A method for generating denture crown surfaces based on topological reconstruction

Abstract

The present application relates to the technical field of image data processing, and in particular to a method for generating a denture crown surface based on topological reconstruction. The method comprises: obtaining point cloud data of the target user's teeth at the target missing tooth location, and performing triangulation processing on the point cloud data to obtain an initial triangular mesh model; determining a first evaluation value of the vertices formed by the triangles in the initial triangular mesh model; determining the weights of the vertices of the triangle pair according to the first evaluation value of the vertices of the co-edge triangle pair in the initial triangular mesh model; performing surface subdivision processing on the triangle pair in the initial triangular mesh model according to the weights of the four vertices included in the triangle pair to obtain a target triangular mesh model; generating a denture crown according to the target triangular mesh model when the target parameter value of the target triangular mesh model meets the preset conditions. The above technical solution can improve the service life of the generated denture crown.

Description

Technical Field

[0001] The present application relates to the technical field of image data processing, and in particular to a method for generating a denture crown surface based on topological reconstruction. Background Art

[0002] Denture crowns are also known as false tooth crowns, artificial crowns or braces. They are often used to replace defective or missing teeth so that oral users can chew through the installed denture crowns to restore the normal function of the teeth; or, through the installed denture crowns, the user's tooth shape is more beautiful.

[0003] In order to provide users with a more comfortable denture crown experience, the shape of the denture crown can be adaptively designed before installation. In the relevant technology, for example, in the Chinese patent application document with publication number CN111568592A, a digital model intelligent design method for an oral digital impression instrument is provided, including: storing candidate crown data, the stored candidate crown data information includes tooth number, crown type, crown overall size feature vector and tooth storage path; using an oral digital acquisition device to collect three-dimensional model data of the oral cavity after tooth preparation, the data collected by the oral digital acquisition device includes the upper jaw and the lower jaw, and confirming the occlusal relationship between the upper and lower jaws; marking the oral three-dimensional model, marking the abutment tooth position, crown type, and abutment tooth edge line; automatically designing the teeth to be manufactured based on the three-dimensional model obtained after preprocessing, and matching several candidate crowns from the database based on the data information of the designed teeth to be manufactured; determining the similarity between the candidate crowns and the teeth to be manufactured; and adjusting according to the overall size feature vector of the teeth to be manufactured, the tooth surface feature vector and the scaling ratio of the candidate crowns.

[0004] In the related art, several candidate crowns are matched from a database, and the scaling ratio of the candidate crowns is adjusted according to the overall size of the tooth to be manufactured. However, the denture crown obtained after scaling the candidate crowns may be difficult to adapt to the actual situation of the user, which threatens the life of the denture crown or the original tooth, affecting the service life of the denture crown. Summary of the invention

[0005] In order to overcome the problem that the denture crown generated in the related art may affect the lifespan of the denture crown or the user's original teeth, the present application provides a denture crown surface generation method based on topological reconstruction, including: obtaining point cloud data of the target user's teeth at the target missing tooth position, and triangulating the point cloud data to obtain an initial triangular mesh model; for the vertices formed by the triangles in the initial triangular mesh model, determining a first evaluation value of the vertex, the first evaluation value is used to characterize the sharpness of the vertex; for the triangle pairs with common edges in the initial triangular mesh model, determining the weights of the vertices of the triangle pair according to the first evaluation values ​​of the vertices of the triangle pair; performing surface subdivision processing on the triangle pairs in the initial triangular mesh model according to the weights of the four vertices included in the triangle pair to obtain a target triangular mesh model; and generating a denture crown according to the target triangular mesh model when the target parameter value of the target triangular mesh model meets preset conditions.

[0006] In this way, the point cloud data of the user's teeth at the target missing tooth position is triangulated to obtain an initial triangular mesh model, and the co-occurring triangle pairs in the initial triangular mesh model are subjected to curve subdivision processing, and a denture crown is generated based on the obtained target triangular mesh model; since the initial triangular mesh model is obtained based on the point cloud data of the user's teeth at the target missing tooth position, the obtained denture crown can better match the actual situation of the user's missing tooth position, avoiding extrusion between the denture crowns or between the denture crowns and the original teeth, which can increase the service life of the denture crowns and the service life of the original teeth adjacent to the denture crowns.

[0007] At the same time, since the target triangular mesh model used when generating the denture crown is obtained by surface subdivision of co-occurring triangle pairs, the vertices in the obtained target triangular network model can be smoother, which can avoid excessive concentration of force on the denture crown when worn. Therefore, the user can have a better wearing experience when wearing the denture crown.

[0008] Furthermore, the surface subdivision processing of co-occurring triangle pairs is performed based on the evaluation values ​​of the vertices of the triangle pairs. The first evaluation value is used to characterize the sharpness of the vertices. Compared with directly using more refined triangles for surface reconstruction, it can reduce the amount of calculation required for surface reconstruction while ensuring the effect of surface reconstruction, thereby reducing the operating power consumption of the device.

[0009] Optionally, determining the first evaluation value of the vertex includes: for a target triangle intersecting the vertex, determining a second evaluation value of the target triangle according to a side length of the target triangle, the second evaluation value being used to characterize the degree of difference between the target triangle and the regular triangle; the first evaluation value of the vertex satisfies the following formula: , R is the first evaluation value of the vertex, n is the number of triangles intersecting the vertex, k is a positive integer less than or equal to n, t k is the second evaluation value of the kth triangle intersecting the vertex, is the target angle between the normal vector corresponding to the kth triangle intersecting the vertex and the target vector, the target vector is the sum of the multiple normal vectors corresponding to the multiple triangles intersecting the vertex, and M is the first sum of the multiple target angles corresponding to the multiple triangles intersecting the vertex.

[0010] In this way, the first evaluation value of the target vertex in the initial triangular mesh model is determined based on the angles between different triangles corresponding to the vertex. The greater the difference in angles between different triangles corresponding to the target vertex, the more likely the target vertex is to be a sharp vertex. Therefore, the first evaluation value can better characterize the sharpness of the vertex.

[0011] Optionally, determining the second evaluation value of the target triangle according to the side length of the target triangle includes: , where t is the second evaluation value of the target triangle, a1 is the maximum side length in the target triangle, a2 is the minimum side length in the target triangle, L is the distance between the center of the circumscribed circle of the target triangle and the center of gravity of the target triangle, and P is the radius of the circumscribed circle of the target triangle.

[0012] In this way, the difference between the target triangle and the regular triangle can be better characterized by the length relationship between the sides of the target triangle and the distance between the center of the circumscribed circle of the target triangle and the center of gravity of the target triangle.

[0013] Optionally, determining the weights of the vertices of the triangle pair based on the first evaluation values ​​of the vertices of the triangle pair includes: determining a second sum of the first evaluation values ​​of multiple vertices of the triangle pair; and taking a ratio of the first evaluation value of the vertices of the triangle pair to the second sum as the weights of the vertices of the triangle pair.

[0014] In this way, higher weights can be set for vertices with higher evaluation values ​​to better avoid sharp vertices in the triangular mesh model.

[0015] Optionally, performing surface subdivision processing on the triangle pairs in the initial triangular mesh model according to the weights of the four vertices included in the triangle pairs, including: generating new vertices for the triangle pairs according to the weights of the four vertices included in the triangle pairs, and performing surface subdivision processing on the triangle pairs in the initial triangular mesh model according to the generated new vertices and the four vertices included in the triangle pairs; wherein the coordinates of the generated new vertices , D2 is the coordinate of the first endpoint of the common side of the triangle pair, D4 is the coordinate of the second endpoint of the common side of the triangle pair, R2 is the first evaluation value of the first endpoint, R4 is the first evaluation value of the second endpoint, S f is the weight of the fth vertex in the triangle pair, are the coordinates of the fth vertex in the triangle pair.

[0016] In this way, since new vertices are generated for the triangle pair according to the weights of the four vertices included in the triangle pair, the weights of the vertices are determined according to the first evaluation value of the vertex, and the first evaluation value can characterize the sharpness of the vertex; compared to generating new vertices only according to the positions of the four vertices in the triangle pair, since the weights of sharper vertices are higher, the generated new vertices can be made closer, which can not only reduce the sharp vertices existing in the triangular mesh model, but also effectively make the obtained triangular mesh model reflect the original features in the point cloud data.

[0017] Optionally, the point cloud data of the target user's teeth at the target missing tooth location is acquired in the following manner: acquiring first point cloud data of a first tooth of the target user, and acquiring second point cloud data of a second tooth, wherein the first tooth is a tooth located on one side of the target missing tooth location, and the second tooth is a tooth located on the other side of the target missing tooth location; generating point cloud data of the target user's teeth at the target missing tooth location based on the first point cloud data and the second point cloud data.

[0018] Optionally, the triangulating the point cloud data to obtain an initial triangular mesh model includes: utilizing a Delaunay triangulation algorithm to triangulate the point cloud data to obtain an initial triangular mesh model.

[0019] Optionally, the method also includes: when the target parameter value of the target triangular mesh model does not meet the preset conditions, for a pair of triangles with common edges in the target triangular mesh model, determining the weights of the vertices of the triangle pair according to the first evaluation values ​​of the vertices of the triangle pair; performing surface subdivision processing on the triangle pairs in the target triangular mesh model according to the weights of the four vertices included in the triangle pairs, and re-using the triangular mesh model obtained after the surface subdivision processing as the target triangular mesh model.

[0020] In this way, when the target parameter values ​​of the target triangular mesh model do not meet the preset conditions, further surface division can be performed on the triangle pairs in the triangular mesh model to obtain a more accurate triangular mesh model.

[0021] Optionally, the target parameter value includes the number of target vertices, the target vertex is a vertex having a first evaluation value greater than a preset evaluation threshold, and the target parameter value satisfies a preset condition including: the number of target vertices is less than a first preset number threshold.

[0022] Optionally, the target parameter value includes the total number of triangles, and the target parameter value satisfies a preset condition including: the total number of triangles is greater than a second preset number threshold.

[0023] The technical solution provided by the embodiments of the present application may include the following beneficial effects: triangulating the point cloud data of the user's teeth at the target missing tooth location to obtain an initial triangular mesh model, performing curve subdivision processing on the co-occurring triangle pairs in the initial triangular mesh model, and generating a denture crown based on the obtained target triangular mesh model; since the initial triangular mesh model is obtained based on the point cloud data of the user's teeth at the target missing tooth location, the obtained denture crown can better match the actual situation of the user's missing tooth location, avoiding extrusion between the denture crowns or between the denture crowns and the original teeth, which can increase the service life of the denture crowns, and can increase the service life of the original teeth adjacent to the denture crowns.

[0024] At the same time, since the target triangular mesh model used when generating the denture crown is obtained by surface subdivision of co-occurring triangle pairs, the vertices in the obtained target triangular network model can be smoother, which can avoid excessive concentration of force on the denture crown when worn. Therefore, the user can have a better wearing experience when wearing the denture crown.

[0025] Furthermore, the surface subdivision processing of co-occurring triangle pairs is performed based on the evaluation values ​​of the vertices of the triangle pairs. The first evaluation value is used to characterize the sharpness of the vertices. Compared with directly using more refined triangles for surface reconstruction, it can reduce the amount of calculation required for surface reconstruction while ensuring the effect of surface reconstruction, thereby reducing the operating power consumption of the device.

[0026] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] 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.

[0028] Figure 1 The present invention is a flowchart of a method for generating a denture crown surface based on topological reconstruction according to an exemplary embodiment.

[0029] Figure 2is a schematic diagram showing a triangle centering vertex according to an exemplary embodiment;

[0030] Figure 3 The figure is a schematic diagram showing a surface subdivision processing result of a triangle pair according to an exemplary embodiment. DETAILED DESCRIPTION

[0031] Here, exemplary embodiments are described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application.

[0032] First, the application scenario of the embodiment of the present application is briefly introduced. In the application scenario of the present application, the denture crown can be adaptively designed before installation. In the related art, the preset denture model is scaled to adapt to the patient's dental condition. However, the denture obtained after scaling the preset denture model may still be difficult to adapt to the actual situation of the patient's teeth. For example, the height or width may not be adapted to the patient's missing teeth, so that the denture crown may be squeezed against the patient's original teeth, thereby affecting the service life of the denture crown, or it may also affect the service life of the patient's original teeth.

[0033] In response to the above technical problems, an embodiment of the present application provides a method for generating a denture crown surface based on topological reconstruction, which triangulates the point cloud data of the user's teeth at the target missing tooth location to obtain an initial triangular mesh model, and performs curve subdivision processing on the co-occurring triangle pairs in the initial triangular mesh model, and generates a denture crown based on the obtained target triangular mesh model; since the initial triangular mesh model is obtained based on the point cloud data of the user's teeth at the target missing tooth location, the obtained denture crown can better match the actual situation of the user's missing tooth location, avoiding extrusion between the denture crowns or between the denture crowns and the original teeth, which can increase the service life of the denture crowns, and can increase the service life of the original teeth adjacent to the denture crowns.

[0034] At the same time, since the target triangular mesh model used when generating the denture crown is obtained by surface subdivision of co-occurring triangle pairs, the vertices in the obtained target triangular network model can be smoother, which can avoid excessive concentration of force on the denture crown when worn. Therefore, the user can have a better wearing experience when wearing the denture crown.

[0035] Furthermore, the surface subdivision processing of co-occurring triangle pairs is performed based on the evaluation values ​​of the vertices of the triangle pairs. The first evaluation value is used to characterize the sharpness of the vertices. Compared with directly using more refined triangles for surface reconstruction, it can reduce the amount of calculation required for surface reconstruction while ensuring the effect of surface reconstruction, thereby reducing the operating power consumption of the device.

[0036] Figure 1 is a flowchart of a method for generating a denture crown surface based on topological reconstruction according to an exemplary embodiment, which can be applied to a terminal device such as Figure 1 As shown, the method includes the following steps.

[0037] In step S101, point cloud data of the target user's teeth at the target missing tooth location is obtained, and the point cloud data is triangulated to obtain an initial triangular mesh model.

[0038] Point cloud data is data that can reflect the three-dimensional position of the target object. By obtaining the point cloud data of the target user's teeth at the target missing tooth location, it is helpful to determine the actual situation of the user's teeth at the target missing tooth location, so as to make a matching denture crown based on the actual situation of the user's missing tooth location, thereby improving the user's wearing experience of the denture crown.

[0039] The point cloud data can be obtained by scanning the user's oral cavity with a laser scanner; or, image data can be obtained by optically scanning the user's oral cavity, and the image data can be converted to obtain point cloud data of the user's teeth; or, an MRI (Magnetic Resonance Imaging) image obtained by MRI at the user's oral cavity can be converted to obtain point cloud data of the user's teeth; or, the user's oral cavity can be scanned with an oral scanner to obtain point cloud data of the user's teeth.

[0040] The point cloud data may be triangulated to obtain an initial triangular mesh model, wherein the initial triangular mesh model includes a plurality of adjacent triangles, two adjacent triangles are collinear with each other, and vertices in the initial triangular mesh model may correspond to the plurality of adjacent triangles.

[0041] In one embodiment, the triangulating the point cloud data to obtain an initial triangular mesh model includes: using a Delaunay triangulation algorithm to triangulate the point cloud data to obtain an initial triangular mesh model.

[0042] The Delaunay triangulation algorithm can convert a set of scattered points into a triangular mesh. Commonly used Delaunay triangulation algorithms include the Bowyer-Watson algorithm, the divide-and-conquer algorithm, and the scan line algorithm.

[0043] In this way, by triangulating the point cloud data to obtain the initial triangular mesh model, it is possible to visualize the three-dimensional point cloud data, convert discrete point cloud data into a continuous triangular mesh model, and make it easier to make denture crowns for users based on the obtained triangular mesh model.

[0044] In one embodiment, the point cloud data of the target user's teeth at the target missing tooth location is acquired in the following manner: first point cloud data of a first tooth of the target user is acquired, and second point cloud data of a second tooth is acquired, wherein the first tooth is a tooth located on one side of the target missing tooth location, and the second tooth is a tooth located on the other side of the target missing tooth location; based on the first point cloud data and the second point cloud data, point cloud data of the target user's teeth at the target missing tooth location is generated.

[0045] When only scanning the point cloud data of the missing teeth, the obtained point cloud data may be difficult to accurately describe the actual situation of the missing teeth; for example, due to the defects or lack of teeth in the missing teeth of the mandible, it is difficult to obtain point cloud data of the top surface of the teeth in the mandible.

[0046] If the pre-set tooth model is used to make the denture directly, the made teeth may differ greatly from the user's missing teeth in width or height, which affects the user's experience of using the denture crown.

[0047] In an embodiment of the present application, point cloud data of the teeth on both sides of the missing tooth are collected, and the information of the teeth on both sides of the missing tooth can be used as a reference to determine more accurate point cloud data of the target missing tooth; for example, the point cloud data of the top surfaces of the first tooth and the second tooth can be used as the point cloud data of the top surface of the target missing tooth, so that a complete description of the surface information of the target missing tooth can be achieved through the obtained point cloud data.

[0048] In this way, based on the first point cloud data and the second point cloud data, point cloud data of the target user's teeth at the target missing tooth location is generated. Since the first point cloud data and the second point cloud data are obtained based on the point cloud data of the teeth on both sides of the target missing tooth location, the obtained point cloud data can better describe the information of the target missing tooth location.

[0049] In step S102 , first evaluation values ​​of vertices formed by triangles in the initial triangular mesh model are determined.

[0050] Among them, the first evaluation value is used to characterize the sharpness of the vertex. The larger the first evaluation value is, the sharper the vertex is, and the denture crown made by the initial triangular mesh model is sharper at the vertex, which may cause the force concentration at the vertex of the denture crown and affect the service life of the denture crown. On the contrary, the smaller the first evaluation value is, the less sharp the vertex is, and the denture crown made by the initial triangular mesh model is rounder at the vertex, which can disperse the force of the denture crown at the vertex.

[0051] There may be noisy data points in the point cloud data of the target user's teeth at the target missing tooth location, or there may be missing point cloud data points in the point cloud data, which may result in the presence of sharp vertices in the initial triangular mesh model obtained by three-dimensional segmentation of the point cloud data. Therefore, if the denture crown is made directly based on the initial triangular mesh model, there may be sharp position points in the made denture crown, affecting the user's experience of using the denture.

[0052] In order to avoid the appearance of relatively sharp vertices in the initial three-dimensional mesh model, a first evaluation value of the vertex can be determined. The first evaluation value of the vertex can be determined based on the angle between multiple triangles adjacent to the vertex; for example, the larger the angle between multiple triangles adjacent to the vertex, the more likely the vertex formed by the multiple triangles is to be a sharp vertex.

[0053] In one embodiment, determining the first evaluation value of the vertex includes: for a target triangle intersecting the vertex, determining a second evaluation value of the target triangle according to the side length of the target triangle, the second evaluation value being used to characterize the degree of difference between the target triangle and the regular triangle; the first evaluation value of the vertex satisfies the following formula: , R is the first evaluation value of the vertex, n is the number of triangles intersecting the vertex, k is a positive integer less than or equal to n, t k is the second evaluation value of the kth triangle intersecting the vertex, is the target angle between the normal vector corresponding to the kth triangle intersecting the vertex and the target vector, the target vector is the sum of the multiple normal vectors corresponding to the multiple triangles intersecting the vertex, and M is the first sum of the multiple target angles corresponding to the multiple triangles intersecting the vertex.

[0054] Multiple triangles intersecting the vertex can be determined, different triangles correspond to different target angles, and the angle sizes of multiple target angles of multiple triangles intersecting the vertex are summed to obtain a first sum after summing the angle sizes of the multiple target angles.

[0055] The second evaluation value of the target triangle is determined according to the side length of the target triangle, and the second evaluation value is used to characterize the degree of difference between the target triangle and the equilateral triangle; the larger the second evaluation value, the greater the difference between the target triangle and the equilateral triangle, and the greater the difference between the three angles in the target triangle; the more likely the target triangle corresponds to a sharp vertex.

[0056] For example, multiple triangles adjacent to the same vertex are A1, A2, A3, A4 and A5, and the normal vectors corresponding to triangles A1, A2, A3, A4 and A5 can be determined respectively. For example, triangle A1 corresponds to normal vector B1, triangle A2 corresponds to normal vector B2, triangle A3 corresponds to normal vector B3, triangle A4 corresponds to normal vector B4, and triangle A5 corresponds to normal vector B5; among which, the process of determining the normal vector corresponding to the plane will not be repeated in the embodiments of the present application.

[0057] Perform vector addition operation on the normal vectors B1, B2, B3, B4 and B5 to obtain the target vector after the addition operation. The target vector can reflect the overall direction of multiple vectors corresponding to multiple triangles; the angle between the normal vector of the triangle and the target vector can reflect the degree of difference between the direction of the triangle and the directions of other triangles corresponding to the same vertex.

[0058] In this way, the first evaluation value of the target vertex in the initial triangular mesh model is determined based on the angles between different triangles corresponding to the vertex. The greater the difference in angles between different triangles corresponding to the target vertex, the more likely the target vertex is to be a sharp vertex. Therefore, the first evaluation value can better characterize the sharpness of the vertex.

[0059] In one embodiment, determining the second evaluation value of the target triangle according to the side length of the target triangle includes: , where t is the second evaluation value of the target triangle, a1 is the maximum side length in the target triangle, a2 is the minimum side length in the target triangle, L is the distance between the center of the circumscribed circle of the target triangle and the center of gravity of the target triangle, and P is the radius of the circumscribed circle of the target triangle.

[0060] In this way, the difference between the target triangle and the regular triangle can be better characterized by the length relationship between the sides of the target triangle and the distance between the center of the circumscribed circle of the target triangle and the center of gravity of the target triangle.

[0061] In step S103, for a pair of triangles with a common edge in the initial triangular mesh model, weights of the vertices of the pair of triangles are determined according to first evaluation values ​​of the vertices of the pair of triangles.

[0062] Adjacent triangles in a triangular mesh model have common edges. Two adjacent triangles can form a triangle pair, and the triangle pair includes four vertices in total; the four vertices include the two endpoints of the common edge of the two triangles in the triangle pair, and two other vertices except the two endpoints of the common edge.

[0063] In one embodiment, determining the weights of the vertices of a triangle pair based on the first evaluation values ​​of the vertices of the triangle pair includes: determining the second sum of the first evaluation values ​​of multiple vertices of the triangle pair; and using the ratio of the first evaluation value of the vertices of the triangle pair to the second sum as the weights of the vertices of the triangle pair.

[0064] For example, the same triangle pair may include four vertices, each of which has a corresponding first evaluation value. By summing the four first evaluation values ​​corresponding to the four vertices, a second sum obtained by summing the four first evaluation values ​​can be obtained.

[0065] In this way, higher weights can be set for vertices with higher evaluation values ​​to better avoid sharp vertices in the triangular mesh model.

[0066] In step S104, the triangle pairs in the initial triangle mesh model are subjected to surface subdivision processing according to the weights of the four vertices included in the triangle pairs to obtain a target triangle mesh model.

[0067] In the triangulated mesh model, the smaller the size of the triangles used in the triangulation process, the better the triangulation effect on the point cloud data; however, as the size of the triangles used decreases, the number of triangles required for triangulation will gradually increase, resulting in an increase in the amount of calculation required for triangulation; on the contrary, the larger the size of the triangles used in the triangulation process, the fewer triangles are required for triangulation, and the amount of calculation required will also be reduced accordingly, but the effect of triangulation on the point cloud data will decrease.

[0068] Therefore, by performing surface subdivision processing on the triangle pairs in the initial triangular mesh model according to the weights of the four vertices included in the triangle pairs, compared with using all smaller-sized triangles to construct the triangular mesh model, the number of triangles required for constructing the triangular mesh model can be reduced, and the amount of calculation required by the terminal device can be reduced; and compared with using all larger-sized triangles to construct the triangular mesh model, a more refined triangular mesh model can be obtained, thereby achieving a better fit for the user's missing teeth.

[0069] For example, the Loop subdivision algorithm can be used to perform surface subdivision processing on the triangle pairs in the initial triangular mesh model, generate new vertices based on the original triangle pairs, and thus generate more triangles with the new vertices as corner points, thereby constructing a more refined triangular mesh model.

[0070] In one embodiment, the surface subdivision processing is performed on the triangle pairs in the initial triangular mesh model according to the weights of the four vertices included in the triangle pairs, including: generating new vertices for the triangle pairs according to the weights of the four vertices included in the triangle pairs, and performing surface subdivision processing on the triangle pairs in the initial triangular mesh model according to the generated new vertices and the four vertices included in the triangle pairs; wherein the coordinates of the generated new vertices are , D2 is the coordinate of the first endpoint of the common side of the triangle pair, D4 is the coordinate of the second endpoint of the common side of the triangle pair, R2 is the first evaluation value of the first endpoint, R4 is the first evaluation value of the second endpoint, S f is the weight of the fth vertex in the triangle pair, are the coordinates of the fth vertex in the triangle pair.

[0071] For example, the horizontal coordinates of the four vertices in the triangle pair can be substituted into the calculation formula of W to obtain the horizontal coordinate of the newly generated vertex; referring to the process of obtaining the horizontal coordinate of the newly generated vertex, the vertical coordinate of the newly generated vertex in the three-dimensional space can be obtained to obtain the various components of the coordinates of the new vertex in the three-dimensional space.

[0072] Figure 2 Schematic diagram of the vertices of the triangle in the embodiment of the present application, such as Figure 2 As shown, the triangle pair includes four vertices, namely vertex 1, vertex 2, vertex 3 and vertex 4, wherein vertex 2 and vertex 4 are the two end points of the common edge of the two triangles in the triangle pair respectively; vertex 5 is a new vertex generated in the embodiment of the present application, and vertex 5 can be located on the line between vertex 2 and vertex 4, and vertex 5 can also be located outside the line between vertex 2 and vertex 4.

[0073] In this way, since new vertices are generated for the triangle pair according to the weights of the four vertices included in the triangle pair, the weights of the vertices are determined according to the first evaluation value of the vertex, and the first evaluation value can characterize the sharpness of the vertex; compared to generating new vertices only according to the positions of the four vertices in the triangle pair, since the weights of sharper vertices are higher, the generated new vertices can be made closer, which can not only reduce the sharp vertices existing in the triangular mesh model, but also effectively make the obtained triangular mesh model reflect the original features in the point cloud data.

[0074] According to the generated new vertices, the triangle pairs in the initial triangular mesh model can be tessellated. Figure 3 is a schematic diagram of the result of surface subdivision processing on a triangle pair; Figure 3 As shown, vertex 6 is the midpoint of the line formed by vertex 1 and vertex 2, vertex 7 is the midpoint of the line formed by vertex 1 and vertex 4, vertex 8 is the midpoint of the line formed by vertex 2 and vertex 3, and vertex 9 is the midpoint of the line formed by vertex 3 and vertex 4. By generating the new vertex 5, the original triangle pair can be re-divided.

[0075] Since the original triangle pair is re-divided, the triangle corresponding to vertex 2 has changed, and the triangle corresponding to vertex 4 has changed. Therefore, the sharpness of vertex 2 and vertex 4 will change, which can avoid sharp vertices in the obtained triangular mesh model while retaining the original characteristics of the point cloud data.

[0076] In step S105, when the target parameter values ​​of the target triangular mesh model meet the preset conditions, a denture crown is generated according to the target triangular mesh model.

[0077] After surface division of the triangle pairs in the initial triangular mesh model, the triangular mesh model will be more refined. In order to take into account the accuracy of the triangular mesh model and the operating power consumption of the terminal device, the further division of the triangle pairs in the initial triangular mesh model can be stopped when the target parameter value of the target triangular mesh model meets the preset conditions to generate a denture crown based on the triangular mesh model.

[0078] For example, the three-dimensional data of the target triangular mesh model can be sent to a denture crown manufacturing device, so that the denture crown manufacturing device manufactures the denture crown according to the three-dimensional data. Compared with the point cloud data obtained by direct scanning, since the three-dimensional data is the processed target triangular mesh model, it can avoid the sharp parts caused by directly manufacturing the denture crown according to the point cloud data, and can retain the characteristics of the target user's missing teeth, thereby improving the user experience of the denture crown and increasing the service life of the denture crown.

[0079] By using the denture crown surface generation method based on topological reconstruction provided in the embodiment of the present application, the point cloud data of the user's teeth at the target missing tooth position is triangulated to obtain an initial triangular mesh model, and the co-occurring triangle pairs in the initial triangular mesh model are subjected to curve subdivision processing, and the denture crown is generated according to the obtained target triangular mesh model; since the initial triangular mesh model is obtained based on the point cloud data of the user's teeth at the target missing tooth position, the obtained denture crown can better match the actual situation of the user's missing tooth position, avoiding extrusion between the denture crowns or between the denture crowns and the original teeth, which can increase the service life of the denture crowns, and can increase the service life of the original teeth adjacent to the denture crowns.

[0080] At the same time, since the target triangular mesh model used when generating the denture crown is obtained by surface subdivision of co-occurring triangle pairs, the vertices in the obtained target triangular network model can be smoother, which can avoid excessive concentration of force on the denture crown when worn. Therefore, the user can have a better wearing experience when wearing the denture crown.

[0081] Furthermore, the surface subdivision processing of co-occurring triangle pairs is performed based on the evaluation values ​​of the vertices of the triangle pairs. The first evaluation value is used to characterize the sharpness of the vertices. Compared with directly using more refined triangles for surface reconstruction, it can reduce the amount of calculation required for surface reconstruction while ensuring the effect of surface reconstruction, thereby reducing the operating power consumption of the device.

[0082] In one embodiment, the target parameter value includes the number of target vertices, the target vertex is a vertex whose first evaluation value is greater than a preset evaluation threshold, and the target parameter value satisfies a preset condition including: the number of target vertices is less than a first preset number threshold.

[0083] When the number of target vertices is less than the first preset number threshold, since the target vertex is a vertex with a first evaluation value less than the preset evaluation threshold, the first evaluation value is used to characterize the sharpness of the vertex, indicating that the number of sharp vertices in the triangular mesh model is already small, and the triangular mesh model can be used to produce a denture crown that meets the requirements.

[0084] Among them, the preset evaluation threshold can be set according to actual needs. For example, when the numerical range of the first evaluation value is between 0 and 1, the preset evaluation threshold can be between 0.6 and 0.8; the first preset quantity threshold can be determined according to the surface area of ​​the tooth, or the value of the first preset quantity threshold can be pre-set. The first preset quantity threshold can be, for example, between 5 and 10.

[0085] In one embodiment, the target parameter value includes the total number of triangles, and the target parameter value satisfies a preset condition including: the total number of triangles is greater than a second preset number threshold.

[0086] In this way, when the total number of triangles in the triangular mesh model is greater than the second preset number threshold, it means that after surface division of the triangle pairs in the initial triangular mesh model, the accuracy of the triangular mesh model has probably met the requirements, which helps to reduce the amount of calculation of the terminal device while ensuring the accuracy of the obtained triangular mesh model.

[0087] The second preset quantity threshold can be determined based on the surface area of ​​the denture crown and the target accuracy parameter. For example, the target accuracy parameter can be the area of ​​the triangle for triangulation. The second preset quantity threshold can be determined based on the ratio of the surface area of ​​the denture crown to the area of ​​the triangle for triangulation.

[0088] In one embodiment, when the target parameter value of the target triangular mesh model does not meet the preset conditions, the weights of the vertices of the triangle pair with common edges in the target triangular mesh model can be determined according to the first evaluation values ​​of the vertices of the triangle pair; the triangle pairs in the target triangular mesh model are subjected to surface tessellation processing according to the weights of the four vertices included in the triangle pair, and the triangular mesh model obtained after the surface tessellation processing is used again as the target triangular mesh model.

[0089] In this way, when the target parameter values ​​of the target triangular mesh model do not meet the preset conditions, further surface division can be performed on the triangle pairs in the triangular mesh model to obtain a more accurate triangular mesh model.

[0090] It should be understood that the features of some embodiments of the various applications described herein may be combined with each other, unless specifically stated otherwise.

[0091] Although terms such as "first", "second", and "third" may be used herein to describe various components, parts, regions, layers, or sections, these components, parts, regions, layers, or sections are not limited to these terms. Instead, these terms are only used to distinguish one component, part, region, layer, or section from another component, part, region, layer, or section. Therefore, without departing from the teachings of the examples described herein, the first component, part, region, layer, or section mentioned in the examples may also be referred to as the second component, part, region, layer, or section.

[0092] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description herein, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0093] In addition, the word "exemplary" is used herein to mean serving as an example, instance, or diagram. Any aspect or design described herein as "exemplary" is not necessarily to be understood as being advantageous over other aspects or designs. Instead, the use of the word exemplary is intended to present concepts in a concrete manner. As used herein, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or".

[0094] Likewise, although the present application has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. With particular regard to the various functions performed by the components (e.g., elements, resources, etc.) described above, unless otherwise noted, the terms used to describe such components are intended to correspond to any component (functionally equivalent) that performs the specific functions of the described components, even if not structurally equivalent to the disclosed structures.

[0095] Additionally, while particular features of the present application may have been disclosed with respect to only one of several implementations, such features may be combined with one or more other features of other implementations as may be desired and advantageous for any given or particular application.

[0096] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary technical means in the art that are not disclosed in the present application, and the specification and embodiments are only considered as exemplary.

[0097] It should be understood that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A method for generating denture crown surfaces based on topological reconstruction, characterized in that: include: Obtaining point cloud data of the target user's teeth at the target missing tooth location, and performing triangulation processing on the point cloud data to obtain an initial triangular mesh model; For the vertices formed by the triangles in the initial triangular mesh model, the first evaluation value of the vertex is determined, including: for the target triangle intersecting with the vertex, the second evaluation value of the target triangle is determined according to the side length of the target triangle, and the second evaluation value represents the degree of difference between the target triangle and the regular triangle; the first evaluation value of the vertex satisfies the following formula: , R is the first evaluation value of the vertex, n is the number of triangles intersecting the vertex, k is a positive integer less than or equal to n, t k is the second evaluation value of the kth triangle intersecting the vertex, is the target angle between the normal vector corresponding to the kth triangle intersecting the vertex and the target vector, the target vector is the vector sum of multiple normal vectors corresponding to multiple triangles intersecting the vertex, and M is the first sum of multiple target angles corresponding to multiple triangles intersecting the vertex; the first evaluation value represents the sharpness of the vertex; For a pair of triangles with a common edge in the initial triangular mesh model, weights of the vertices of the pair of triangles are determined according to first evaluation values ​​of the vertices of the pair of triangles; Performing surface subdivision processing on the triangle pairs in the initial triangle mesh model according to the weights of the four vertices included in the triangle pairs to obtain a target triangle mesh model; When the target parameter values ​​of the target triangular mesh model meet the preset conditions, a denture crown is generated according to the target triangular mesh model.

2. The method for generating denture crown surfaces based on topological reconstruction according to claim 1, characterized in that: Determining a second evaluation value of the target triangle according to the side length of the target triangle includes: , where t is the second evaluation value of the target triangle, a1 is the maximum side length in the target triangle, a2 is the minimum side length in the target triangle, L is the distance between the center of the circumscribed circle of the target triangle and the center of gravity of the target triangle, and P is the radius of the circumscribed circle of the target triangle.

3. The method for generating denture crown surfaces based on topological reconstruction according to claim 1, characterized in that: The step of determining the weights of the vertices of the triangle pair according to the first evaluation values ​​of the vertices of the triangle pair comprises: Determining a second sum of the first evaluation values ​​of the plurality of vertices of the triangle pair; The ratio of the first evaluation value of the vertices of the triangle pair to the second sum is used as the weight of the vertices of the triangle pair.

4. The method for generating denture crown surfaces based on topological reconstruction according to claim 1, characterized in that: According to the weights of the four vertices included in the triangle pair, the triangle pair in the initial triangle mesh model is subjected to surface subdivision processing, including: Generate new vertices for the triangle pair according to the weights of the four vertices included in the triangle pair, and perform surface subdivision processing on the triangle pair in the initial triangular mesh model according to the generated new vertices and the four vertices included in the triangle pair; Among them, the coordinates of the new vertex generated , D2 is the coordinate of the first endpoint of the common side of the triangle pair, D4 is the coordinate of the second endpoint of the common side of the triangle pair, R2 is the first evaluation value of the first endpoint, R4 is the first evaluation value of the second endpoint, S f is the weight of the fth vertex in the triangle pair, are the coordinates of the fth vertex in the triangle pair.

5. The method for generating denture crown surfaces based on topological reconstruction according to claim 1, characterized in that: The point cloud data of the target user's teeth at the target missing tooth position is obtained in the following manner: Acquire first point cloud data of a first tooth of a target user, and acquire second point cloud data of a second tooth, wherein the first tooth is a tooth located on one side of the target missing tooth location, and the second tooth is a tooth located on the other side of the target missing tooth location; Point cloud data of the target user's teeth at the target missing tooth location are generated according to the first point cloud data and the second point cloud data.

6. The method for generating denture crown surfaces based on topological reconstruction according to claim 1, characterized in that: The triangulation process of the point cloud data to obtain the initial triangulated mesh model includes: using a Delaunay triangulation algorithm to triangulate the point cloud data to obtain the initial triangulated mesh model.

7. The method for generating denture crown surfaces based on topological reconstruction according to claim 1, characterized in that: The method further comprises: When the target parameter value of the target triangular mesh model does not satisfy the preset condition, for a triangle pair with a common edge in the target triangular mesh model, determining the weights of the vertices of the triangle pair according to the first evaluation values ​​of the vertices of the triangle pair; According to the weights of the four vertices included in the triangle pair, the triangle pair in the target triangle mesh model is subjected to surface subdivision processing, and the triangle mesh model obtained after the surface subdivision processing is used again as the target triangle mesh model.

8. The method for generating denture crown surface based on topological reconstruction according to any one of claims 1 to 7, characterized in that: The target parameter value includes the number of target vertices, the target vertices are vertices whose first evaluation value is greater than a preset evaluation threshold, and the target parameter value satisfies a preset condition including: the number of target vertices is less than a first preset number threshold.

9. The method for generating denture crown surface based on topological reconstruction according to any one of claims 1 to 7, characterized in that: The target parameter value includes the total number of triangles, and the target parameter value satisfies a preset condition including: the total number of triangles is greater than a second preset number threshold.

Images