model is the target tooth model; if the number of edges is greater than the preset number, the obtained tooth model is determined as the tooth model to be processed to continue the edge shrinkage processing.

[0100] Optionally, in this embodiment, when performing edge shrinkage processing on the initial tooth model, it is also necessary to determine which edge to shrink. This process can be a cyclic process. That is, shrink one edge each time and cycle or shrink a batch of edges each time and cycle until the tooth model to be processed after shrinkage meets the conditions. Therefore, in each shrinkage, it is necessary to determine which edge or which batch of edges to shrink.

[0101] In this embodiment, the initial model can be used as the model to be processed, and the edges to be shrunk for the model to be processed can be determined by simulation or calculation first. If a certain edge is shrunk, the sum of the distances from the vertex corresponding to each edge in the shrunk model to the adjacent polygonal facets corresponding to the vertex of the edge in the tooth model to be processed is calculated. If the sum is the smallest, the edge is shrunk according to the strategy. Each time the edge is shrunk, the calculation is repeated, and the edge shrinkage is repeated until the number of edges of the tooth model to be processed meets the preset number requirement. At this point, the edge shrinkage is completed, and the target tooth model is obtained.

[0102] According to another aspect of the embodiment of the present application, a method for manufacturing a dental instrument is also provided. Figure 6 As shown, including:

[0103] S602, after obtaining the gum line according to the gum line extraction method, convert the gum line into a cutting line;

[0104] S604, cutting the initial equipment based on the cutting line to obtain a dental instrument.

[0105] The method for extracting the gum line is specifically referred to in the above embodiment, which will not be described here. It should be noted that in this embodiment, the initial equipment and the target tooth model have an associated relationship. Specifically, the initial equipment can be generated based on the initial tooth model or the target tooth model.

[0106] Optionally, in this embodiment, after the gum line is determined, the initial device can also be cut according to the position of the gum line on the target tooth model. The initial device is a shell-like membrane surrounding the physical tooth model, and the physical tooth model is formed by 3D printing or other methods based on the initial tooth model or the target tooth model, so that the shape of the side of the shell-like membrane being pressed is the same as the structure of the tooth part of the physical tooth model, or the structure of the tooth part is the same as that of at least part of the gum part. By cutting, the target device, that is, the tooth membrane, which is the same as the tooth part surrounding the target tooth model, can be cut from the initial device. Specifically, it can be an invisible braces.

[0107] As an optional example, when the initial equipment to be cut is obtained, before cutting the initial equipment according to the first position of the gum line on the target tooth model, the gum line extraction method also includes: performing at least one of smoothing and position adjustment processing on the gum line.

[0108] In this embodiment, before the initial equipment is cut according to the gum line, or before the gum line is converted into a cutting line, the gum line can also be adjusted. The adjustment includes smoothing and position adjustment. Smoothing means that after the final gum line is generated, the gum line is closely fitted with the real gum line. Since the intersection of teeth is relatively sharp, it does not meet the requirements of the generation process, so the gum line needs to be smoothed at this location, that is, the gum line is desharpened. Similarly, position adjustment means that after the gum line is generated, it is closely fitted with the real gum line, which does not meet the requirements of the post-generation process, and a certain margin needs to be left, that is, the gum line is shifted downward as a whole (it can also be shifted upward). The angle of the sharp angle for desharpening is limited to <180°, and the overall offset of the offset is between 0 and 2 mm. The post-processed gum line can be used as a cutting curve.

[0109] The gum line extraction method of the present application can be mainly used in the scene of correction demonstration. After determining the gum line corresponding to the user's tooth model, the teeth can be divided according to the gum line or the membrane can be cut according to the gum line. And the orthodontic guide plate, the design of the substitute tooth model and the design of the temporary teeth can be further designed based on the tooth division data.

[0110] In this embodiment, if the user's teeth are to be examined or orthodontically treated, the user's oral cavity can be scanned first to obtain data of a three-dimensional tooth model of the user's teeth. The data can be displayed to the user and the doctor through a display screen, so that the doctor can explain the condition of the teeth to the user.

[0111] The 3D dental model of the user obtained by oral scanning can be a closed or open model. The 3D dental model includes the tooth area and the gum area, and the boundary between the tooth area and the gum area is not marked. Therefore, if you want to separate the teeth, you need to determine the dividing line between the teeth and the gums (gum line).

[0112] Specifically, first, obtain the imported 3D tooth model, that is, the initial tooth model. After importing the initial tooth model, downsample the initial tooth model to reduce the number of edges of the initial tooth model and obtain a tooth model with a specified number of edges. The downsampling effect can be referred to Figure 7 , downsample the two points V1 and V2 to V, and the number of edges in the initial tooth model is reduced. Calculate the target features of each edge of the initial tooth model, and pass the edge features through the edge classification network to obtain the edge category, which is divided into two categories: tooth edge and gingival edge. Select the one with the larger value from the prediction results as the edge category. The edge classification network structure refers to Figure 4 As shown. Using the classification information of the edge, the boundary vertices of the segmentation of the gums and teeth are obtained, and these vertices are used as feature points; these feature points are projected back to the initial tooth model, and the nearest point on the initial tooth model is found as the first feature point on the initial tooth model; the feature point with the larger curvature among the first feature points is retained as the target feature point; the target feature point on the initial tooth model is interpolated to obtain a closed curve, which is the gum line. The automatic recognition method of the gum line of the tooth model will greatly promote the automated generation and processing flow of orthodontics, and improve work efficiency and user experience.

[0113] According to another aspect of the embodiment of the present application, a method for manufacturing a dental instrument is also provided, and the method for manufacturing a dental instrument may include the following steps:

[0114] Step 1: Get a digital tooth model.

[0115] The tooth model may be the target tooth model in the gum line extraction method embodiment. Accordingly, the tooth model may be obtained in the same manner as the target tooth model, that is, it may be obtained by mouth scanning or by traditional impression taking, which is not limited here.

[0116] Step 2: pre-process the digital tooth model.

[0117] In one embodiment, the pre-processing operation may include steps in the gum line extraction method to identify the gum line, and may further include converting the gum line into a cutting line for cutting the initial equipment in the subsequent step to obtain the dental instrument, or in some application scenarios, it can also be applied to automatic tooth segmentation, gum crown separation, etc. Among them, the gum line extraction method can be the same as that in the gum line extraction method embodiment described above, and the relevant details can be referred to the aforementioned content, which will not be repeated here.

[0118] In another embodiment, the pre-processing operation may further include performing a tooth segmentation operation on the target tooth model.

[0119] In some application scenarios, tooth segmentation can be performed based on the extracted gum line. Figure 8 As shown, the method for performing a tooth segmentation operation on a target tooth model may include the following steps:

[0120] Step S202, obtaining the gum line of the three-dimensional tooth model and the tooth area of ​​the three-dimensional tooth model;

[0121] Step S204, extracting the peak points of the gum line, and pairing the peak points to obtain a peak point combination;

[0122] Step S206, determining a segmentation path between teeth in the tooth region based on the combination of peak points;

[0123] Step S208, segmenting the tooth region according to the segmentation path to obtain target segmented teeth.

[0124] It should be noted that the three-dimensional tooth model here can be understood as the aforementioned target tooth model.

[0125] Optionally, the purpose of the above three-dimensional tooth model segmentation method is to accurately segment each tooth on the three-dimensional tooth model into individual teeth.

[0126] The gum line acquisition method in this application scenario can be the same as that in the aforementioned gum line extraction implementation. For details, please refer to the aforementioned implementation and will not be repeated here. Of course, the gum line can also be determined by identifying a two-dimensional projection image of a three-dimensional tooth model, which is not limited here.

[0127] Optionally, the peak point of the above three-dimensional tooth model can be a point on the gum line of the three-dimensional tooth model that is higher than the adjacent points. For example, on the gum line of the three-dimensional tooth model, a straight line formed by multiple points continues to rise and starts to drop at one point, then this point is a peak point. The peak point can be understood as the highest point of the gums located at the gap between two teeth.

[0128] In the present embodiment, the pairing of the crest points can determine every two crest points as a crest point combination, and the two crest points in a crest point combination are used to determine the boundary between two teeth. Each crest point combination includes two crest points.

[0129] In this embodiment, after the peak point combination is determined, a segmentation path between two teeth in the tooth region can be determined according to the two peak points.

[0130] According to the segmentation path, the tooth area can be segmented to obtain a single tooth. Fig. 9 As shown, there are peaks and valleys on the gum line between the teeth and gums in the 3D tooth model ( Fig. 9 The peak point is the higher point on the gum between the two teeth (it may be the highest point, or not the highest point, located on the gum line). The trough point is the lower point on the gum line. By pairing the peak points, the peak points at the gap between each two teeth can be matched into a peak point combination. Through the peak point combination, the segmentation path between the two teeth can be determined. Finally, the teeth are segmented through the segmentation path to obtain a single tooth. The segmentation result can be shown as follows: Fig.10 shown.

[0131] The present application obtains the gum line and the tooth area of ​​the three-dimensional tooth model, extracts the peak points of the gum line, and pairs the peak points to obtain a peak point combination, and then determines a segmentation path based on the peak point combination, and segments the tooth area according to the segmentation path to obtain a method for segmenting target teeth, thereby accurately segmenting each tooth in the three-dimensional tooth model, thereby achieving the effect of accurately segmenting the three-dimensional tooth model.

[0132] As an optional example, obtaining the tooth region of the three-dimensional tooth model includes: segmenting the three-dimensional tooth model based on the gum line to obtain the tooth region of the three-dimensional tooth model.

[0133] Optionally, in this embodiment, before dividing the three-dimensional tooth model, the three-dimensional tooth model can be segmented using the gum line, and after segmentation, the tooth region of the three-dimensional tooth model is obtained. Segmenting the three-dimensional tooth model can be regarded as hiding or not processing the gum region of the three-dimensional tooth model, and when dividing the three-dimensional tooth model later, the gum region can be prevented from affecting the accuracy of dividing the teeth.

[0134] As an optional example, before obtaining the gum line of the three-dimensional tooth model, the method further includes: determining an initial orientation of the three-dimensional tooth model; and adjusting the three-dimensional tooth model from the initial orientation to a target orientation.

[0135] Optionally, in this embodiment, after obtaining the user's oral scan data to obtain the user's three-dimensional dental model, the direction of the three-dimensional dental model can be adjusted. The purpose of adjusting the direction of the three-dimensional dental model is to "straighten" the three-dimensional dental model, so that all three-dimensional dental models can be adjusted to a fixed orientation, making curvature recognition more accurate. For example, the initial orientation may be different for all three-dimensional dental models. If the desktop is taken as a horizontal plane, the direction of the upward normal of the desktop can be taken as the target orientation. Then, after the three-dimensional dental model is adjusted to the target orientation, it can be in a state where the teeth are facing upward. After obtaining the three-dimensional dental model, the orientation of the three-dimensional dental model can be adjusted to the target orientation, so that the directions of all the acquired three-dimensional dental models can be unified.

[0136] As an optional example, determining the initial orientation of the 3D tooth model includes: if the 3D tooth model is a non-closed model, determining the minimum directed bounding box of the 3D tooth model; and determining the initial orientation of the 3D tooth model according to the minimum directed bounding box.

[0137] Optionally, in this embodiment, the three-dimensional tooth model can be divided into two types, the first type is a closed model, and the second type is a non-closed model. The closed model is formed by adding a plane as the bottom surface after the edge is stretched.

[0138] For a non-closed 3D tooth model, a minimum directed bounding box can be used to enclose the 3D tooth model. The two faces with the largest area of ​​the minimum directed bounding box are the side of the 3D tooth model facing the teeth and the side of the gum part away from the teeth. The direction of one normal vector can be selected from the two largest normal vectors of the two faces of the minimum directed bounding box as the target orientation.

[0139] As an optional example, determining the initial orientation of a three-dimensional tooth model based on a minimum directed bounding box includes: confirming a preset axis direction based on the two faces with the largest area of ​​the minimum directed bounding box; based on the preset axis direction, obtaining a first average coordinate value of a boundary edge of the three-dimensional tooth model and a second average coordinate value of vertices of a polygonal facet of the three-dimensional tooth model; and determining the initial orientation based on the first average coordinate value and the second average coordinate value.

[0140] Optionally, in this embodiment, the preset axis may be a preset direction, such as a coordinate axis of a three-dimensional space or other directions. Any direction is taken as the preset direction, and the direction of the preset axis is the same as the preset direction.

[0141] After determining the preset axis, the first average coordinate value of the boundary edge of the three-dimensional tooth model and the second average coordinate value of all vertices can be obtained. The boundary edge is the boundary between the teeth and gums. The first average coordinate value of the boundary edge can be understood as the average value of the dividing points of the teeth and gums, and the second average coordinate value can be understood as the center of gravity of the three-dimensional tooth model. The center of gravity of the three-dimensional tooth model is biased toward one side of the tooth area. Therefore, of the two largest faces of the minimum directed bounding box that encloses the three-dimensional tooth model, the face that is closer to the second average coordinate value is the side where the teeth are located. Therefore, the initial orientation of the three-dimensional tooth model can be determined.

[0142] As an optional example, determining the initial orientation of the three-dimensional tooth model includes: when the three-dimensional tooth model is a closed model, determining the polygonal patch group to which the polygonal patches on the surface of the three-dimensional tooth model belong, wherein the plane angle between any two polygonal patches in the same polygonal patch group is less than an angle threshold; and determining the initial orientation of the three-dimensional tooth model based on the sum of the areas of the polygonal patches in the polygonal patch group.

[0143] In this embodiment, the closed model can be obtained by filling a non-closed model, or by directly scanning the inside of the oral cavity to obtain a closed three-dimensional tooth model. The closed three-dimensional tooth model can determine the initial orientation by calculating the area of ​​a polygonal patch group composed of polygonal patches.

[0144] As an optional example, when the three-dimensional tooth model is a closed model, determining the polygonal patch group to which the polygonal patches on the surface of the three-dimensional tooth model belong includes: selecting any first patch from all patches that have not been divided into the polygonal patch group as a patch in a polygonal patch group, and determining the polygonal patch whose plane normal angle with the first patch is less than an angle threshold as a patch located in the same polygonal patch group as the first patch, wherein, in an initial case, all polygonal patches on the three-dimensional tooth model are not divided into the polygonal patch group; continuing to select any target patch from all patches that have not been divided into the polygonal patch group as a patch in another polygonal patch group, and determining the polygonal patch whose plane normal angle with the target patch is less than the angle threshold as a patch located in the same polygonal patch group as the target patch, until all polygonal patches are divided into the polygonal patch groups.

[0145] As an optional example, when the three-dimensional tooth model is a closed model, determining the polygonal patch group to which the polygonal patches on the surface of the three-dimensional tooth model belong includes: selecting any first patch from all patches that have not been divided into the polygonal patch group as a patch in a polygonal patch group, and determining a polygonal patch whose normal has an angle with the normal of the first patch that is less than an angle threshold as a patch in the same polygonal patch group as the first patch, wherein, in an initial case, all polygonal patches on the three-dimensional tooth model are not divided into the polygonal patch group; selecting any target patch from all faces that have not been divided into the polygonal patch group as a patch in another polygonal patch group, and determining a polygonal patch whose normal has an angle with the normal of the target patch that is less than the angle threshold as a patch in the same polygonal patch group as the target patch, until all polygonal patches are divided into the polygonal patch group.

[0146] In this embodiment, the polygonal patches may be grouped to obtain different polygonal patch groups, and the angles between the polygonal patches in the polygonal patch groups are smaller than the angle threshold.

[0147] When dividing polygonal patch groups, any polygonal patch among all polygonal patches can be used as a polygonal patch in a polygonal patch group. Then, with the polygonal patch as the base patch, all polygonal patches whose face angle with the polygonal patch is less than the angle threshold or whose normal angle with the normal of the polygonal patch is less than the angle threshold are added to the polygonal patch group. Then, among the remaining polygonal patches, the face angle of each polygonal patch with the face angle of the base patch is greater than or equal to the angle threshold. Repeat this operation until all polygonal patches belong to a polygonal patch group. The polygonal patches in each polygonal patch group can be considered to be located on the same plane. Calculate the sum of the areas of the polygonal patches in the polygonal patch group. The polygonal patch in the polygonal patch group with the largest sum of areas is considered to be the gum side of the closed model, and the other side is the tooth side, thereby determining the initial orientation of the three-dimensional tooth model.

[0148] As an optional example, extracting the peak point of the gum line includes: determining the coordinate value of each point on the gum line based on the target orientation; and determining the peak point from the gum line according to the coordinate value, wherein the coordinate value of the peak point is greater than the coordinate value of the adjacent point of the peak point on the gum line.

[0149] In this embodiment, since the orientation of the three-dimensional tooth model is adjusted to the target orientation, for a point on the gum line, if the coordinate value in the target direction is greater than that of an adjacent point, then the point is regarded as a peak point.

[0150] If the distance between two adjacent peak points is too close, one of the points with a larger coordinate value can be used as the peak point, and the other point is not used as the peak point, because the peak point is the gap area between two teeth. Therefore, the two peak points cannot be too close to each other. If they are too close, it means that the peak point may be determined incorrectly.

[0151] As an optional example, pairing the peak points to obtain the peak point combination includes: dividing the peak points into a first peak point group and a second peak point group according to the positional relationship between the peak points and the three-dimensional tooth model; taking each peak point in the first peak point group as a first peak point, and taking the first peak point and the second peak point in the second peak point group as a group of peak point combinations, wherein the second peak point is the peak point in the second peak point group that is closest to the first peak point, and the angle between the line connecting the first peak point and the second peak point and the tooth midline of the three-dimensional tooth model is greater than an angle threshold.

[0152] Optionally, in this embodiment, when pairing the crest points, two crest points that are closest to each other and whose connecting line passes through the tooth center line are paired as a pair of crest point combinations. The tooth center line is the connecting line of the midpoints of the teeth on the three-dimensional tooth model. If the crest points pass through the connecting line, it means that the crest points on both sides of the tooth are paired, and the crest points on one side of the tooth are not paired.

[0153] As an optional example, after taking each peak point in the first peak point group as a first peak point, and combining the first peak point and the second peak point in the second peak point group as a group of peak points, the method also includes: deleting the successfully paired peak points from the first peak point group and the second peak point group; taking each peak point in the second peak point group as a third peak point, and combining the third peak point and the fourth peak point in the first peak point group as a group of peak points, wherein the fourth peak point is the peak point in the first peak point group that is closest to the third peak point, and the angle between the line connecting the third peak point and the fourth peak point and the tooth midline of the three-dimensional tooth model is greater than an angle threshold.

[0154] In this embodiment, pairing can be performed one by one starting from the peak points on one side of the tooth in the three-dimensional tooth model. For each peak point on one side of the tooth in the three-dimensional tooth model, a peak point with the smallest distance is selected from the other side of the tooth and the angle between the line connecting the two peak points and the tooth midline meets the preset threshold condition. The two peak points are combined into a peak point combination. After the pairing is completed, all successfully paired peak points are deleted, and then pairing is performed again starting from the other side of the tooth, thereby achieving pairing of all peak points.

[0155] Furthermore, if the peak point with the smallest distance is found only based on the distance, it is easy to make matching errors in the case of bevel teeth or incisors. The above matching method can avoid matching errors in this scenario by using whether the angle meets the preset threshold condition.

[0156] There may be many situations in which pairing fails, such as the distance between the two peak points is too large, or one peak point on one side can be paired with both peak points on the other side.

[0157] As an optional example, based on the peak point combination, determining the segmentation path between teeth in the tooth area includes: determining each peak point combination as the current combination; and determining the shortest distance between two peak points in the current combination on the three-dimensional tooth model as a segmentation path.

[0158] After the peak point combination is determined, a segmentation path may be determined according to the peak point combination. The segmentation path may be the shortest path between two peak points on the tooth.

[0159] As an optional example, based on the peak point combination, determining the segmentation path between teeth in the tooth area includes: determining each peak point combination as the current combination; determining the shortest distance between two peak points in the current combination on the three-dimensional tooth model as the first path; correcting the first path by superimposing curvature to obtain a target path; and determining the target path as the segmentation path.

[0160] In this embodiment, the segmentation path can be used as the path for segmenting the teeth, or the segmentation path can be adjusted. After the shortest path between two peak points on the teeth is obtained, the path can be corrected by superimposing curvature, and the corrected path is used as the segmentation path.

[0161] As an optional example, the first path is corrected by superimposing curvature to obtain the target path, including: taking each point on the first path as the current point, and determining a replacement point for the current point within a preset range on the three-dimensional tooth model; wherein the replacement point is a point that meets the curvature threshold requirement; and taking the line connecting the replacement points as the target path.

[0162] In this embodiment, the shortest path is corrected by superimposing curvature, that is, the points on the path are locally adjusted according to the curvature, and each point on the shortest path is corrected. Each point is used as the current point. If there is a point that meets the curvature threshold requirement within a preset range near the current point on the three-dimensional tooth model, the current point is replaced with the point that meets the curvature threshold requirement. The replaced points are connected as the segmentation path.

[0163] The above three-dimensional tooth model segmentation method is described below with reference to an example.

[0164] The 3D tooth model segmentation method of the present application can be mainly used in the scene of correction display. After the teeth are segmented, the tooth position is adjusted according to the correction plan, and the corrected teeth are generated and displayed. Furthermore, the tooth segmentation technology can also be applied to the design of orthodontic guides, the design of substitute dental models, and the design of temporary teeth.

[0165] In this embodiment, if the user's teeth are to be examined or orthodontically treated, the user's oral cavity can be scanned first to obtain data of a three-dimensional tooth model of the user's teeth. The data can be displayed to the user and the doctor through a display screen, so that the doctor can explain the condition of the teeth to the user.

[0166] The 3D dental model of the user obtained by mouth scanning can be a closed or open model. The 3D dental model includes the tooth area and the gum area, and the boundary between the tooth area and the gum area is not marked. Therefore, if you want to separate the teeth, you need to determine the dividing line between the teeth and the gums (gum line) and the segmentation path between the teeth.

[0167] That is to say, in this scheme, the scanning data output by the 3D scanner is obtained; based on the identified model features, the model is automatically aligning; based on the automatically aligning model, the characteristic values ​​of the three-dimensional dental mold are extracted by the curvature geometry algorithm, and the extracted characteristic values ​​are filtered and denoised to obtain the gum line and its peak points, and the tooth part and the gum part are separated to obtain the pure tooth part; the peak points of the gum line are used for pairing, and the segmentation path between teeth is determined by the curvature and shortest path method to obtain all segmented teeth.

[0168] Fig.11 This is an optional flow chart of this embodiment. In this embodiment, segmenting the three-dimensional tooth model is mainly divided into the following steps:

[0169] 1 Import the model

[0170] Importing a model means importing a 3D tooth model. A 3D tooth model is a model obtained by oral scanning. After the 3D tooth model is imported into the system, the system can display the structure of the 3D tooth model on the display screen.

[0171] The three-dimensional tooth model can be a scanned model (non-closed model) output by a 3D scanner, and the input three-dimensional tooth model can be in any direction. In this solution, any other type of tooth model with a plane does not affect the implementation of the present invention.

[0172] The 3D tooth model is a digital 3D body composed of a series of polygonal patches.

[0173] 2. Automatic model alignment

[0174] After the 3D tooth model is imported into the model, it may have different orientations. Therefore, the orientation of the 3D tooth model can be adjusted to the target orientation first, so as to straighten the 3D tooth model.

[0175] For the imported 3D tooth model, its features are identified. The purpose of identifying features is to find the alignment angle of the 3D tooth model. Due to the different application types of different dental models, their features are inconsistent. At the same time, according to different dental model types, they can be classified by extracting features. When aligning, it is necessary to determine the initial orientation of the 3D tooth model and then adjust it to the target orientation.

[0176] There are several ways to determine the initial orientation. For example,

[0177] 1) If the model is a mouth scan model, which is a non-closed model, the oriented bounding box (OBB) technology is first used to determine the bounding box of the model, and the direction of a normal line of the two largest surfaces of the six surfaces of the bounding box is determined as the final tooth orientation. This method determines the size and direction of the box based on the geometric shape of the object itself, and the box does not need to be perpendicular to the coordinate axis. In this way, the most suitable and compact bounding box can be selected.

[0178] After obtaining the enclosing box, the first average coordinate value of the boundary edge of the three-dimensional tooth model and the second average coordinate value of the vertex of the polygonal face of the three-dimensional tooth model are obtained based on the preset axis direction. Then, the side where the second average coordinate value is closer to the face is determined as the side of the tooth orientation, and the initial orientation of the three-dimensional tooth model is determined.

[0179] According to the angle of the target, the enclosing box is rotated using the rotation matrix so that the model is rotated to the target direction.

[0180] 2) If the model is a closed model with a flat bottom surface, it is aligned according to the method of the largest flat bottom surface of the model. The method for detecting the largest plane of the tooth is: set a certain polygonal patch, superimpose the set polygonal patch and the 3D tooth model composed of polygonal patches, set the error threshold e, when e is greater than a certain value, it is considered that the set polygonal patch and the patch on the 3D tooth model are not flat; otherwise, they are considered to be in the same plane. When the set polygonal patch and a patch of the tooth model are in the same plane, superimpose them together, and continue to look for the next polygonal patch and judge the error threshold. The above steps are repeated until the largest plane of the tooth model is obtained. Determine the current normal vector of the largest plane of the tooth model, and obtain the target normal vector of the largest plane of the tooth model.

[0181] According to the cross multiplication method, the rotation angle and rotation axis are solved according to the vector values ​​before and after the rotation (using the cross multiplication method, the current normal vector and the target normal vector are solved to obtain the rotation angle and rotation axis). The cross multiplication method is a binary operation of vectors in vector space, and its operation result is a vector rather than a scalar; using the above rotation angle and its rotation axis, any model can be rotated to the desired spatial position.

[0182] 3 Extracting the gum line based on feature recognition

[0183] The purpose of identifying and extracting the gum line of a three-dimensional tooth model is to divide the three-dimensional tooth model according to the gum line. The gum line can be determined in a variety of ways. For example, it can be determined by a neural network model, and the three-dimensional tooth model can be input into the neural network model, and the gum line of the three-dimensional tooth model can be marked by the neural network model. Alternatively, the three-dimensional tooth model can be projected onto a two-dimensional plane, and then the tooth area on the two-dimensional plane can be identified and then corresponded to the three-dimensional tooth model, thereby marking the boundary between the teeth and the gums, that is, the gum line.

[0184] Taking the neural network model to identify the gum line as an example, after placing the model at the specified position, the characteristic values ​​extracted from the tooth model are filtered and de-noised according to the geometric calculation method of curvature to obtain the contour of the three-dimensional tooth model; the curvature plan calculation method is the rotation rate of the tangent direction angle of a certain surface on the dental model to the arc length, indicating the degree of concavity and convexity of the surface, which is also called a feature in this scheme. The characteristic values ​​of the concave and convex areas of the dental model can be obtained through the curvature method (the real gum line on the dental model is also reflected by concavity and convexity);

[0185] After obtaining the initial dental model feature value, it is necessary to remove the noise. The reason for removing the noise is that in addition to the gum line area, other parts of the teeth also have bumps and depressions, which are also considered as features. This part will affect the subsequent fitting with the contour line, so it needs to be filtered or removed to finally get the optimal feature value.

[0186] The eigenvalues ​​are simplified into a contour line, that is, an initial gum line. Since the initial gum line is not a smooth curve, there will be local folding and deviation. The principal component analysis method is used to process the initial gum line to obtain the points of the main direction. The data is determined by whether the main direction is consistent. For example, the peaks and troughs are the locations where the curve bends and changes direction. These locations can determine the points of the main direction. In view of this situation, this solution uses the principal component analysis method to obtain its main contour shape, determine the points of the main direction of the contour, avoid the non-smooth area of ​​the line segment, and obtain the final smooth gum line required.

[0187] 4. Segmentation of gums and teeth based on gum line

[0188] After the gum line is identified, the tooth part and the gum part of the three-dimensional tooth model can be segmented according to the position of the gum line. The purpose of segmenting the tooth part and the gum part is to make the tooth division more accurate.

[0189] 5. Obtain peak points based on the gum line and perform pairing

[0190] The points that determine the main direction of the contour are also the peak and trough points. This solution determines the insertion control points according to the curvature of the gum line (the peak and trough points are curved areas), and because the trough point is always lower than the peak point, the peak point can be determined according to the upper and lower distances (the height difference in the target direction) and the trough point can be filtered to obtain a complete peak point.

[0191] After obtaining the peak points, pair the two peak points with the shortest distance and whose connecting line passes through the tooth midline as the starting and ending points of tooth segmentation. Fig.12 As shown, Fig.12 In the example above, the peak points on both sides of the teeth are matched. ( Fig.12 A combination of wave peak points connected by a dotted line in FIG. 1 , and not all dotted lines are shown).

[0192] 6. Obtain the segmentation curve of the tooth according to the point pairing, curvature threshold and minimum path

[0193] Since the teeth are previously connected to each other, they need to be cut through curves to form independent single teeth. This solution first uses the shortest distance method to determine the initial cutting curve. The shortest distance shown is from the paired starting peak point, along the surface of the triangular face of the dental mold, to reach the ending peak point with the shortest distance. Since the shortest distance is not the best cutting line, this solution corrects the shortest distance by superimposing the curvature. Since the contact between teeth is uneven, the shortest distance segmentation line must be within the range of large curvature. The final segmentation line is established by superimposing the two methods. The determined segmentation path is as follows: Fig.13 shown.

[0194] 7. Divide the teeth according to the segmentation curve

[0195] All teeth are divided according to the segmentation curve to obtain segmented teeth.

[0196] In other application scenarios, the tooth segmentation operation may be performed directly without the need to extract the gum line. Fig.14 As shown, the 3D tooth model segmentation method may include the following steps:

[0197] Step S202, obtaining a two-dimensional projection image of the three-dimensional tooth model, and identifying the two-dimensional projection image to obtain multiple tooth regions;

[0198] Step S204, confirming original seed points corresponding to multiple tooth regions in the three-dimensional tooth model;

[0199] Step S206, expanding the original seed point within a preset range to obtain the target seed point of the tooth in the three-dimensional tooth model;

[0200] Step S208, segmenting the three-dimensional tooth model based on the target seed point of each tooth to obtain segmented teeth.

[0201] Similarly, the three-dimensional tooth model here can be understood as the aforementioned target tooth model. The purpose of the three-dimensional tooth model segmentation method is to accurately segment each tooth on the three-dimensional tooth model into individual teeth.

[0202] The two-dimensional projection image can be an image obtained by projecting the three-dimensional tooth model onto a plane. The two-dimensional projection image includes a tooth area and a non-tooth area. By recognizing the two-dimensional projection image, multiple tooth areas can be identified, so that the teeth on the three-dimensional tooth model can be divided. Among them, the recognition method can use machine vision or artificial intelligence to recognize the two-dimensional projection image to obtain the tooth area.

[0203] The surface of the 3D tooth model is composed of polygonal patches, such as triangular patches. A triangular patch contains 3 vertices, and all the vertices of the triangular patches can be regarded as seed points. The above-mentioned original seed points are the seed points corresponding to the tooth area in the 2D projection image among all the seed points of the 3D tooth model. In other words, the tooth area can be preliminarily determined on the 3D tooth model through the original seed points.

[0204] Since the tooth area determined by the original seed point may not be accurate, the original seed point can be expanded to obtain the target seed point by expanding the original seed point. The area covered by the target seed point can be regarded as the teeth on the 3D tooth model, and the 3D tooth model can be accurately divided by the target seed point.

[0205] After the tooth area is identified, it can be understood that the position and area of ​​the teeth have been determined on the two-dimensional projection image. Then, it is matched to the three-dimensional tooth model to determine the original seed point on the three-dimensional tooth model. Since the seed point is the vertex of the triangular facet on the surface of the three-dimensional tooth model, the original seed point can be understood as the area covering the teeth on the three-dimensional tooth model. In order to ensure accuracy, the original seed point is further expanded to obtain the target seed point, and the three-dimensional tooth model is segmented according to the target seed point to obtain the segmented teeth. At this point, the teeth in the three-dimensional tooth model can be divided into single teeth.

[0206] The above method determines the original seed points on the three-dimensional tooth model by identifying the two-dimensional projection image of the three-dimensional tooth model, and expands the original seed points to obtain the target seed points, thereby marking the range of teeth on the three-dimensional tooth model through the target seed points. The three-dimensional tooth model can be further segmented according to the target seed points to obtain segmented teeth, thereby achieving the effect of accurately segmenting the three-dimensional tooth model.

[0207] Optionally, in this embodiment, after obtaining the original seed point, the original seed point may be expanded to obtain the target seed point. The process of expanding the original seed point may be divided into one or more stages.

[0208] For example, in one stage, the original seed point can be expanded according to a preset curvature threshold to obtain a target seed point. The preset curvature threshold can be understood as a constraint used when expanding the original seed point to prevent the original seed point from expanding beyond the limit. The preset curvature threshold may include one or more curvature values. If the preset curvature threshold includes a curvature value, the original seed point can be expanded according to the curvature value to obtain the target seed point. If the preset curvature threshold includes multiple curvature values, the first curvature value can be used to expand the original seed point, and then the second curvature value can be used to expand the expansion result of the first curvature value, and the third curvature value can be used to expand the expansion result of the second curvature value, until all curvature values ​​are used once.

[0209] As an optional example, expanding the original seed point according to a preset curvature threshold to obtain a target seed point includes: expanding the original seed point according to an initial curvature threshold to obtain a first seed point; expanding the first seed point according to a target curvature threshold to obtain a target seed point, wherein the target curvature threshold is obtained based on the initial curvature threshold.

[0210] Taking the preset curvature threshold consisting of the initial curvature threshold and the target curvature threshold as an example, the original seed point is first expanded by the initial curvature threshold to obtain the first seed point, and then the first seed point is expanded by the target curvature threshold to obtain the target seed point. The initial curvature threshold and the target curvature threshold can be the same or different, and the target seed point is obtained through two expansions.

[0211] As an optional example, the original seed point is expanded according to the initial curvature threshold to obtain the first seed point, which includes: taking the seed point adjacent to the original seed point as the current seed point; when the curvature of the current seed point is less than or equal to the initial curvature threshold, taking the current seed point and the original seed point as the first seed point.

[0212] In this embodiment, when the original seed point is expanded using the initial curvature threshold, the curvature of the seed point adjacent to the original seed point can be obtained. Curvature is the rotation rate of the tangent direction angle to the arc length at a point on the curve, which is defined by differentiation and indicates the degree to which the curve deviates from a straight line. A numerical value indicating the degree of curvature of the curve at a certain point. Each seed point corresponds to a curvature. By comparing the relationship between the curvature and the initial curvature threshold, it is determined whether the seed point adjacent to the original seed point can be the first seed point. The original seed point can be used as the first seed point without comparing the curvature.

[0213] The adjacent here and in the following text can be understood as two vertices that form the same side of the same triangle with the seed point. For example, adjacent to the original seed point means two vertices that form the same side of the same triangle with the original seed point.

[0214] As an optional example, the first seed point is expanded according to the target curvature threshold to obtain the target seed point, including: taking the seed point adjacent to the first seed point as the current seed point; when the curvature of the current seed point is less than or equal to the target curvature threshold, taking the first seed point and the current seed point as the target seed points.

[0215] After the original seed point is expanded using the initial curvature threshold to obtain the first seed point, the first seed point can be expanded using the target curvature threshold to obtain the target seed point. The curvature of the seed point adjacent to the first seed point is determined, and then the curvature is compared with the target curvature threshold. By comparing the size relationship, it is determined whether the seed point adjacent to the first seed point is the target seed point. At this point, the original seed point is expanded using the initial curvature threshold and the target curvature threshold to obtain the target seed point.

[0216] As an optional example, before expanding the first seed point according to the target curvature threshold to obtain the target seed point, the method further includes: taking the sum of the initial curvature threshold and a preset value as the target curvature threshold, wherein the preset value is a positive number.

[0217] Optionally, in this embodiment, the initial curvature threshold and the target curvature threshold may be empirical values, or the initial curvature threshold may be an empirical value, and the target curvature threshold is determined based on the initial curvature threshold. For example, the sum of the initial curvature threshold and the preset value is used as the target curvature threshold, that is, the target curvature threshold is obtained based on the initial curvature threshold, and the target curvature threshold is greater than the initial curvature threshold. The preset value is a pre-set value and can be modified according to different three-dimensional tooth models.

[0218] As an optional example, after expanding the original seed point according to the initial curvature threshold to obtain the first seed point, or expanding the first seed point according to the target curvature threshold to obtain the target seed point, the above method also includes: when the corresponding point of the first seed point on the two-dimensional projection image does not fall into the corresponding tooth area, adjusting the first seed point to a non-first seed point; or when the corresponding point of the target seed point on the two-dimensional projection image does not fall into the corresponding tooth area, adjusting the target seed point to a non-target seed point.

[0219] Optionally, in this embodiment, when the original seed point is expanded according to the initial curvature threshold or the first seed point is expanded according to the target curvature threshold, it is also necessary to check whether the expanded seed point meets the requirements, that is, whether the expansion exceeds the range, whether the seed point in the non-tooth area is used as the first seed point or the seed point in the non-tooth area is used as the target seed point. For example, when the original seed point is expanded according to the initial curvature threshold, if the curvature of the seed point adjacent to the original seed point is less than or equal to the initial curvature threshold, it is also necessary to determine the area where the corresponding point of the seed point on the two-dimensional projection image is located. If it is not located in the tooth area, it means that the seed point has left the tooth area of ​​the three-dimensional tooth model, so the seed point is used as a non-first seed point. When the first seed point is expanded according to the target curvature threshold, if the curvature of the seed point adjacent to the first seed point is less than or equal to the target curvature threshold, it is also necessary to determine the area where the corresponding point of the seed point on the two-dimensional projection image is located. If it is not located in the tooth area, it means that the seed point has left the tooth area of ​​the three-dimensional tooth model, so the seed point is used as a non-target seed point.

[0220] As an optional example, after the original seed points are expanded according to the curvature threshold to obtain the target seed points, and before the three-dimensional tooth model is segmented based on the target seed points of each tooth to obtain the segmented teeth, the above method also includes: obtaining a target area by expanding the area obtained by expanding multiple tooth areas; and in the target area, expanding the target seed points according to the initial curvature threshold and height.

[0221] After the original seed points are expanded to obtain the target seed points, the teeth of the three-dimensional tooth model can be segmented according to the target seed points. In addition, the target seed points can be expanded again before segmenting the teeth. In other words, in addition to the first stage expansion of the original seed points using the initial curvature threshold and the target curvature threshold to obtain the target seed points, the second stage expansion can also be performed.

[0222] In the second stage of expansion, the tooth area on the two-dimensional projection image can be adjusted first, and the tooth area can be expanded to obtain the target area. Then, the target area is used as a limit, and the target seed point is expanded in the second stage using the initial curvature threshold and height. The purpose of expanding the tooth area to the target area is to ensure that all seed points on the teeth on the three-dimensional tooth model will be marked as target seed points to avoid omission.

[0223] As an optional example, when the target seed point is expanded according to the initial curvature threshold and height, the seed point adjacent to the target seed point can be used as the current seed point; when the height of the current seed point is greater than the preset standard height and the curvature of the current seed point is less than or equal to the target curvature threshold, the current seed point is used as the target seed point.

[0224] The height may be the value of the seed point in the preset direction of the three-dimensional tooth model. For example, the preset direction of the three-dimensional tooth model may be taken as the Z axis, and the coordinate value of the seed point on the Z axis may be taken as the height of the seed point.

[0225] The preset direction may be any direction. After the three-dimensional tooth model is obtained, the orientation of the three-dimensional tooth model may be adjusted to the preset direction, so that the directions of all the obtained three-dimensional tooth models may be unified.

[0226] When using the initial curvature threshold and height to expand the target seed point, the seed point adjacent to the target seed point can be used as the current seed point. If the curvature and height values ​​of the current seed point meet the requirements of the initial curvature threshold and height, the current seed point can be used as the target seed point, thereby completing the expansion of the target seed point.

[0227] As an optional example, when the height of the current seed point is greater than a preset standard height and the curvature of the current seed point is less than or equal to a target curvature threshold, taking the current seed point as the target seed point includes: when the height of the current seed point is greater than the standard height, and the curvature of the current seed point is less than or equal to the target curvature threshold, and the corresponding point of the current seed point on the two-dimensional projection image is within the target area, taking the current seed point as the target seed point, wherein the target area is an area obtained by enlarging multiple tooth areas; when the corresponding point of the current seed point on the two-dimensional projection image is outside the target area, taking the current seed point as a non-target seed point.

[0228] Optionally, when the target seed point is expanded using the initial curvature threshold and height, it is necessary to ensure that the expanded target seed point does not exceed the target area. The target area is the area obtained after the tooth area is expanded. The purpose of expanding the tooth area is to include a part of the non-tooth area near the tooth area in the target area, so that when the target seed point is expanded using the initial curvature threshold and height, the target seed point can be allowed to expand to the non-tooth area near the tooth area. Doing so can allow the expanded target seed point to cover all tooth areas.

[0229] As an optional example, after the target seed point is expanded according to the initial curvature threshold and height, the method further includes: taking a seed point adjacent to the expanded target seed point as a current seed point; and taking the current seed point as a target seed point as well.

[0230] After the target seed point is expanded using the initial curvature threshold and height, the expanded target seed point can be expanded again, and the seed points adjacent to the target seed point are also used as target seed points. The purpose of this expansion is also to make the expanded target seed point cover all tooth areas, so that when the tooth is segmented according to the expanded target seed point, the tooth is complete.

[0231] As an optional example, before expanding the original seed points within a preset range, the above method also includes: expanding multiple tooth areas to obtain a target area; marking points other than the points in the target area on the three-dimensional tooth model as third seed points; and expanding the third seed points according to a curvature threshold.

[0232] In this embodiment, the tooth area is first expanded to obtain the target area, the purpose of which is to make the target area include all tooth areas and also include non-tooth areas near the tooth areas. Therefore, when the points of the target area other than the points on the three-dimensional tooth model are marked as third seed points, the third seed points are not points on the teeth. By expanding the third seed points, the points of the non-tooth part (gum part or the space between teeth) close to the tooth part can be marked as third seed points, so that the boundary between the part outside the tooth and the tooth part can be brought closer to the tooth part, reducing the scope of the target area, so that although the target area includes the non-tooth area, it includes less non-tooth area.

[0233] After the third seed point is expanded, the dividing line between the tooth part and the part outside the tooth on the three-dimensional tooth model becomes "thinner".

[0234] As an optional example, expanding the third seed point according to the curvature threshold includes: taking a seed point adjacent to the third seed point as the current seed point; and taking the current seed point as the third seed point when the curvature of the current seed point is greater than the curvature threshold.

[0235] In this embodiment, when the third seed point is expanded, the third seed point can be expanded according to the curvature and the curvature threshold. The curvature of the third seed point can be calculated by calculating the rotation rate of the tangent direction angle of the point to the arc length through differentiation. The curvature threshold can be a preset threshold, and the curvature threshold can be different for different three-dimensional tooth models.

[0236] As an optional example, after taking the seed point adjacent to the third seed point as the current seed point, the method further includes: when the point corresponding to the current seed point in the two-dimensional projection image is located in the target area, taking the current seed point as a non-third seed point.

[0237] After the third seed point is expanded, it is necessary to check whether the third seed point is expanded into the target area. Because the target area includes the tooth area, if the third seed point is expanded into the target area, it may be expanded into the tooth area. Therefore, the third seed point in the target area should be returned as a non-third seed point.

[0238] As an optional example, after expanding the third seed point according to the curvature threshold, the above method also includes: determining a first area composed of the third seed points; determining a sub-area from the first area; and when the sub-area is surrounded by the target seed point, determining the seed point in the sub-area as the target seed point.

[0239] Optionally, in this embodiment, after the third seed point is expanded, the third seed point constitutes the first area. The first area can be divided into multiple sub-areas. Each of the multiple sub-areas can be understood as an area composed of multiple third seed points. If a sub-area is surrounded by the target seed point, it means that the sub-area is located within the tooth part on the three-dimensional tooth model, but the sub-area may not be a tooth, that is, a hole part on the tooth. Therefore, the seed point of the sub-area is used as the target seed point and divided into the tooth part.

[0240] As an optional example, obtaining a two-dimensional projection image of a three-dimensional tooth model includes: adjusting the orientation of the three-dimensional tooth model from an initial orientation to a target orientation; and projecting the three-dimensional tooth model with the target orientation onto a target surface to obtain a two-dimensional projection image.

[0241] Optionally, in this embodiment, when projecting the three-dimensional tooth model into a two-dimensional projection image, the orientation of the three-dimensional tooth model can be adjusted first, and the orientation can be adjusted to a target orientation. The target orientation can be a pre-set orientation. The purpose of adjusting the orientation of the three-dimensional tooth model is to make the tooth area on the two-dimensional projection image more complete and less blocked when the three-dimensional tooth model is projected into a two-dimensional projection image. For example, the horizontal plane can be used as the X-axis and Y-axis of the three-dimensional coordinate, and the upward direction of the horizontal plane can be used as the target orientation. After acquiring the three-dimensional tooth model, the tooth direction of the three-dimensional tooth model can be oriented toward the target orientation.

[0242] After adjusting the orientation of the three-dimensional tooth model, the three-dimensional tooth model may be projected onto a target plane, which may be a horizontal plane.

[0243] As an optional example, recognizing the two-dimensional projection image to obtain multiple tooth regions includes: inputting the two-dimensional projection image into a recognition model, and allowing the recognition model to mark multiple tooth regions on the two-dimensional projection image.

[0244] Optionally, in this embodiment, the two-dimensional projection image can be recognized by the recognition model, so that the tooth area can be recognized. After the two-dimensional projection image is input into the recognition model, the recognition model extracts features and recognizes, and outputs multiple tooth areas.

[0245] As an optional example, in a three-dimensional tooth model, confirming the original seed points corresponding to multiple tooth regions includes: taking the vertex of each triangle in the three-dimensional tooth model as the current vertex; when the corresponding point of the current vertex in the two-dimensional projection image is located in multiple tooth regions, taking the current vertex as an original seed point.

[0246] Optionally, in this embodiment, the surface of the three-dimensional tooth model is covered by a polygonal patch, and the polygonal patch can be a triangular patch. Taking the triangular patch as an example, each triangular patch has three vertices. Two adjacent triangular patches share an edge. Among the vertices of each triangular patch, if the point corresponding to the two-dimensional projection image is located in the tooth area, the vertex can be used as the original seed point.

[0247] As an optional example, after segmenting the three-dimensional tooth model based on the target seed point of each tooth to obtain segmented teeth, the method further includes: sorting the segmented teeth.

[0248] As an optional example, sorting the segmented teeth includes: taking the average of the midpoints of all teeth as the starting point and the midpoint of each tooth as the end point to form a vector for each tooth; taking the straight line where the two teeth with the largest distance between their midpoints are located among all teeth as the target straight line; and sorting all teeth according to the angle between the vector and the target straight line.

[0249] Optionally, after the teeth in this embodiment are segmented, they can be sorted. The line connecting the midpoint of the tooth and the midpoint of each tooth is used as a vector, and the teeth can be sorted by the angle between the target straight line formed by the two teeth with the largest distance. In other words, the teeth can be sorted starting from the first tooth on one side and going to the last tooth on the other side.

[0250] As an optional example, after segmenting the three-dimensional tooth model based on the target seed points of the teeth to obtain segmented teeth, the method further includes: smoothing the edges of the teeth to obtain smoothed edges.

[0251] As an optional example, smoothing the edge of a tooth to obtain a smoothed edge includes: sorting the vertices on the edge of the tooth; taking the second vertex among the sorted vertices as the current vertex, and performing the following operations on the current vertex until the current vertex does not include the rear vertex: taking the center point of the front vertex and the rear vertex of the current vertex as a smoothing point; each time a smooth point is obtained, taking the rear vertex of the current vertex as the new current vertex, and taking the obtained smooth point as the front vertex of the new current vertex; connecting the first vertex on the edge of the tooth with the obtained smooth point in order to obtain the smoothed edge of the tooth.

[0252] In this embodiment, the purpose of smoothing the edges of the teeth is to make the edges of the dividing line between the teeth and the parts outside the teeth smaller, so as to avoid the tooth model cut out later being too sharp and causing discomfort to the user's gums after installation.

[0253] When smoothing, a series of seed points formed a curve among the seed points that the edge of the tooth passes through. Starting from the initial seed point, average it with the second seed point to get the first midpoint, average the first midpoint with the third seed point to get the second midpoint, average the second midpoint with the fourth seed point to get the third midpoint. Repeat the above steps until the last seed point of the edge of the tooth. Connect all the midpoints in order to get the smoothed edge of the tooth.

[0254] The above three-dimensional tooth model segmentation method is described below with reference to an example.

[0255] For example, Fig.15 As shown, Fig.15A two-dimensional projection image of an exemplary three-dimensional tooth model. Fig.15 The teeth and gums in the image are the 3D tooth model obtained by scanning the mouth. If the 3D tooth model is projected onto a plane, we can see Fig.15 The two-dimensional projection image is shown.

[0256] After obtaining the user's oral scan data to obtain the user's 3D tooth model, the direction of the 3D tooth model can be adjusted. The purpose of adjusting the direction of the 3D tooth model is to project the 2D projection image so that the tooth part of the 3D tooth model can appear as much as possible on the 2D projection image.

[0257] When adjusting the direction, you can input the 3D tooth model and align it in the positive direction of the Z axis. The alignment method can be any alignment method in the art, and no further limitation is given here. For example, placing the teeth of the 3D tooth model on the table with the teeth facing upwards, the table can be the X-axis and Y-axis of the 3D rectangular coordinate system, and the normal of the table facing the teeth is the Z axis. After aligning the 3D tooth model in this direction, the teeth of the 3D tooth model will face upwards. Fig.15 It may be a top view of the three-dimensional tooth model, that is, a two-dimensional projection image obtained by projecting the three-dimensional tooth model onto a desktop.

[0258] After the three-dimensional tooth model is projected onto a plane to obtain a two-dimensional projection image, the recognition model can be used to recognize the two-dimensional projection image, so that the tooth area on the two-dimensional projection image can be recognized. The recognized tooth area can be marked with a box. The box can be the minimum axial bounding box containing the mask area, or it can be an oblique box. The recognized tooth area can be a regular shape or an irregular shape, for example, Fig.16 The box 402 in the figure is the identified tooth region. The tooth region includes teeth and some non-tooth regions. Fig.16 The boxes in the figure are examples only. Fig.17 As shown, Fig.17 is the identified tooth area.

[0259] After the tooth area is identified in the two-dimensional projection image, the actual tooth area in the three-dimensional model can be determined. The tooth area on the two-dimensional projection image corresponds to the three-dimensional tooth model, which can correspond to the tooth part on the three-dimensional tooth model. All points on the tooth part are filtered, and the points whose normal direction intersects with the original model are removed, and the remaining points after filtering are used as the original seed points.

[0260] For example, Fig.18 As shown, a three-dimensional tooth model ( Fig.18The surface (teeth part and non-teeth part, the surface of the entire model) of the model (only two front teeth are shown) is composed of triangular facets (it can also be composed of quadrilateral, pentagonal, etc. polygonal facets). The triangular facets are not completely located on the same plane, and there are angles between each other. The vertices of the triangular facets are seed points. Alternatively, after the noise is removed from the vertices of the triangular facets, the remaining points are used as seed points. If the corresponding point of the seed point on the 3D tooth model on the 2D projection image is located at Fig.16 The tooth area shown in the figure is taken as the original seed point.

[0261] In this embodiment, the original seed point can be expanded to obtain the target seed point. The purpose of expanding the original seed point is that the original seed point may not include all the tooth parts on the 3D tooth model, so the tooth parts of the 3D tooth model are covered by expansion.

[0262] The expansion of the original seed point is divided into multiple stages.

[0263] In the first stage, the original seed point is expanded by curvature. Expanding the original seed point actually means checking whether there are seed points adjacent to the original seed point that can be used as the target seed point together with the original seed point.

[0264] To determine whether seed points are adjacent, we can determine whether the seed points are located on the same straight line.

[0265] When the original seed point is extended by curvature, it can be extended twice in succession. It can be extended first by the initial curvature threshold, and then by the target curvature threshold. The target curvature threshold is the sum of the initial curvature threshold and a preset value. Therefore, for the seed point adjacent to the original seed point, first determine whether the curvature is less than the initial curvature threshold. If the curvature is less than the initial curvature threshold, it is used as the first seed point together with the original seed point. Then, if the curvature of the seed point adjacent to the first seed point is less than or equal to the target curvature threshold, it is used as the target seed point together with the first seed point. Thus, the original seed point is extended twice in succession. At this time, the first stage of extension is not over. Because the original seed point has been extended twice in succession in the first stage of extension, there may be too many extended points that exceed the tooth part. At this time, it is necessary to determine whether the corresponding position of the extended point on the two-dimensional projection image falls into the tooth area. If it falls into the tooth area, it means that the extension of the original seed point on the three-dimensional tooth model does not exceed the tooth part. If it does not fall into the tooth area, the corresponding seed point is no longer used as the target seed point. At this point, the first phase of expansion is completed.

[0266] In the second stage, the target seed points in the first stage can be expanded by the initial curvature threshold and height. In the second stage, the seed points adjacent to the target seed points obtained after the expansion in the first stage can be used as the seed points to be expanded. The curvature of these seed points is less than or equal to the initial curvature threshold, and the height is greater than the preset standard height. If both conditions are met, these seed points are also used as target seed points. If one condition is not met, it is not used as a target seed point. In a specific example, the preset standard height can be the height of the current point.

[0267] In addition, in addition to the curvature and height of these seed points meeting the conditions, these seed points must also be within the target area on the two-dimensional projection image. The target area is the area after the tooth area is enlarged. That is, on the two-dimensional projection image, the tooth area is slightly enlarged to obtain the target area. Then, during the second stage of expansion, if the expanded seed points correspond to the two-dimensional projection image and exceed the target area, the seed points that exceed the target area are not used as target seed points, that is, the expansion is rolled back. At this point, the second stage of expansion is completed.

[0268] That is to say, each tooth seed point is first expanded according to the given curvature threshold, and it is ensured that it does not exceed the tooth area range on the two-dimensional projection image. These points are used as the initial points of each tooth; based on the initial point, it is expanded again according to the given (curvature threshold + 0.2 to get the target curvature threshold), and it is ensured that it does not exceed the bounding box range of the tooth area;

[0269] The expansion is performed based on a given curvature threshold and height, and is ensured not to exceed the bounding box of the tooth area + the expanded range (i.e., the target area); each tooth boundary point is extended outward once (extended to the gaps between teeth and near the gum line), and the extension distance can be preset.

[0270] The initial seed point is not the final tooth area, and needs to be continuously diffused. This solution forms the diffusion range based on the two-dimensional projection. The tooth area bounding box + expanded area refers to the range to which the seed point can diffuse. The tooth area bounding box + expanded area forms the diffusion range based on the two-dimensional projection image, and the diffusion range can be controlled by the algorithm parameters.

[0271] The reason for multiple divisions when expanding the tooth area is that the adjacent teeth in some dental models are not clearly separated. The height is limited at the end when expanding the tooth area to reduce the possibility of the teeth extending downward to the gums. The tooth boundary is extended outward once because the teeth obtained by segmentation directly according to the curvature threshold will be much smaller than the original teeth, which is caused by the small curvature near the gum line, so it needs to be extended.

[0272] In addition to the expansion in the first and second stages, the parts outside the teeth can also be expanded. That is, the points on the three-dimensional tooth model that correspond to the points outside the target area on the two-dimensional projection image are used as the third seed points. The third seed points are points outside the tooth part, such as points on the gum part or the gaps between the teeth. This part of the seed points needs to be expanded toward the tooth part. When expanding, it can be expanded according to the curvature. If the curvature of the seed point adjacent to the third seed point is greater than the required curvature threshold, then this part of the seed points and the third seed point are used together as the third seed points, that is, the points outside the teeth. However, it should be noted that if the expanded third seed point is located in the target area on the two-dimensional projection image, the seed point may have expanded to the tooth part. Therefore, it is necessary to fall back and use the third seed point located in the target area as a non-third seed point.

[0273] The boundary between the target seed points obtained by the expansion of the first and second stages and the third seed points obtained after the expansion can be used as the boundary of the tooth.

[0274] If there are holes on the teeth, the target seed point and the third seed point may be surrounded, such as the target seed point surrounds a part of the third seed point. This is because there are holes on the teeth, and the holes are identified as third seed points. In this case, the points in the area surrounded by the target seed point are also used as target seed points.

[0275] After the expansion is completed, the tooth is segmented according to the target seed point and the third seed point to obtain a single tooth. Alternatively, the tooth boundary can be smoothed before segmenting the tooth, and the smoothed boundary will be more gentle. For example, Fig.19 As shown, S1-S4 are the points of the tooth boundary, A1 is the midpoint between S1 and S3, A2 is the midpoint between A1 and S4, and so on. By connecting all the midpoints A1-An, a smoothed boundary is obtained.

[0276] After segmenting the teeth to obtain individual teeth, the teeth can be sorted. For example, the 3D tooth model can be sorted as follows: Fig. 20 As shown. The average value of the tooth midpoint of the 3D tooth model is used as the starting point, and the tooth midpoint of each tooth is used as the midpoint, which can be connected to multiple vectors. The straight line between the two teeth with the largest tooth midpoint is used as the target line ( Fig. 20 middle dotted line), check the angle between the vector and the target line, and sort by the size of the angle.

[0277] In addition, in some embodiments, the pre-processing operation may also include slicing the digitized tooth model, adding a base plate, hollowing out the base plate, adding dental mold fixing accessories, adding identification information, etc., but is not limited to all of the aforementioned steps (i.e., gum line extraction, tooth separation, tooth arrangement, slicing, adding a base plate, hollowing out the base plate, adding dental mold fixing accessories, adding identification information, etc.), and at least one of them can be selected according to actual needs.

[0278] Step 3: Perform molding processing based on the digital tooth model after pre-processing to obtain a physical tooth mold.

[0279] In one embodiment, 3D printing can be performed based on the digital tooth model or the tooth model obtained after the above pre-processing operation to obtain a physical tooth model. The 3D printing can adopt light-curing 3D printing, such as SLA, DLP, LCD, or other 3D printing methods, such as 3DP, MJF, FDM, Polyjet, etc.

[0280] In some embodiments, based on the aforementioned pre-processing operations, the obtained physical dental model may have a hollow base plate, fixed accessories, identification information, etc.

[0281] Furthermore, the 3D printing process also includes a post-processing step, which can be selected according to the 3D printing method used. For example, when the light-curing 3D printing technology is used, the post-processing step can be selected as a post-curing, cleaning and other steps.

[0282] Of course, in other embodiments, the molding method is not limited to 3D printing, and other molding methods such as injection molding may also be used, which are not limited here.

[0283] Step 4: Perform lamination on the solid dental model.

[0284] After obtaining the solid dental model, the preheated polymer material film can be laminated on the solid dental model to obtain a shell-shaped film covering the solid dental model, that is, the initial device that has not been cut. Specifically, the shell-shaped film at least covers the tooth part of the solid dental model.

[0285] In one embodiment, an image of a physical dental mold can be collected through an image acquisition terminal, such as a CCD image sensor, and then the identification information can be identified through recognition technologies such as OCR. Then, based on the identification information, the corresponding lamination instructions are called out in the database, and lamination processing is performed based on the dental mold instructions, wherein the lamination instructions may include pressure parameters, diaphragm preheating time, lamination temperature, etc.

[0286] Step 5: Marking the shell-shaped diaphragm.

[0287] In this step, the shell-shaped membrane is mainly marked based on the identification information added in the pre-processing operation to form a mark on the shell-shaped membrane to obtain an initial device with a mark.

[0288] Specifically, similar to the aforementioned steps, an image of the physical dental model can be captured through an image acquisition terminal, such as a CCD image sensor, and then the identification information can be identified through OCR and other recognition technologies. Then, the corresponding marking instructions are called out based on the identification information to mark the shell-shaped membrane based on the parameter information contained in the marking instructions.

[0289] It should be noted that in the method for manufacturing the dental instrument, the execution of this step is not limited, that is, whether the marking operation is required can be selected according to actual needs.

[0290] Step 6: Cut the initial equipment to obtain dental instruments.

[0291] This step mainly involves cutting the initial device based on the cutting line converted from the extracted gum line, thereby removing the useless part of the initial device and retaining only the useful part, thereby obtaining a dental device. Specifically, the dental device may be an invisible brace.

[0292] It should be noted that the acquisition of the cutting line in this step can be the same as in the above-mentioned embodiment of the manufacturing method of the dental instrument. For relevant details, please refer to the above-mentioned embodiment and will not be repeated here. In addition, the order of step five and step six is ​​not limited in this embodiment.

[0293] In one embodiment, similar to the aforementioned steps, an image of a physical dental model can be captured through an image acquisition terminal, such as a CCD image sensor, and then the identification information can be identified through recognition technologies such as OCR, and then the corresponding cutting instructions can be called out based on the identification information to cut the initial equipment based on the parameter information contained in the cutting instructions.

[0294] See also Fig.21 According to another aspect of the embodiment of the present application, an electronic device is provided, including a memory 801, a processor 803, a communication interface 805 and a communication bus 807, wherein the memory 801 stores a computer program executable on the processor 803, the memory 801 and the processor 803 communicate via the communication bus 807 and the communication interface 805, and the processor 803 implements the above-mentioned gum line extraction method and / or dental instrument manufacturing method when executing the computer program. Optionally, the specific examples in this embodiment can refer to the examples described in the above embodiments, and this embodiment will not be repeated here.

[0295] According to another aspect of the embodiment of the present application, a computer program product or computer program is provided, the computer program product or computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the above-mentioned gum line extraction method and / or the method for making a dental instrument. When the embodiment of the present application is specifically implemented, the above-mentioned embodiments can be referred to, and the corresponding technical effects are achieved.

[0296] It is understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit may be implemented in one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in the present application, or a combination thereof.

[0297] For software implementation, the technology described herein can be implemented by a unit that performs the functions described herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

[0298] The aforementioned storage media include: U disk, mobile hard disk, ROM, RAM, disk or CD and other media that can store program codes.

[0299] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A gum line extraction method, characterized in that: include: Acquire a target tooth model, wherein the target tooth model includes a plurality of polygonal patches; Determining edge categories of the edges of the plurality of polygonal facets, wherein the edge categories include tooth edges and gum edges; determining a gum line of the target tooth model according to the edge category of the edge; Wherein, the determining the edge categories of the edges of the plurality of polygonal face patches comprises: acquiring target features of the edges of the plurality of polygonal face patches; determining the edge categories of the edges according to the target features; Wherein, determining the gum line of the target tooth model according to the edge category of the edge includes: determining the patch category of the polygonal patch according to the edge category, wherein the patch category includes tooth patch and gum patch; and extracting the gum line based on the common edges of adjacent polygonal patches with different patch categories.

2. The method according to claim 1, characterized in that: The target features include geometric features.

3. The method according to claim 2, characterized in that The target feature of the edge includes at least one of the following: The dihedral angle between the first polygonal patch and the second polygonal patch sharing the edge, the first curvature value of the first vertex of the edge, the second curvature value of the second vertex of the edge, the first distance from the vertex of the first polygonal patch away from the edge to the edge, the second distance from the vertex of the second polygonal patch away from the edge to the edge, the first opposite angle of the edge in the first polygonal patch, and the second opposite angle of the edge in the second polygonal patch.

4. The method according to claim 2, characterized in that: The target feature of the edge includes at least one of the following features: The dihedral angle between the first polygonal patch and the second polygonal patch sharing the edge, the first curvature value of the first vertex of the edge, the second curvature value of the second vertex of the edge, the first spatial coordinate of the first vertex, the second spatial coordinate of the second vertex, the length of the edge, the angle between the edge and the adjacent edge, the first distance from the vertex of the first polygonal patch away from the edge to the edge, the second distance from the vertex of the second polygonal patch away from the edge to the edge, the first opposite angle of the edge in the first polygonal patch, the second opposite angle of the edge in the second polygonal patch, the first normal of the first vertex, the second normal of the second vertex, the normal of the first polygonal patch, and the normal of the second polygonal patch.

5. The method according to claim 2, characterized in that: Determining the edge category of the edge according to the target feature includes: Upgrading the target feature of the initial dimension of the edge to obtain a first feature of the first dimension; Performing dimensionality reduction on the first feature to obtain a second feature of the target dimension; The edge is determined to be a tooth edge or a gum edge according to the value of the second feature.

6. The method according to claim 1, characterized in that Determining the patch category of the polygonal patch according to the edge category includes: In the polygonal patch, when the number of the gum edges is greater than the number of the tooth edges, the polygonal patch is determined to be a gum patch; when the number of the gum edges is less than the number of the tooth edges in the polygonal patch, the polygonal patch is determined to be a tooth patch.

7. The method according to claim 1, characterized in that The extracting of the gum line based on the shared edges of the adjacent polygonal facets of different facet categories comprises: Determine a first feature point based on the vertex of the common edge, wherein the first feature point is located on the initial tooth model; Determining a target feature point from the first feature points according to the curvature relationship; The gum line is determined according to the target feature point.

8. The method according to claim 7, characterized in that The determining of the first feature point based on the vertex of the shared edge comprises: In a case where the target tooth model is a model obtained by performing edge contraction processing on the initial tooth model, determining the nearest point of the vertex of the common edge on the initial tooth model as the first feature point; When the target tooth model is an initial tooth model, the vertices on the common edge are determined as the first feature points.

9. The method according to claim 7, characterized in that: According to the curvature relationship, determining the target feature point from the first feature point includes: Among the first feature points, the first feature point whose curvature is greater than the curvature of the adjacent first feature point is determined as the target feature point.

10. The method according to claim 7, characterized in that Determining the gum line according to the target feature point includes: Performing an interpolation operation on the target feature point to obtain an interpolated target feature point; The interpolated target feature points are sequentially connected to form the gum line.

11. The method according to claim 1, characterized in that: The obtaining of the target tooth model comprises: Acquire an initial tooth model, wherein the initial tooth model includes a plurality of polygonal patches, and the number of edges in the initial tooth model is greater than the number of edges in the target tooth model; The number of edges in the initial tooth model is reduced to a preset number in a preset manner to obtain the target tooth model.

12. The method according to claim 11, characterized in that The reducing the number of edges in the initial tooth model to a preset number in a preset manner to obtain the target tooth model comprises: For each edge of the tooth model to be processed, after edge shrinkage processing is performed on each edge in each of a plurality of shrinkage methods, the sum of distances from the vertex corresponding to each edge to the adjacent polygonal facets of the vertex corresponding to each edge in the tooth model to be processed is calculated; wherein, in the first processing, the tooth model to be processed is the initial tooth model; Determine the edge corresponding to the minimum value among the sums of the calculated multiple distances and the contraction method; The edge corresponding to the minimum value is subjected to the edge shrinkage processing according to the shrinkage method corresponding to the minimum value to obtain the target tooth model.

13. A method for manufacturing a dental instrument, characterized in that: include: After the gum line is obtained according to the method according to any one of claims 1 to 12, converting the gum line into a cutting line; The initial equipment is cut based on the cutting line to obtain the dental instrument; wherein the initial equipment is associated with the target tooth model.

14. The manufacturing method according to claim 13, characterized in that: Before converting the gum line into a cutting line, the method further comprises: At least one of a smoothing process and a position adjustment process is performed on the gum line.

15. The manufacturing method according to claim 13, characterized in that: Also includes: Performing tooth segmentation processing on the target tooth model; The teeth obtained after the tooth segmentation process are sorted to obtain a tooth model to be formed; wherein the initial equipment and the tooth model to be formed are associated with each other.

16. The manufacturing method according to claim 15, characterized in that: The step of performing tooth segmentation processing on the target tooth model comprises: obtaining a tooth region of a three-dimensional tooth model; Extracting the crest points of the gum line and pairing the crest points to obtain a crest point combination; Based on the combination of the wave peak points, determining a segmentation path between teeth in the tooth area; The tooth region is segmented according to the segmentation path to obtain target segmented teeth.

17. The manufacturing method according to claim 16, characterized in that: The step of pairing the peak points to obtain the peak point combination comprises: According to the positional relationship between the crest points and the three-dimensional tooth model, the crest points are divided into a first crest point group and a second crest point group; Taking each crest point in the first crest point group as a first crest point, taking the first crest point and the second crest point in the second crest point group as a crest point combination, wherein the second crest point is the crest point in the second crest point group that is closest to the first crest point, and the angle between the line connecting the first crest point and the second crest point and the tooth midline of the three-dimensional tooth model is greater than an angle threshold; Deleting the successfully paired peak points from the first peak point group and the second peak point group; Each peak point in the second peak point group is used as a third peak point, and the third peak point and the fourth peak point in the first peak point group are used as a group of peak point combinations, wherein the fourth peak point is the peak point in the first peak point group that is closest to the third peak point, and the angle between a line connecting the third peak point and the fourth peak point and a tooth midline of the three-dimensional tooth model is greater than an angle threshold.

18. The manufacturing method according to claim 15, characterized in that: The step of performing tooth segmentation processing on the target tooth model comprises: Acquire a two-dimensional projection image of the three-dimensional tooth model, and identify the two-dimensional projection image to obtain multiple tooth regions; In the three-dimensional tooth model, confirming original seed points corresponding to the plurality of tooth regions; Expanding the original seed point within a preset range to obtain a target seed point of the tooth in the three-dimensional tooth model; The three-dimensional tooth model is segmented based on the target seed point of each tooth to obtain segmented teeth.

19. The manufacturing method according to claim 18, characterized in that: The step of expanding the original seed points within a preset range to obtain target seed points of teeth in the three-dimensional tooth model includes: Expanding the original seed point according to the initial curvature threshold to obtain a first seed point; The first seed point is expanded according to a target curvature threshold to obtain the target seed point, wherein the target curvature threshold is obtained according to the initial curvature threshold.

20. The manufacturing method according to claim 19, characterized in that: The step of expanding the original seed point according to the initial curvature threshold to obtain the first seed point includes: Taking a seed point adjacent to the original seed point as a current seed point; When the curvature of the current seed point is less than or equal to the initial curvature threshold, taking the current seed point and the original seed point as the first seed point; The step of expanding the first seed point according to the target curvature threshold to obtain the target seed point includes: Taking a seed point adjacent to the first seed point as the current seed point; When the curvature of the current seed point is less than or equal to the target curvature threshold, the first seed point and the current seed point are used as the target seed point.

21. The method according to claim 19, characterized in that: Before the step of expanding the first seed point according to the target curvature threshold to obtain the target seed point, the method further includes: The sum of the initial curvature threshold and a preset value is used as the target curvature threshold, wherein the preset value is a positive number; After the step of expanding the original seed point according to the initial curvature threshold to obtain the first seed point, or expanding the first seed point according to the target curvature threshold to obtain the target seed point, the method further includes: If the corresponding point of the first seed point on the two-dimensional projection image does not fall into the corresponding tooth area, adjusting the first seed point to a non-first seed point; or When the corresponding point of the target seed point on the two-dimensional projection image does not fall into the corresponding tooth area, adjusting the target seed point to a non-target seed point; After the original seed points are expanded according to the curvature threshold to obtain the target seed points, and before the step of segmenting the three-dimensional tooth model based on the target seed points of each tooth to obtain the segmented teeth, the method further includes: The target area is obtained by enlarging the plurality of tooth areas; In the target area, the target seed point is expanded according to an initial curvature threshold and a height.

22. The manufacturing method according to claim 15, characterized in that: Also includes: Performing a forming operation based on the tooth model to be formed to obtain a solid tooth model; Performing a film pressing process on the physical dental model to obtain a shell-shaped film sheet covering the physical dental model; The shell-shaped membrane is subjected to a marking operation to obtain the initial device with a marking.

23. An electronic device, characterized in that: It includes a memory, a processor, a communication interface and a communication bus, the memory stores a computer program executable by the processor, the memory and the processor communicate through the communication bus and the communication interface, and the processor implements the method described in any one of claims 1-12 or 13-22 when executing the computer program.

24. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method described in any one of claims 1 to 12 or 13 to 22 is executed.

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