Digital production method and system for artificial gingiva of dental implant bridge

Abstract

The invention relates to the technical field of dental restoration, in particular to a digital production method and system for an artificial gingiva of a dental implant bridge, and the method comprises the steps: obtaining the slope difference of an occlusion section, dividing a contour region, setting segmented filling parameters, constructing a normal track, generating a central path, building an outer contour curved surface, and fusing filling data to generate a complete artificial gingiva model. According to the method, the slope difference value of the section point positions of the occlusal surface is calculated, so that the change state of the contour region is accurately recognized, the spatial analysis capability of the section data is improved, and the structural feature extraction is more refined. And filling parameters are respectively set for different contour areas by adopting a linear fitting mode, so that the partition regulation and control capability of the filling structure is effectively enhanced, and the height of a space filling level is more matched with the bionic requirement of gingiva. The continuous path is constructed by means of the direction vector of the contact surface of the adjacent dental prosthesis, so that the natural space transition between the gingival structure and the bridge structure is ensured, and the problems of path breakage and distortion in the manual design process are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of dental restoration, and in particular to a digital production method and system for artificial gums of a dental implant bridge. Background Art

[0002] The field of dental restoration technology encompasses methods and processes for functional and aesthetic reconstruction of missing teeth. Its core content covers multiple aspects, including implant placement, denture fabrication, and oral tissue simulation. This field systematically involves the acquisition and analysis of oral anatomical data, implant design and placement techniques, the mechanical configuration of bridges and prostheses, and the simulation and restoration of periodontal soft tissue.

[0003] Among them, the digital production method of artificial gums for dental implant bridges refers to the method of designing and processing the structure used to simulate the gum part in dental implant bridges using digital modeling and molding technology. This method mainly focuses on the morphological acquisition, data conversion, modeling design and physical molding of artificial gums.

[0004] In existing technologies, artificial gingival structures are often modeled based on empirical rules, lacking quantitative identification of cross-sectional contour variation trends. This leads to ambiguity in contour data during regional demarcation, making it difficult to achieve hierarchical precision control during the subsequent filling process. Without vector analysis of the contact surface directions of adjacent teeth, bridge segment path construction often relies on manual stretching or baseline capture, which can easily lead to directional discontinuities in the spatial connection curves and increase the risk of structural distortion during gingival modeling. External contour construction often uses discrete point connections, ignoring changes in the normal direction of path nodes. This results in abrupt nodes in the generated surface, which not only affects the smoothness of the molding process but also reduces the adaptability of the structure. During the geometric structure merging process, the fusion range is determined solely based on coordinate overlap, lacking identification of the boundary normal direction and the spatial intersection. This can easily lead to fractured edges at the model joints, seriously compromising structural integrity. During the physical molding stage, the spatial positioning relationship between the three-dimensional model and the actual bridge structure is not considered, resulting in gaps or misalignment in the gingival structure after installation, affecting the stability of the restoration. This operating mode not only reduces the realism and molding efficiency of the artificial gingival but also limits the practical operability of the digital process. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a digital production method and system for artificial gums of a dental implant bridge.

[0006] In order to achieve the above-mentioned object, the present invention adopts the following technical solution: a digital production method of artificial gingiva for dental implant bridge, comprising the following steps:

[0007] S1: Obtain the cross-sectional data of the bridge occlusal surface, calculate the slope difference of each cross-sectional point, and divide the contour into a variable section and a stable section according to the difference;

[0008] S2: setting parameters of the gum filling surface level for the contour changing section and the contour stable section respectively by piecewise linear fitting method, and outputting contour control filling data;

[0009] S3: The normal trajectory of the adjacent tooth restoration contact surface for bridge artificial gingiva modeling is constructed, and each normal vector in the constructed normal trajectory is continuously connected to obtain the bridge segment center guide path;

[0010] S4: inputting the bridge segment center guide path into CAD to perform artificial gingival space contour modeling to obtain the gingival space outer contour surface;

[0011] S5: geometrically merging the contour control filling data with the outer contour surface of the gingival space in CAD to generate a complete artificial gingival structure model.

[0012] As a further solution of the present invention, the contour change section and the contour stable section are specifically the slope absolute difference range, the contour change state mark, and the curve point coordinate set. The contour control filling data includes the filling level Z value, the area classification label, and the transition surface node sequence. The bridge segment center guide path includes the path point spatial position, the path segment normal direction, and the path segment sequence identifier. The gingival space outer contour surface includes the contour cross-sectional shape, the contour space coordinates, and the contour connection sequence. The artificial gingival structure model includes the bridge connection area, the occlusal filling area, and the gingival extension boundary.

[0013] As a further solution of the present invention, the steps for obtaining the contour change section and the contour stable section are specifically as follows:

[0014] S111: Acquire three-dimensional structural data of the bridge frame occlusal area, extract cross-sectional curve information corresponding to the occlusal surface, collect z-axis coordinate values ​​of points arranged in sequence on the cross section, calculate the z-axis slope value between each pair of adjacent points based on the order of the points, and generate a cross-sectional point slope value sequence;

[0015] S112: calculating the slope variation of each point in the cross-section slope value sequence, identifying the fluctuation trend in the slope variation sequence by local extreme value detection, marking the change state of each curve segment, and generating curve slope variation identification data;

[0016] S113: Based on the curve slope change identification data, the curve segments in each section whose continuous change amount is greater than the set slope change threshold are divided into contour change segments, and the curve segments whose continuous change amount is less than the slope change threshold are divided into contour stable segments.

[0017] As a further solution of the present invention, the step of acquiring the contour control filling data is specifically as follows:

[0018] S211: Calling the z-axis coordinates of the points in the contour changing section and the contour stable section and the area categories to which they belong, setting a fixed value lifting height for the contour changing section, setting a proportional coefficient for the contour stable section to adjust the compression height, and calculating the corresponding partition filling level Z values ​​respectively;

[0019] S212: Identify adjacent connected areas between the contour changing segment and the contour stable segment, calculate the distance between the Z-axis coordinates in the connected areas, perform linear interpolation on the distance range, construct a transition filling Z value sequence between the two intervals, and generate a transition filling Z value for the junction segment;

[0020] S213: Combining the partition filling level Z value and the junction section transition filling Z value, arranging the Z values ​​in order of point coordinates to construct a complete filling level structure, and marking the area type and level height of each point to generate contour control filling data.

[0021] As a further solution of the present invention, the steps of obtaining the guiding path of the center of the bridge section are specifically as follows:

[0022] S311: Acquire the contact surface area of ​​the adjacent tooth restorations at both ends of the bridge structure, select a specified number of spatial sampling points within the middle range of the contact surface, construct a cutting plane for each sampling point using CAD, extract the normal direction vector information of the plane, and generate a normal vector set of the adjacent tooth contact surface;

[0023] S312: Positioning and sorting each normal vector in the set of normal vectors of the adjacent tooth contact surfaces according to the angle between each vector and the longitudinal axis of the bridge frame in spatial position order, recording the spatial position coordinates and direction information, and generating ordered direction data of the normal vector;

[0024] S313: Based on the direction change trend and spatial coordinate information recorded in the ordered direction data of the normal vector, the Frenet-Serret path generation method is called to perform continuous curve fitting on the ordered vector, a center guide trajectory for artificial gingival modeling in the bridge area is constructed, and a center guide path of the bridge segment is generated.

[0025] As a further solution of the present invention, the steps for obtaining the outer contour surface of the gingival space are specifically as follows:

[0026] S411: Inputting the spatial coordinate information of the path points of the bridge section center guide path data into the CAD, determining the corresponding normal direction at each node of the path, locating the cross section according to the normal direction to construct a reference plane, and generating path node normal positioning information;

[0027] S412: Constructing a standard elliptical or eccentric wheel cross-sectional structure on each reference plane according to the normal positioning information of the path nodes, establishing contour geometry in sequence according to the node sequence, recording the contour morphological parameters and spatial position of each cross section, and generating a node cross-sectional contour structure;

[0028] S413: performing surface connection operations on the node cross-section contour structure in CAD in sequence according to the path order, generating a continuous space contour surface along the bridge segment center guide path, and generating a gingival space outer contour surface.

[0029] As a further solution of the present invention, the steps for obtaining the complete artificial gingival structure model are specifically as follows:

[0030] S511: Calling the three-dimensional coordinate information and boundary geometry information of the contour control filling data and the outer contour surface of the gingival space, performing data import and alignment operations in CAD, constructing a unified spatial coordinate system based on respective reference points, and generating contour alignment positioning data;

[0031] S512: Based on the contour alignment positioning data, identifying the spatial overlap region between the filling structure and the outer contour surface in CAD, performing intersection judgment according to the geometric boundary, extracting boundary line information of the intersection region, and recording the coordinates and normal direction of the overlap segment to generate an overlap boundary recognition result;

[0032] S513: Based on the overlapping boundary recognition result, the Boolean addition instruction is called in the CAD to geometrically fuse the contour-controlled filling structure with the outer contour surface of the gingival space to form a complete artificial gingival structure model. The CAM device is called to perform cutting or printing operations on the model with red dental resin material. The formed artificial gingival structure is bonded to the implant bridge through the preset retention groove of the structure to achieve seamless connection between the digital model of the bridge restoration and the physical entity.

[0033] A digital production system for artificial gingiva of a dental implant bridge, the digital production system for artificial gingiva of a dental implant bridge being used to execute the digital production method for artificial gingiva of a dental implant bridge, the system comprising:

[0034] The contour feature analysis module obtains the cross-sectional data of the bridge occlusal surface, calculates the slope difference of each cross-sectional point, and divides the contour into a variable section and a stable section based on the difference;

[0035] The partition filling parameter generation module sets the parameters of the gingival filling surface level for the contour change section and the contour stable section respectively by using a piecewise linear fitting method, and outputs contour control filling data;

[0036] The normal trajectory guidance path generation module constructs the normal trajectory of the adjacent tooth restoration contact surface for bridge artificial gingiva modeling, and continuously connects each normal vector in the constructed normal trajectory to obtain the bridge segment center guidance path;

[0037] The gingival space contour modeling module inputs the bridge segment center guide path into the CAD to perform artificial gingival space contour modeling to obtain the gingival space outer contour surface;

[0038] The digital gingival structure fusion module geometrically merges the contour control filling data with the outer contour surface of the gingival space in CAD to generate a complete artificial gingival structure model.

[0039] Compared with the prior art, the advantages and positive effects of the present invention are:

[0040] In the present invention, by calculating the slope difference of the occlusal cross-section points, the changing state of the contour area can be accurately identified, the spatial resolution capability of the cross-section data is improved, and the structural feature extraction is more refined. The filling parameters of different contour areas are set separately by linear fitting, which effectively enhances the partitioning control capability of the filling structure and makes the spatial filling level height more compatible with the gingival bionic requirements. A continuous path is constructed with the help of the direction vector of the contact surface of the adjacent tooth restoration to ensure a natural spatial transition between the gingival structure and the bridge structure, avoiding the path breakage and distortion problems in the manual design process. The cross-sectional structure is established with the path node as a reference, and the continuous surface connection is performed in CAD, which can accurately control the curvature and spatial compliance of the gingival external contour, and improve the smoothness and realism of the modeled structure. Through the alignment of geometric data and the judgment of intersection overlap, a high degree of fit between the filling structure and the spatial contour is achieved, avoiding spatial dislocation and boundary tearing in the structure splicing. Finally, the fused structural model is output to the physical molding equipment, and the seamless connection with the bridge is completed through the preset structure, so that the virtual design results can be stably transitioned to the physical restoration link. In the overall technical process, multi-dimensional collaborative operations such as dynamic curvature recognition, directional trajectory fitting, continuous surface generation, and regional filling structure fusion are used to significantly improve the spatial accuracy, filling layer integrity, and structural continuity of artificial gingival modeling. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0042] Figure 2 This is a flow chart of step S1 of the present invention;

[0043] Figure 3 This is a flow chart of step S2 of the present invention;

[0044] Figure 4 This is a flow chart of step S3 of the present invention;

[0045] Figure 5 This is a flow chart of step S4 of the present invention;

[0046] Figure 6 This is a flow chart of step S5 of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0048] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0049] See also Figure 1 The present invention provides a technical solution: a digital production method for artificial gingiva of a dental implant bridge, comprising the following steps:

[0050] S1: Obtain the cross-sectional data of the bridge occlusal surface, calculate the slope difference of each cross-sectional point, and divide the contour into a variable section and a stable section according to the difference;

[0051] S2: Use piecewise linear fitting method to set parameters of the gingival filling surface level for the contour change segment and the contour stable segment, and output contour control filling data;

[0052] S3: The normal trajectory of the adjacent tooth restoration contact surface for bridge artificial gingiva modeling is constructed, and each normal vector in the constructed normal trajectory is continuously connected to obtain the bridge segment center guide path;

[0053] S4: Input the bridge segment center guide path into CAD to model the artificial gingival space contour and obtain the gingival space outer contour surface;

[0054] S5: The contour control filling data and the outer contour surface of the gingival space are geometrically merged in CAD to generate a complete artificial gingival structure model;

[0055] The contour change section and the contour stable section are specifically the slope absolute difference range, contour change state mark, and curve point coordinate set. The contour control filling data includes the filling level Z value, area classification label, and transition surface node sequence. The bridge segment center guide path includes the path point spatial position, path segment normal direction, and path segment sequence identifier. The gingival space outer contour surface includes the contour cross-sectional shape, contour space coordinates, and contour connection sequence. The artificial gingival structure model includes the bridge connection area, occlusal filling area, and gingival extension boundary.

[0056] See also Figure 2 The specific steps for obtaining the contour change segment and the contour stable segment are:

[0057] S111: Acquire three-dimensional structural data of the bridge frame occlusal area, extract cross-sectional curve information corresponding to the occlusal surface, collect z-axis coordinate values ​​of points arranged in sequence on the cross section, calculate the z-axis slope value between each pair of adjacent points based on the order of the points, and generate a cross-sectional point slope value sequence;

[0058] When obtaining the three-dimensional structural data of the occlusal area of ​​the bridge, it is necessary to construct a complete three-dimensional surface mesh based on the data set of the bridge position in the digital dental model, and define a reference center axis along the extension direction of the bridge in the CAD environment. Then, using this axis as a reference, set equally spaced vertical section planes inside the bridge area. For example, set a section plane every 1.0 mm, and 10 cross-sectional curves can be obtained in the bridge area with a total length of 9 mm; on each section, collect 20 sampling points evenly distributed along the section direction, and record their spatial coordinate information. Extract the z-axis coordinate of each point and arrange them in point order, and then calculate the slope of the adjacent points in the z direction. The slope value k of the adjacent points i The calculation formula is:

[0059]

[0060] The index i represents the number of the current point, i+1 represents the number of its subsequent adjacent point, and the two numbers correspond to a pair of points one by one. i and z i are the coordinate values ​​of the point in the x and z directions respectively; k i is the local slope between the i-th point and the i+1-th point. When the point spacing in the x-direction is constant at 1.0 mm, the denominator can be considered a constant, and the slope is the difference between adjacent z-coordinates.

[0061] For example, suppose the coordinates of the first and second points in a cross-sectional curve in the z direction are 0.20 and 0.25 respectively, corresponding to x1 = 0.0 and x2 = 1.0, then: By analogy, a continuous sequence of cross-sectional point slope values ​​is constructed along the point sequence, which serves as the basic input data for subsequent identification of contour change features.

[0062] S112: Calculate the slope change of each point in the cross-section slope value sequence, identify the fluctuation trend in the slope change sequence through local extreme value detection, mark the change state of each curve segment, and generate curve slope change identification data;

[0063] When further identifying the geometric fluctuation characteristics of the structure based on the slope value sequence of the cross-section point, it is necessary to calculate the degree of change between adjacent slope values ​​to measure the amplitude of local curvature fluctuation, which is defined as the slope change The specific calculation formula is:

[0064]

[0065] Where i2 is the index number of the current slope value, and i2+1 represents the index number of the next slope value. The two correspond to a pair of adjacent slope values. It is important to note that the index i2 here does not overlap with the index i1 used for point numbering, and they are used for different purposes: the former is used to indicate the position of the change in slope, while the latter is used for the position of the original coordinate point sequence.

[0066] For example, if the first and second slope values ​​are k1=0.05 and k2=0.10 respectively, then the slope change is: Δk1=|0.10-0.05|=0.05; in order to determine whether the change constitutes a local geometric fluctuation, this embodiment sets the slope change threshold Δk t =0.04. The setting is based on the statistical data of the bridge occlusal surface in 20 artificial gingiva modeling projects. The average slope change is 0.018 and the standard deviation is 0.0093. Therefore, the empirical formula is used: when When , the corresponding position is identified as a potential fluctuation point. In order to further improve the robustness of the judgment, the minimum continuous fluctuation segment length threshold L is set min =3, only when continuous Only when the length exceeds this value and the whole value is greater than the threshold value, the segment is considered to be a valid contour change area. Finally, all segments that meet the conditions are marked and their fluctuation start and end point indexes, change intensity sequence and state identification are output to form the curve slope change identification data.

[0067] S113: Based on the curve slope change identification data, the curve segments in each cross section whose continuous change amount is greater than the set slope change threshold are divided into contour change segments, and the curve segments whose continuous change amount is less than the slope change threshold are divided into contour stable segments;

[0068] After obtaining the curve slope change identification data, in order to further convert the data into regional classification information that can be used for modeling, it is necessary to structurally divide the identified continuous fluctuation segments and define the following classification criteria: when all slope changes Δk in the continuous segment are equal i Satisfy Δk i >Δk t , and the length of this segment is greater than or equal to the continuous recognition point threshold L min =3, it is defined as a “profile change section”; when all Δk i <Δk t If the segment length is greater than or equal to 5, it is defined as a “stable contour segment”. t =0.04 is derived from the statistical analysis of 20 sets of actual design data in the bridge model, with a mean of 0.018 and a standard deviation of 0.0093. The empirical deviation amplification setting method is adopted:

[0069]

[0070] This setting ensures that in more than 95% of the samples, large slope jumps can be effectively identified as change areas. In the actual process, the system traverses each cross-sectional curve one by one and calculates the Δk i Perform continuous segment clustering judgment: take the starting point of the change segment as index 1, search from left to right for the point group that meets the continuous change condition, and record the starting point number, ending point number, segment length and average change value of each continuous segment. For example, if the slope change of points 5 to 9 is [0.05, 0.06, 0.05, 0.05], all of them are greater than Δk t , and the number of consecutive points is 5 ≥ 3, then this segment can be identified as a contour changing segment. Conversely, if the change in points 10 to 14 is [0.01, 0.02, 0.01, 0.03, 0.02], all less than the threshold, and the length is 5 points, then it is identified as a contour stable segment. The final processing result is: all qualified segments in each cross-sectional curve are marked as "changing" or "stable", and their start and end point indexes, lengths, classification status codes (1 for changing, 0 for stable), and corresponding original coordinate segments are output, integrating to form contour changing segment data and contour stable segment data.

[0071] See also Figure 3 , the specific steps for obtaining contour control filling data are:

[0072] S211: Recalling the z-axis coordinates and area categories of points in the contour changing section and the contour stable section, setting a fixed value lifting height for the contour changing section, and setting a proportional coefficient for the contour stable section to adjust the compression height, and calculating the corresponding partition filling level Z values ​​respectively;

[0073] Based on the contour change segment data and the contour stable segment data, it is necessary to assign the Z value of each type of point to the partition filling level according to the characteristics of different regions. First, extract all the point numbers and corresponding original z coordinate values ​​in the contour change segment and the contour stable segment, and record the area mark to which they belong. For all the point i3 in the change segment, let its original z-axis coordinate be Then its filling value is height-enhanced in the form of a fixed value, expressed as: in, Indicates the final filling level height of point i3, H b The unit is millimeters, which is the unified lifting height parameter of the contour change section. The value is based on the measured structural tolerance of the occlusal surface morphology analysis. Referring to 20 bridge restoration models, the allowable filling thickness range in the change section is between 0.6mm and 1.2mm. The median is taken as the reference lifting height, so H is set. b =0.8mm. For point i4 in the stable section, let its original coordinates be The filling value is set by the compression ratio coefficient α s ∈(0,1) compresses the original height, and the calculation formula is: Among them, α s It represents the compression ratio coefficient of the stable section. It is set to 0.6 based on the average height analysis of the stable area of ​​the model to avoid structural stacking redundancy.

[0074] For example, the point number of a change zone is 23, and its original height is z 23 =2.5mm, then the filling value is: Z 23 =2.5+0.8=3.3mm; if the stable area point number is 37, its original height is z 37 =2.5mm, then the filling value is: Z 37 =0.6×2.5=1.5mm; all points in the area are calculated in order of number The results are summarized to generate a set of Z values ​​for the partition filling level, providing the original data basis for subsequent spatial transition construction.

[0075] S212: Identify adjacent connected areas between the contour change segment and the contour stable segment, calculate the distance between the Z-axis coordinates in the connected areas, perform linear interpolation on the distance range, construct a transition filling Z value sequence between the two segments, and generate a transition filling Z value for the junction segment;

[0076] To ensure a high degree of continuity of the filling structure among different region types, a transitional filling section needs to be constructed at the boundary between the contour change section and the contour stable section. First, identify all pairs of connection points between adjacent change regions and stable sections, and extract the spatial coordinates x1, x2 of the two end boundary points and the corresponding filling heights Z1, Z2, which are defined as follows: x1: the horizontal position coordinate of the end point of the change section; x2: the horizontal position coordinate of the starting point of the stable section; Z1: the filling height corresponding to the point x1, sourced from the aforementioned Z2: the filling height corresponding to the point x2, sourced from the aforementioned Calculate the horizontal distance between the two end points: D = x2 - x1; Set equally spaced interpolation points in this interval. Let the current interpolation point position be x, and its corresponding transitional filling height Z(x) is calculated by linear interpolation:

[0077]

[0078] In this interpolation model, the meaning of each variable is as follows: Z(x): the filling height at the interpolation point position x; Z1: the starting filling value (boundary of the change section); Z2: the ending filling value (boundary of the stable section); D: the horizontal distance between the two boundary points; x: the horizontal position of the interpolation point, satisfying x1 < x < x2, x - x1: represents the relative position offset of the current interpolation point x relative to the left boundary point x1, used to scale the weight to linearly transition from Z1 to Z2.

[0079] For example, let x1 = 2.0 mm, x2 = 4.0 mm, corresponding to Z1 = 3.3 mm, Z2 = 1.5 mm, and take the midpoint x = 3.0 mm, then: According to this rule, batch interpolation operations can be performed on all connection regions to generate a continuous sequence of Z values for the transitional filling of the junction section, and record the corresponding point numbers and coordinate positions.

[0080] S213: Combine the Z values of the partition filling levels and the Z values of the transitional filling of the junction section, arrange the Z values in the order of point coordinates to construct a complete filling level structure, and mark the region type and level height of each point to generate contour control filling data;

[0081] After obtaining the Z values ​​for the partitioned fill level and the transition fill level at the junction, all points need to be spatially ordered to construct a complete hierarchical fill structure. First, all points are numbered uniformly and a region tag field is added (variable: 1, stable: 0, transition: 2). Then, they are sorted from smallest to largest by x-coordinate to construct a unified point sequence. Each point records four dimensions: original x, original z, calculated fill value Z, and region type. The structured representation is as follows: point number → (x, z, Z, region tag). For example, point number 42, located in the transition section, has spatial coordinates of x = 3.0 mm, z = 2.2 mm, and an interpolated fill value of Z = 2.4 mm. This is represented as: 42 → (3.0, 2.2, 2.4, 2). This operation is performed on all points to form a complete contour control fill data set, which serves as the basis for the fill level parameters of the subsequent geometric fusion model, ensuring 3D modeling continuity and complete representation of hierarchical information.

[0082] See also Figure 4 ,The specific steps for obtaining the guiding path of the bridge segment center are:

[0083] S311: Acquire the contact surface area of ​​the adjacent tooth restorations at both ends of the bridge structure, select a specified number of spatial sampling points within the middle range of the contact surface, construct a cutting plane for each sampling point using CAD, extract the normal direction vector information of the plane, and generate a normal vector set of the adjacent tooth contact surface;

[0084] In order to construct the three-dimensional path guidance structure of the artificial gingiva of the bridge, it is necessary to first identify the contact surface between the two ends of the bridge and the adjacent tooth restorations and obtain their normal structural characteristics. This operation is completed by analyzing the topological structure of the three-dimensional model of the bridge in the CAD modeling environment. First, locate the connection area between the left and right ends of the bridge and the adjacent tooth restorations. Starting from the longitudinal boundary of the bridge, expand outward 0.5mm along its normal projection distance and limit it to the middle range of the contact surface. Then, spatial sampling points are equidistantly selected in a regular grid manner within this area, and the number of points extracted on each contact surface is set to N. pt = 10, that is, a total of 20 points are sampled on both ends to establish the initial normal vector set. For each sampling point x, y, z, its number is pt j , where j = 1, 2, ..., 20, represents the index position of the point in the entire point set. The position coordinates of each point in three-dimensional space are expressed as: In the CAD environment, each point As the center, the tangent plane is constructed according to the local differential method of the surface to which it is attached, and the unit normal vector of the plane in three-dimensional space is extracted, which is recorded as: in, is the unit normal vector of point j; n xj 、n yj 、n zjRespectively represent its components in the x, y, and z directions of three-dimensional space. This vector satisfies the normalization condition: Ensure that all normal vectors reflect the dominant direction of the local curvature of the points on the contact surface. The stability of the contact surface normal information has a significant impact on the subsequent guidance path modeling. In order to control the degree of data dispersion, the plane normal fluctuation allowable threshold θ is set. var ≤10°. This angle is derived from the standard deviation statistics of the normal direction angle distribution of 20 standard bridge models. The maximum direction deviation does not exceed 12.7°, so the control threshold is set within 10°. After the normal vectors of all sampling points are extracted, a structured set is formed: Each element in the set contains the spatial coordinates of the sampling point and the corresponding unit normal vector. This set is the normal vector set of the adjacent tooth contact surface, which is used in subsequent modeling steps such as direction sorting and path fitting to ensure that the path construction process refers to the actual structural directional characteristics of the dentition.

[0085] S312: Based on the angle between each vector in the set of normal vectors of the adjacent tooth contact surface and the longitudinal axis of the bridge, each normal vector is positioned and sorted in spatial position order, and the spatial position coordinates and direction information are recorded to generate ordered direction data of the normal vector;

[0086] After obtaining the normal direction data of the adjacent tooth contact surface, these direction vectors need to be arranged in order and spatially oriented for subsequent bridge path fitting calculations. This process uses the overall direction of the bridge as the reference axis, calculates the angle between each normal vector and the reference direction, and sorts the points according to their positions in the longitudinal coordinates of the bridge to generate ordered normal vector direction data. First, assume that the overall extension direction of the bridge is the main axis direction, and define the unit reference direction vector as: in: The longitudinal reference axis vector of the bridge; this vector is defined in the standard right-hand coordinate system, along the positive direction of the x-axis, and has a modulus of As the basis for the subsequent calculation of the spatial direction angle. For each vector in the extracted normal vector set Among them: pt j : represents the jth sampling point, j = 1, 2, ..., 20; n xj 、n yj 、n zj : are the components of the normal vector corresponding to the j-th point in the x, y, and z directions respectively; The modulus of the normal vector should be 1 in theory. If there is a deviation, it needs to be normalized. Calculate each normal vector Vector with bridge axis The angle between Use the cosine formula for the angle between two vectors:

[0087]

[0088] because and And the unit normal vector has been normalized, then:

[0089]

[0090] in: The angle between the normal vector of the jth sampling point and the main axis of the bridge, in degrees; arccos: inverse cosine function, used to recover the angle from the cosine value; n xj : Directly represents the directional consistency of the vector in the axial direction of the bridge. The closer the value is to 1, the closer it is to the longitudinal direction of the bridge.

[0091] Let the normal vector of the j=6th sampling point be Then its modulus is:

[0092]

[0093] After normalization, there is n x6 ≈0.912, then:

[0094] Set the angle deviation threshold θ limit The basis is as follows: the contact surface direction data were extracted from 20 bridge clinical design models, and the mean of the normal direction angle was statistically obtained. The standard deviation is σ θ =7.3°, using the empirical formula: all The vector will be marked as a deviation point and used for curvature constraint or error analysis in the subsequent fitting process.

[0095] Then, the spatial coordinates of each point Corresponding normal vector and its angle value Forming triples: Forming a collection: In order to ensure that the direction path construction extends naturally from one end of the bridge to the other end, it is necessary to locate the point in the direction of the bridge axis (i.e. value) in ascending order, and define the sorting operation as: The sorted set R sort This is the ordered direction data of the normal vector, which is used for the subsequent Frenet-Serret continuous path construction to ensure that the order of each point is consistent with the structural logic and complies with the principles of directional continuity and coordinate orderliness of the bridge segment model fitting.

[0096] S313: Based on the direction change trend and spatial coordinate information recorded in the ordered direction data of the normal vector, the Frenet-Serret path generation method is used to perform continuous curve fitting on the ordered vector, thereby constructing a central guide trajectory for artificial gingival modeling in the bridge area and generating a central guide path for the bridge segment;

[0097] In the constructed normal vector ordered direction data set Based on each element Represents the complete information structure of the jth sorted sampling point, including the three-dimensional spatial coordinates of the point Unit normal vector (n xj ,n yj ,n zj ), and the angle between the normal vector and the main axis of the bridge It is necessary to further perform continuous fitting of the spatial path based on these sorted points to generate a three-dimensional center guide path for the bridge segment for artificial gingiva modeling. The path is constructed using the Frenet-Serret curve method, based on the local geometric direction change of each point on the path, to construct a path function. in represents the path space coordinate function, s is the arc length parameter of the path, in millimeters, and the points are numbered in ascending order from the starting point of the path. The first step in constructing the path function is to define the spatial position of each sorted sampling point, which is denoted as:

[0098]

[0099] in, is the three-dimensional coordinate vector of the j-th sampling point, Respectively represent the coordinate values ​​of the point in the x, y, and z coordinate directions of the space; subscript pt j Number the position of the point in the sorted point set. and Calculate its unit tangent vector Indicates the local direction of the path change at this point, expressed as:

[0100]

[0101] In this formula, Represents the tangential direction vector of the path at the jth arc length position, unit length; symbol Represents the coordinate vector of the j+1th sampling point in the sort, indicating that it is a continuous adjacent point after the jth point, j+1 is the increasing index of the position number, which is used to construct the vector difference; the symbol |||| represents the Euclidean norm of the three-dimensional vector, that is, the spatial length operation; the obtained That is, the unit vector pointing from point j to point j+1, representing the local direction of the path at that position. Continue to construct the principal normal vector with two adjacent tangent vectors Defined as:

[0102]

[0103] in, Represents the principal normal unit vector at the jth sampling point, indicating the direction change trend of the path near this point, which belongs to the curvature direction component. and For two adjacent tangent vectors, use their direction changes to establish the main normal; the main normal is also a unit vector, pointing to the "outside" of the path bend; continue to construct the binormal vector Defined as:

[0104]

[0105] in, Represents the binormal vector of the path at the jth point, which represents the direction orthogonal to the tangent and the principal normal, forming a three-dimensional orthogonal coordinate system. The symbol × represents the cross product operation between three-dimensional vectors. The direction of the cross product result is perpendicular to the two input vectors, and the direction is determined by the right-hand rule. Finally, at each arc length position s j On the , the following three sets of geometric direction vectors are formed: The tangent vector represents the forward direction of the path; The principal normal vector represents the direction of curvature change; The binormal vector represents the direction plane normal according to which the cross section rotation is constructed.

[0106] For example, if two points are and Then the difference vector is (0.5, 0.3, 0.3), and its length is The corresponding unit tangent vector is:

[0107] The same calculation Then, substitute into the above formula to find Then calculate by cross product Each set of vectors forms an orthogonal frame; the corresponding vectors of all path points are Combine them in order to form a spatial path function The discrete structure can be constructed by interpolating cubic spline or B-spline functions to establish a continuous representation. This is the guiding path for the center of the bridge segment. In the artificial gingiva modeling of the bridge frame, this path provides the position reference, direction reference, and posture reference of the cross-sectional contour structure, which is used to control the extension, rotation, and fusion of the overall shape in space, forming the path skeleton in digital modeling.

[0108] See also Figure 5 , the steps for obtaining the outer contour surface of the gingival space are as follows:

[0109] S411: Inputting the spatial coordinate information of the path points of the bridge segment center guide path data into the CAD, determining the corresponding normal direction at each node of the path, locating the cross section according to the normal direction to construct a reference plane, and generating path node normal positioning information;

[0110] The 3D trajectory data of the central guide path of the bridge section is imported into CAD. Within the modeling environment, the coordinates of each spatial node along the path are read point by point, and the directional trend of each node along the path is analyzed. At each node, the local spatial orientation of the node is determined based on the positional relationship between the preceding and following adjacent points. This is the direction vector at that node. A reference plane perpendicular to the path orientation is then established in this direction. This reference plane serves as the geometric basis for subsequent cross-section construction. The center point of the plane is the 3D coordinate position of the path node, and the normal direction is the local normal or dominant curvature direction of the path at that node. In this way, a series of independent spatial planes that align with the local orientation of the path are continuously arranged throughout the entire path, ensuring that the geometric reference information relied upon for cross-section construction is accurately obtained at any location in space. Each reference plane not only has a clear orientation and position in space but also possesses the characteristic of being orthogonal to the path tangent.

[0111] S412: Based on the normal positioning information of the path nodes, a standard elliptical or eccentric wheel cross-section structure is constructed on each reference plane, the contour geometry is established in sequence according to the node sequence, the contour morphological parameters and spatial position of each cross section are recorded, and the node cross-section contour structure is generated;

[0112] Based on established reference planes at each node of the path, a corresponding cross-sectional structure is constructed on each plane, typically a standard ellipse or a slightly eccentric closed contour. The construction process uses the center point of the plane as the contour center, sets the major and minor axis lengths according to design requirements, and generates a complete, closed two-dimensional contour line within the plane. This contour line represents the gingival cross-section of the bridge segment at that node. The cross-section can be a symmetrical ellipse or a personalized eccentric design based on the morphology of adjacent teeth or soft tissue. During the construction process, each cross-sectional contour not only has specific geometric dimensions but also includes information about its position, orientation, and rotation in space. These cross-sections are constructed sequentially along the path, fully documenting their distribution and geometric characteristics at the node points. The size ratios, directional gradients, and rotation angles of all cross-sections can be adjusted based on anatomical or physiological requirements to ensure that the shape meets clinical requirements such as occlusal physiology and a natural transition of gingival retraction.

[0113] S413: performing surface connection operations on the node cross-section contour structures in CAD in sequence according to the path order, generating a continuous space contour surface along the bridge segment center guide path, and generating a gingival space outer contour surface;

[0114] After completing the construction of all cross-sectional contours, the surface connection function provided by the CAD modeling tool is used to connect each adjacent section one by one in the order of the path to form a continuous and closed three-dimensional spatial surface structure. During the connection process, the system automatically interpolates and fits according to the shape, size and direction of each two adjacent sections to generate a connection surface with smooth curvature and natural transition. The connection surface wraps and extends all cross-sectional contours as a whole, and finally forms the external surface contour of the artificial gingiva of the bridge section. Through this operation, the sections that were originally discretely distributed at the path nodes are unified and encapsulated into a complete outer shell surface. This surface not only accurately reflects the spatial direction and local changes of the path, but also ensures the fit, closure and stability of the gingival model in clinical applications. The generated spatial contour surface is continuous, editable and structurally controllable, and is an important intermediary layer that connects shape and functional performance in the process of digital gingival modeling.

[0115] See also Figure 6 The specific steps for obtaining a complete artificial gingival structure model are as follows:

[0116] S511: Calling the contour control filling data and the three-dimensional coordinate information and boundary geometry information of the outer contour surface of the gingival space, importing and aligning the data in CAD, constructing a unified spatial coordinate system based on the respective reference points, and generating contour alignment positioning data;

[0117] After completing the construction of the spatial outer contour surface of the artificial gingiva, in order to jointly model the pre-set contour-controlled filling structure with the outer contour surface, it is first necessary to import these two types of structural data in the CAD environment and complete the unified alignment of the spatial coordinate system. The specific process is: import the filling structure file and the outer contour surface data into the modeling software respectively, select the spatial reference reference points of each of them in the software, usually known spatial reference features such as the structure center point, the contour geometry center of gravity or the path starting node, and use these reference points as the core anchor points for the coordinate system alignment to establish a unified reference coordinate system in space. The software automatically performs alignment calculations between the reference points, transforms the filling structure as a whole into a coordinate range that matches the outer contour surface, and ensures consistency between the two in position, direction and scale. After the alignment is completed, the system generates a set of positioning data that describes the positional relationship of the filling structure relative to the outer contour surface in three-dimensional space, and records the transformed coordinates, alignment angle and posture change direction of each contour boundary point.

[0118] S512: Based on the contour alignment positioning data, the spatial overlap area between the filling structure and the outer contour surface is identified in the CAD, and an intersection judgment is performed according to the geometric boundary. The boundary line information of the intersection area is extracted, and the coordinates and normal direction of the overlapped segment are recorded to generate an overlap boundary recognition result.

[0119] After completing the spatial alignment of the contour filling structure and the outer contour surface of the gum, it is necessary to identify whether there is a geometric overlap between the two in three-dimensional space. To this end, the boundary detection and intersection judgment functions are enabled in the CAD software, and each contact area between the filling structure surface and the outer contour surface is scanned in turn, and the spatial relationship between the two sets of surfaces is compared and analyzed. According to the set tolerance range, the system compares the spatial distribution and normal orientation of the two structures at their respective surface grid points, and automatically identifies all areas where overlap or interlacing occurs. For each spatial overlapping area identified, the software will extract its boundary line segments, intersection coordinates, and the local normal direction of the area, so that the model closure and curvature continuity can be guaranteed when subsequent geometric Boolean operations are performed. All overlapping data will be recorded as independent structure recognition results, with the spatial geometric information and positioning information of the intersection boundary. This step ensures that in the subsequent structure fusion process, each structural unit can achieve complete digital fit and boundary consistency before actual physical processing, avoiding problems such as internal cavities, boundary breaks, or geometric conflicts after model generation.

[0120] S513: Based on the overlapping boundary recognition results, the Boolean addition instruction is called in the CAD to geometrically fuse the contour-controlled filling structure with the outer contour surface of the gingival space to form a complete artificial gingival structure model. The CAM device is called to perform cutting or printing operations on the model using red dental resin material. The formed artificial gingival structure is bonded to the implant bridge through the structure's preset retention grooves, achieving seamless connection between the digital model and the physical entity of the bridge restoration.

[0121] After structural alignment and identification of overlapping areas, the contour-controlled filling structure and the gingival contour surface are spatially geometrically fused to generate a unified, complete artificial gingival 3D model. This operation is accomplished using the Boolean addition instructions provided by the CAD modeling system. The system invokes the Boolean fusion function to perform structural merging on the identified overlapping areas, automatically reconstructing the mesh boundaries of the two structures into a unified, closed surface to ensure overall model coherence and seamlessness. After the Boolean operation is completed, the resulting 3D model is a complete structure with smooth, continuous surfaces and seamless internal filling transitions, fully meeting the requirements for digital manufacturing. The model is then directly transferred to a digital processing device, such as a dedicated five-axis dental CNC milling machine or a high-precision photosensitive resin 3D printer. Red dental-grade resin is used as the modeling material, with the material type and hardness grade selected based on gingival simulation and user experience. After processing, the resulting artificial gingival structure will have pre-designed retention slots or snap-in structures. It will be physically connected to the implant bridge via bonding, snap-on, or screw connections, achieving precise integration between the digital modeling phase and the clinical restoration. The final artificial gingival restoration not only has a highly consistent occlusal relationship and anatomical morphology, but also meets the multiple requirements of clinical installation accuracy, operational convenience and aesthetic stability, completing the seamless conversion from digital model to physical structure.

[0122] A digital production system for artificial gingiva of a dental implant bridge frame, the digital production system for artificial gingiva of a dental implant bridge frame is used to execute the digital production method for artificial gingiva of a dental implant bridge frame, and the system comprises:

[0123] The contour feature analysis module obtains the cross-sectional data of the bridge occlusal surface, calculates the slope difference of each cross-sectional point, and divides the contour into a variable section and a stable section based on the difference;

[0124] The partition filling parameter generation module uses the piecewise linear fitting method to set the parameters of the gingival filling surface level for the contour change segment and the contour stable segment, and outputs the contour control filling data;

[0125] The normal trajectory guidance path generation module constructs the normal trajectory of the adjacent tooth restoration contact surface for bridge artificial gingiva modeling, and continuously connects each normal vector in the constructed normal trajectory to obtain the bridge segment center guidance path;

[0126] The gingival space contour modeling module inputs the bridge segment center guide path into CAD to perform artificial gingival space contour modeling and obtain the gingival space outer contour surface;

[0127] The digital gingival structure fusion module geometrically merges the contour control filling data with the outer contour surface of the gingival space in CAD to generate a complete artificial gingival structure model.

[0128] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A digital production method for artificial gingiva of a dental implant bridge, characterized in that: The following steps are involved: S1: Obtain the cross-sectional data of the bridge occlusal surface, calculate the slope difference of each cross-sectional point, and divide the contour into a variable section and a stable section according to the difference; S2: setting parameters of the gum filling surface level for the contour changing section and the contour stable section respectively by piecewise linear fitting method, and outputting contour control filling data; S3: The normal trajectory of the adjacent tooth restoration contact surface for bridge artificial gingiva modeling is constructed, and each normal vector in the constructed normal trajectory is continuously connected to obtain the bridge segment center guide path; S4: inputting the bridge segment center guide path into CAD to perform artificial gingival space contour modeling to obtain the gingival space outer contour surface; S5: geometrically merging the contour control filling data with the outer contour surface of the gingival space in CAD to generate a complete artificial gingival structure model.

2. The digital production method of artificial gingiva for dental implant bridge according to claim 1, characterized in that: The contour change section and the contour stable section are specifically the slope absolute difference range, the contour change state mark, and the curve point coordinate set. The contour control filling data includes the filling level Z value, the area classification label, and the transition surface node sequence. The bridge segment center guide path includes the path point spatial position, the path segment normal direction, and the path segment sequence identifier. The gingival space outer contour surface includes the contour cross-sectional shape, the contour space coordinates, and the contour connection sequence. The artificial gingival structure model includes the bridge connection area, the occlusal filling area, and the gingival extension boundary.

3. The digital production method of artificial gingiva for dental implant bridge according to claim 2, characterized in that: The steps for obtaining the contour change section and the contour stable section are specifically as follows: S111: Acquire three-dimensional structural data of the bridge frame occlusal area, extract cross-sectional curve information corresponding to the occlusal surface, collect z-axis coordinate values ​​of points arranged in sequence on the cross section, calculate the z-axis slope value between each pair of adjacent points based on the order of the points, and generate a cross-sectional point slope value sequence; S112: calculating the slope variation of each point in the cross-section slope value sequence, identifying the fluctuation trend in the slope variation sequence by local extreme value detection, marking the change state of each curve segment, and generating curve slope variation identification data; S113: Based on the curve slope change identification data, the curve segments in each section whose continuous change amount is greater than the set slope change threshold are divided into contour change segments, and the curve segments whose continuous change amount is less than the slope change threshold are divided into contour stable segments.

4. The method for digitally producing artificial gingiva for a dental implant bridge according to claim 3, characterized in that: The steps for obtaining the contour control filling data are specifically as follows: S211: Calling the z-axis coordinates of the points in the contour changing section and the contour stable section and the area categories to which they belong, setting a fixed value lifting height for the contour changing section, setting a proportional coefficient for the contour stable section to adjust the compression height, and calculating the corresponding partition filling level Z values ​​respectively; S212: Identify adjacent connected areas between the contour changing segment and the contour stable segment, calculate the distance between the Z-axis coordinates in the connected areas, perform linear interpolation on the distance range, construct a transition filling Z value sequence between the two intervals, and generate a transition filling Z value for the junction segment; S213: Combining the partition filling level Z value and the junction section transition filling Z value, arranging the Z values ​​in order of point coordinates to construct a complete filling level structure, and marking the area type and level height of each point to generate contour control filling data.

5. The method for digitally producing artificial gingiva for a dental implant bridge according to claim 4, characterized in that: The steps for obtaining the guiding path of the center of the bridge section are specifically as follows: S311: Acquire the contact surface area of ​​the adjacent tooth restorations at both ends of the bridge structure, select a specified number of spatial sampling points within the middle range of the contact surface, construct a cutting plane for each sampling point using CAD, extract the normal direction vector information of the plane, and generate a normal vector set of the adjacent tooth contact surface; S312: Positioning and sorting each normal vector in the set of normal vectors of the adjacent tooth contact surfaces according to the angle between each vector and the longitudinal axis of the bridge frame in spatial position order, recording the spatial position coordinates and direction information, and generating ordered direction data of the normal vector; S313: Based on the direction change trend and spatial coordinate information recorded in the ordered direction data of the normal vector, the Frenet-Serret path generation method is called to perform continuous curve fitting on the ordered vector, a center guide trajectory for artificial gingival modeling in the bridge area is constructed, and a center guide path of the bridge segment is generated.

6. The method for digitally producing artificial gingiva for a dental implant bridge according to claim 5, characterized in that: The steps for obtaining the outer contour surface of the gum space are specifically as follows: S411: Inputting the spatial coordinate information of the path points of the bridge section center guide path data into the CAD, determining the corresponding normal direction at each node of the path, locating the cross section according to the normal direction to construct a reference plane, and generating path node normal positioning information; S412: Constructing a standard elliptical or eccentric wheel cross-sectional structure on each reference plane according to the normal positioning information of the path nodes, establishing contour geometry in sequence according to the node sequence, recording the contour morphological parameters and spatial position of each cross section, and generating a node cross-sectional contour structure; S413: performing surface connection operations on the node cross-section contour structure in CAD in sequence according to the path order, generating a continuous space contour surface along the bridge segment center guide path, and generating a gingival space outer contour surface.

7. The method for digitally producing artificial gingiva for a dental implant bridge according to claim 6, characterized in that: The steps for obtaining the complete artificial gingival structure model are specifically as follows: S511: Calling the three-dimensional coordinate information and boundary geometry information of the contour control filling data and the outer contour surface of the gingival space, performing data import and alignment operations in CAD, constructing a unified spatial coordinate system based on respective reference points, and generating contour alignment positioning data; S512: Based on the contour alignment positioning data, identifying the spatial overlap region between the filling structure and the outer contour surface in CAD, performing intersection judgment according to the geometric boundary, extracting boundary line information of the intersection region, and recording the coordinates and normal direction of the overlap segment to generate an overlap boundary recognition result; S513: Based on the overlapping boundary recognition result, the Boolean addition instruction is called in the CAD to geometrically fuse the contour-controlled filling structure with the outer contour surface of the gingival space to form a complete artificial gingival structure model. The CAM device is called to perform cutting or printing operations on the model with red dental resin material. The formed artificial gingival structure is bonded to the implant bridge through the preset retention groove of the structure to achieve seamless connection between the digital model of the bridge restoration and the physical entity.

8. A digital production system for artificial gums for dental implant bridges, characterized in that: The method for digitally producing artificial gingiva for a dental implant bridge according to any one of claims 1 to 7, wherein the system comprises: The contour feature analysis module obtains the cross-sectional data of the bridge occlusal surface, calculates the slope difference of each cross-sectional point, and divides the contour into a variable section and a stable section based on the difference; The partition filling parameter generation module sets the parameters of the gingival filling surface level for the contour change section and the contour stable section respectively by using a piecewise linear fitting method, and outputs contour control filling data; The normal trajectory guidance path generation module constructs the normal trajectory of the adjacent tooth restoration contact surface for bridge artificial gingiva modeling, and continuously connects each normal vector in the constructed normal trajectory to obtain the bridge segment center guidance path; The gingival space contour modeling module inputs the bridge segment center guide path into the CAD to perform artificial gingival space contour modeling to obtain the gingival space outer contour surface; The digital gingival structure fusion module geometrically merges the contour control filling data with the outer contour surface of the gingival space in CAD to generate a complete artificial gingival structure model.

Images