A three-dimensional scanning-based virtual try-on system for dental prostheses

Abstract

This invention discloses a virtual fitting system for dental prostheses based on 3D scanning, belonging to the field of digital dental prosthodontics. It includes a data acquisition module, a trajectory processing module, a model construction module, a fitting simulation module, and an anomaly optimization module. Through 3D scanning and automated point cloud processing, it can quickly acquire high-precision 3D models of the maxillary and mandibular dentition, providing reliable data support for prosthodontic design. Optical motion capture fully reproduces the patient's physiological mandibular movements, overcoming the limitations of existing systems that can only perform static simulations, making occlusal detection more clinically accurate. A unified reference coordinate system is established to achieve precise model registration, controlling prosthodontic positioning errors within 0.01mm, significantly improving fit. It can automatically identify premature contacts and occlusal interferences and perform intelligent optimization of the occlusal surface, replacing repeated manual adjustments, effectively shortening the treatment cycle, improving prosthodontic accuracy and wearing comfort, and enhancing the overall treatment experience.

Description

Technical Field

[0001] This invention relates to the field of digital dental restoration technology, specifically to a virtual fitting system for dental prostheses based on three-dimensional scanning. Background Technology

[0002] Clinical fabrication and fitting of dental prostheses are crucial steps in the treatment of tooth defects and missing teeth. Traditional procedures rely primarily on intraoral occlusal testing, plaster model pouring, and manual adjustment, which have significant technical limitations. Under this traditional approach, prosthesis design is highly dependent on the dentist's experience, and occlusal relationships can only be roughly determined through static occlusal records. This makes it difficult to accurately match the patient's actual mandibular movement trajectory, leading to problems such as poor prosthesis placement, high occlusal points, premature contact, and lateral movement interference. This not only increases the number of clinical adjustments but may also cause complications such as occlusal trauma and temporomandibular joint discomfort.

[0003] With the development of digital dental technology, 3D scanning has been gradually applied to prosthesis design. However, existing digital solutions are mostly based on static dental arch models for virtual design, lacking the ability to dynamically recreate the patient's physiological mandibular movements. Most existing systems can only simulate the static placement of the prosthesis and cannot simultaneously simulate functional movements such as opening and closing, protrusion, and lateral movement, making it difficult to comprehensively detect dynamic occlusal contact. At the same time, existing technologies have shortcomings in the identification and automatic optimization of occlusal abnormalities; premature contact and occlusal interference still require manual judgment and adjustment by dentists, and the advantages of digitalization are not fully realized. Summary of the Invention

[0004] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a virtual fitting system for dental prostheses based on three-dimensional scanning, which solves the problems mentioned in the background section.

[0005] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: a virtual fitting system for dental prostheses based on three-dimensional scanning, comprising: The data acquisition module is used to collect point cloud data of the patient's upper and lower jaws, select static reference points and their coordinates from the point cloud data, and generate a static three-dimensional dental arch model. The trajectory processing module is used to collect the real-time coordinates of the static reference points of the patient's physiological mandibular movements, calculate the motion trajectory parameters, and construct a dynamic jaw position movement model. The model building module is used to design the basic model of the restoration based on the static dentition model and to establish a virtual occlusal surface reference coordinate system. The trial fitting simulation module is used to integrate the dynamic jaw movement model with the basic model of the prosthesis and the model of the maxillary and mandibular dentition to construct a dynamic virtual trial fitting scene, simulate the patient's physiological mandibular movement and determine the occlusal contact data; The anomaly optimization module is used to optimize and adjust the occlusal surface of the prosthesis based on occlusal contact data.

[0006] As a further aspect of the present invention: in the data acquisition module, the dentition point cloud data is obtained by scanning the upper and lower jaw dentition, gingiva and edentulous tissue in the patient's oral cavity using an intraoral 3D scanner; Dental point cloud data is denoted as P={P i}, i=1,2,......,n,P i For the i-th scan point, it contains static three-dimensional coordinates [x (P i ),y(P i ),z(P i )], and P∈{U=[U i1 ], L=[L i2 ]}, where U is the set of maxillary dentition point clouds and L is the set of mandibular dentition point clouds.

[0007] As a further aspect of the present invention: the data acquisition module further performs noise reduction and triangulation processing on the dental arch point cloud data; The method is as follows: for each scan point P i Select a preset number of neighboring points to form a neighborhood set Q i ={P j Then, using the three-dimensional Euclidean distance formula, P is calculated. i With neighboring point P j Spatial distance L ij And find the neighborhood points P of each neighborhood. j The average value is used to obtain the average distance LP. i Then L will be satisfied. ij >LP i The neighboring points of +L0 are identified as isolated noise points and removed to obtain an effective point cloud set P1; and L0 is a preset distance threshold.

[0008] As a further aspect of the present invention: the data acquisition module traverses the effective point cloud set P1, selects three points that are spatially adjacent and have continuous surface trends as vertices of triangular facets, generates only triangular facets with side lengths within a pre-set reasonable range, and topologically integrates them into the maxillary model MU and the mandibular model ML after tiling them in the order from the inside to the outside of the dental facets.

[0009] As a further aspect of the present invention: the static reference points selected by the data acquisition module include: the maxillary incisor decussation point, the mesiobuccal apex of the bilateral maxillary first molars, the midpoint of the mandibular incisor, and the mesiobuccal apex of the bilateral mandibular first molars, respectively forming a set P of maxillary reference points. U With the set of mandibular reference points P L And obtain the three-dimensional static coordinates under the maximum cusp intersection position.

[0010] As a further aspect of the present invention: the physiological mandibular movements collected by the trajectory processing module include: opening and closing movements, protrusion movements, left-side movements, and right-side movements; Each set of movements is repeated multiple times, and the real-time three-dimensional coordinates of the static reference point are obtained through optical motion capture equipment.

[0011] As a further aspect of the present invention: the trajectory processing module calculates the following respectively: vertical displacement of the midpoint of the mandibular incisor during opening and closing movements, anterior-posterior displacement of the midpoint of the mandibular incisor during protrusion movements, leftward displacement of the left buccal tip during leftward movements, and rightward displacement of the right buccal tip during rightward movements, and takes the average value of multiple movement results to form a motion parameter set ML(D).

[0012] As a further aspect of the present invention: when the model building module constructs the basic model MR of the restoration, it uses the point cloud data of the occlusal surface of the opposing dentition as a reference, selects the nearest multiple scanning points of the restoration design point, and takes the average coordinate as the initial coordinate of the restoration occlusal surface design point.

[0013] As a further aspect of the present invention: in the virtual occlusal surface reference coordinate system OXYZ established by the model construction module, the origin O is the midpoint of the line connecting the mesobacterial cusps of the bilateral maxillary first molars, the X-axis is the anterior-posterior direction, the Y-axis is the lateral direction, and the Z-axis is the vertical direction.

[0014] As a further aspect of the present invention: when the trial fitting simulation module performs spatial registration and positioning, the maxillary model MU is fixed in the reference coordinate system, and the initial positioning is completed when the average fitting error between the restoration base model MR and the edge of the edentulous area is less than the preset fitting error threshold; at the same time, the mandibular model ML and the maxillary model MU are registered to the maximum cusp intersection position.

[0015] As a further aspect of the present invention: during the dynamic simulation of the trial fitting module, the corresponding displacement is superimposed frame by frame according to the time frame, thereby driving the mandibular model to complete the simulation of opening and closing, protrusion, left side and right side movements.

[0016] As a further aspect of the present invention: when the trial fitting simulation module detects occlusal contact, it traverses the triangular facets of the occlusal surfaces of the restoration and the opposing dentition, and calculates the shortest distance for each pair of triangular facets; when the shortest distance of the triangular facets is less than or equal to a preset contact threshold, it is determined that they are in contact, and the coordinates and time frame of the contact point are recorded.

[0017] As a further aspect of the present invention: the abnormality optimization module determines the contact point when the opening and closing movement time is less than 0.2s as the early contact point, and determines the contact point in the non-working side area during the forward / lateral movement as the occlusal interference point, and forms the early contact point set and the occlusal interference point set respectively.

[0018] As a further aspect of the present invention: the anomaly optimization module calculates the adjustment amount of the occlusal surface of the restoration by subtracting the shortest distance of the triangular facet from a preset contact threshold; Simultaneously, the vertical coordinates of the vertices of the triangular facets containing the early contact point and the occlusal interference point are reduced accordingly, and iterative optimization is performed until there is no early contact or occlusal interference.

[0019] (III) Beneficial Effects This invention provides a virtual fitting system for dental prostheses based on three-dimensional scanning. Compared with existing technologies, it has the following advantages: This invention uses intraoral 3D scanning and automated point cloud processing to quickly acquire high-precision 3D models of the maxillary and mandibular dentition, gingiva, and edentulous areas. Compared with traditional impression taking and manual modeling, it significantly improves data acquisition efficiency and model accuracy, effectively avoids noise interference, and provides a stable and reliable data foundation for subsequent prosthesis design and virtual fitting.

[0020] This invention uses optical motion capture to fully collect the physiological mandibular movement trajectories of patients, such as opening and closing the mouth, protrusion, and left and right lateral movements. By averaging multiple sets of repeated movements, the accuracy of motion parameters is greatly improved, and the dynamic occlusal behavior of patients' mandibles is realistically reproduced. This invention makes up for the deficiency of existing digital systems that only support static simulation, and makes occlusal detection closer to clinical practice.

[0021] This invention establishes a unified virtual occlusal surface reference coordinate system to achieve precise spatial registration of the maxillary and mandibular models and prosthesis models. The positioning and fitting error of the prosthesis can be controlled within 0.01mm, which significantly improves the positioning accuracy, effectively reduces problems such as poor positioning and loose edge fit during clinical fitting, and improves the adaptability of the prosthesis.

[0022] This invention can simulate mandibular movement frame by frame and detect occlusal contact status in real time. It can automatically identify abnormal points such as premature contact and occlusal interference, and directly calculate the adjustment amount of the occlusal surface through the algorithm to complete the model optimization. It replaces manual experience judgment and repeated adjustments, shortens the design and manufacturing cycle, and improves repair efficiency and occlusal comfort.

[0023] This invention uses digital methods to complete the design, trial fitting, testing and optimization of the prosthesis throughout the entire process, reducing clinical operation steps and the number of patient visits, reducing the workload of doctors, and avoiding complications such as temporomandibular joint discomfort and occlusal trauma caused by malocclusion, thus improving the overall restoration effect and patient treatment experience. Attached Figure Description

[0024] Figure 1 This is a system block diagram of the present invention.

[0025] Figure 2 This is a flowchart illustrating the trajectory processing module of the present invention.

[0026] Figure 3 This is a flowchart illustrating the trial-wear simulation module and the anomaly optimization module of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] Please see Figures 1 to 3 As shown, the embodiments of the present invention provide the following technical solutions: As an embodiment of the present invention: This invention relates to a virtual fitting system for dental prostheses based on three-dimensional scanning, comprising: The data acquisition module is used to collect point cloud data of the patient's upper and lower jaws, select static reference points and their coordinates from the point cloud data, and generate a static three-dimensional dental arch model. In this embodiment, the dentition point cloud data is obtained by scanning the patient's upper and lower jaw dentition, gingiva, and edentulous tissues using an intraoral 3D scanner; The point cloud data of the upper and lower jaw dentition are denoted as P={P i}; in: P={P i} represents the point cloud set of all teeth in the original oral cavity scan; i = 1, 2, ..., n; P i For the i-th scan point, it encompasses the static three-dimensional coordinates [x (P)] corresponding to the scan point. i ),y(P i ),z(P i )]; And P∈{U=[U i1 ], L=[L i2 ]}; U=[U i1 [] represents the set of points in the maxillary dentition; i1=1,2,......,n1; u i1 This represents the i1th scan point on the maxillary dentition, which encompasses the corresponding static three-dimensional coordinates [x (U i1 ),y(U i1 ),z(U i1 [n] represents the total number of scanning points on the maxilla; L=[L i2 [] represents the set of points in the mandibular dentition; i2=1,2,......,n2; L i2 This represents the i2th scan point on the mandibular dentition, which encompasses the corresponding static three-dimensional coordinates [x (L i2 ),y(L i2 ),z(L) i2 [n2] represents the total number of scanning points on the mandible. Next, the point cloud data is denoised and triangulated to generate a static three-dimensional dental arch model, including the maxillary model MU and the mandibular model ML. In the maxillary model MU and the mandibular model ML, each triangular facet is formed by connecting three adjacent point cloud coordinates. In this embodiment, the denoising and triangulation processing methods are as follows: For each scan point P i Select a predetermined number of neighboring points to form a neighborhood set Q. i ={P j}; Where: j = 1, 2, ..., m; m is the number of neighborhood reference points; P j Indicated by P i Centered on the j-th neighboring point, the scan point corresponding to it covers the corresponding three-dimensional coordinates [x (P j ),y(P j ),z(P j )]; Then proceed as follows: Calculate scan point P i With each neighboring point P j Spatial distance L ij ; Subsequently passed: Count scan points P i Average distance LP to all neighboring points i ; Next, the average distance LP i Compare with the preset distance threshold L0: If the neighboring point P j Satisfying L ij >LP i If the value is +L0, it is identified as an isolated noise point and directly removed. After all points are determined, the denoised valid point cloud set P1={P1 k0}; Where: k0 = 1, 2, ..., u0; u0 is the number of valid points; the three-dimensional coordinates corresponding to P1 are [x (P1 k0 ),y(P1 k0 ),z(P1) k0 )]; Where P1∈{U1,L1}; U1 refers to the effective point cloud set of the maxilla; L1 refers to the effective point cloud set of the mandible; The combination involves traversing the effective point cloud P1 and sequentially selecting three points P1 that are spatially adjacent and have continuous surface trends. a P1 b P1 c , as the three vertices of the triangular face; Spatial proximity refers to the fact that the distance between any two of the three points in three-dimensional space is within a preset reasonable range. Continuous surface trend refers to the fact that the three points are located on the same smooth anatomical surface, with no abrupt changes or sharp angles.

[0029] Subsequently passed: Calculate P1 a P1 b P1 c The side length L between the three points is... ab L bc L ac ; In this embodiment, the side length of the triangular facet is set to a reasonable range, and only triangular facets with side lengths within the reasonable range are generated. Then, following the order from the inside to the outside of the dental arch, all valid points that do not form triangular patches are traversed, and new triangular patches are generated by continuously combining three adjacent points, so that adjacent triangular patches share common vertices and common edges, and the entire dental arch, gingiva and edentulous area surfaces are successively covered. Finally, all triangular patches generated from the effective point cloud set U1 of the maxilla are grouped into the maxillary triangular patch group; all triangular patches generated from the effective point cloud set L1 of the mandible are grouped into the mandible triangular patch group. The maxillary triangular facets and mandibular triangular facets are respectively topologically integrated and aggregated into a single complete curved surface structure, which is then encapsulated and shaped as a whole, resulting in the maxillary model MU and the mandibular model ML. Simultaneously, the following points were selected on the patient's dentition: the mastoid process of the maxillary incisors, the mesiobuccal apex of the bilateral maxillary first molars, the midpoint of the mandibular incisors, and the mesiobuccal apex of the bilateral mandibular first molars. These points were denoted as follows: Maxillary reference point set P U ={P U1 ,P U2 ,P U3 ,P U4 ,P U5}; Where: P U1 P is the incisal papilla point. U2 P U3 P is the mesiobuccal apex of the bilateral maxillary first molars. U4 P U5 Other auxiliary reference points for the maxilla; Mandibular reference point set P L ={P L1 ,P L2 ,P L3 ,P L4 ,P L5}; Where: P L1 P is the midpoint of the mandibular incisors. L2 P L3 P is the mesiobuccal apex of the bilateral mandibular first molars. L4 P L5 These serve as auxiliary reference points for the mandible.

[0030] For a static reference point, its three-dimensional coordinates at the maximum cusp intersection position are obtained and denoted as the static coordinate set ∈ {maxillary reference point set, mandibular reference point set}, where: P U1 The corresponding three-dimensional coordinates are [x (P) U1 ),y(P U1 ),z(P U1 ); P U2 The corresponding three-dimensional coordinates are [x (P) U2 ),y(P U2 ),z(P U2 ); P U3 The corresponding three-dimensional coordinates are [x (P) U3 ),y(P U3 ),z(P U3 ); P U4 The corresponding three-dimensional coordinates are [x (P)U4 ),y(P U4 ),z(P U4 ); P U5 The corresponding three-dimensional coordinates are [x (P) U5 ),y(P U5 ),z(P U5 ); P L1 The corresponding three-dimensional coordinates are [x (P) L1 ),y(P L1 ),z(P L1 ); P L2 The corresponding three-dimensional coordinates are [x (P) L2 ),y(P L2 ),z(P L2 ); P L3 The corresponding three-dimensional coordinates are [x (P) L3 ),y(P L3 ),z(P L3 ); P L4 The corresponding three-dimensional coordinates are [x (P) L4 ),y(P L4 ),z(P L4 ); P L5 The corresponding three-dimensional coordinates are [x (P) L5 ),y(P L5 ),z(P L5 ); In this embodiment, the maximum intercuspal position refers to the static state in which the patient keeps their mouth closed, teeth clenched normally, and mandible still. The trajectory processing module is used to collect the real-time coordinates of the static reference point of the patient's physiological mandibular movement, calculate the movement trajectory parameters, and construct a dynamic jaw position movement model. Includes the following steps: Step S1: Mandibular movement trajectory data acquisition: Guide the patient to complete multiple sets of physiological mandibular movements, including opening and closing movements, protrusion movements, left-side movements, and right-side movements, with each set of movements repeated multiple times; In this embodiment, the real-time three-dimensional coordinates of the static reference point corresponding to the jaw movement are acquired using existing optical motion capture equipment.

[0031] The working principle of optical motion capture equipment is as follows: by attaching reflective markers to the surface of the object being measured, multiple synchronous infrared cameras capture the position information of the markers from different perspectives in real time, and then the three-dimensional coordinates of the markers are calculated by the triangulation algorithm, thereby restoring the motion trajectory of the object in three-dimensional space.

[0032] The opening and closing movement refers to the reciprocating physiological movement of the mandible along the vertical direction, opening the mouth downwards and closing it upwards. Forward movement refers to the linear reciprocating movement of the entire mandible along the horizontal front-back direction, from a static occlusal position to a smooth forward extension and then back to the original position; Left-side movement refers to the lateral physiological movement in which the mandible slides horizontally to the left of the patient with the right side as the supporting side, and then returns to the central position. Right-side movement refers to the lateral physiological movement in which the mandible slides horizontally to the right of the patient with the left side as the supporting side, and then returns to the central position. Step S1.1: During the opening and closing motion, the real-time three-dimensional coordinate set of the static reference point corresponding to the k1th mandibular movement is denoted as: P L，k1 ={P L1，k1 (t),P L2，k1 (t),P L3，k1 (t),P L4，k1 (t),P L5，k1 (t)} Where: t=1,2,......,s; t is the time frame number during the movement; s is the total number of frames in a single movement; k1 represents the index of the number of physiological mandibular movements during the opening and closing movements; P L1，k1 The three-dimensional coordinates corresponding to (t) are [x (P) L1，k1 (t)),y(P L1，k1 (t)), z(P) L1，k1 (t)); P L2，k1 The three-dimensional coordinates corresponding to (t) are [x (P) L2，k1 (t)),y(P L2，k1 (t)), z(P) L2，k1 (t)); P L3，k1 The three-dimensional coordinates corresponding to (t) are [x (P) L3，k1 (t)),y(P L3，k1 (t)), z(P) L3，k1 (t)); P L4，k1 The three-dimensional coordinates corresponding to (t) are [x (P) L4，k1 (t)),y(P L4，k1 (t)), z(P) L4，k1 (t)); P L5，k1 The three-dimensional coordinates corresponding to (t) are [x (P) L5，k1 (t)),y(P L5，k1 (t)), z(P) L5，k1 (t)); In this embodiment, k1=1,2,3; P L1，k1 (t) represents the midpoint of the mandibular incisor at frame t during the k1th opening and closing motion; Step S1.2: During the forward extension movement, the real-time three-dimensional coordinate set of the static reference point corresponding to the k2th mandibular movement is denoted as: P L，k2 ={P L1，k2 (t),P L2，k2 (t),P L3，k2 (t),P L4，k2 (t),P L5，k2 (t)} Where: k2 represents the index of the number of physiological mandibular movements during the protrusion movement; P L1，k2 The three-dimensional coordinates corresponding to (t) are [x (P) L1，k2 (t)),y(P L1，k2 (t)), z(P) L1，k2 (t)); P L2，k2 The three-dimensional coordinates corresponding to (t) are [x (P) L2，k2 (t)),y(P L2，k2 (t)), z(P) L2，k2 (t)); P L3，k2 The three-dimensional coordinates corresponding to (t) are [x (P) L3，k2 (t)),y(P L3，k2 (t)), z(P) L3，k2 (t)); P L4，k2 The three-dimensional coordinates corresponding to (t) are [x (P) L4，k2 (t)),y(P L4，k2 (t)), z(P) L4，k2 (t)); P L5，k2 The three-dimensional coordinates corresponding to (t) are [x (P) L5，k2 (t)),y(P L5，k2 (t)), z(P) L5，k2 (t)); In this embodiment, k2 = 1, 2, 3; P L1，k2 (t) represents the midpoint of the mandibular incisor at frame t during the k2th forward movement; Step S1.3: During the left-side movement, the real-time three-dimensional coordinate set of the static reference point corresponding to the k3th mandibular movement is denoted as: P L，k ={P L1，k3 (t),P L2，k3 (t),P L3，k3 (t),P L4，k3 (t),P L5，k3 (t)} Where: k3 represents the index of the number of physiological mandibular movements during left-side movement; P L1，k3 The three-dimensional coordinates corresponding to (t) are [x (P) L1，k3 (t)),y(P L1，k3 (t)), z(P) L1，k3 (t)); P L2，k3 The three-dimensional coordinates corresponding to (t) are [x (P) L2，k3 (t)),y(P L2，k3 (t)), z(P) L2，k3 (t)); P L3，k3 The three-dimensional coordinates corresponding to (t) are [x (P) L3，k3 (t)),y(P L3，k3 (t)), z(P) L3，k3 (t)); P L4，k3 The three-dimensional coordinates corresponding to (t) are [x (P) L4，k3 (t)),y(P L4，k3 (t)), z(P) L4，k3 (t)); P L5，k3 The three-dimensional coordinates corresponding to (t) are [x (P) L5，k3 (t)),y(P L5，k3 (t)), z(P) L5，k3 (t)); In this embodiment, k3 = 1, 2, 3; P L1，k3 (t) represents the midpoint of the mandibular incisor at frame t during the k3rd leftward movement; Step S1.4: During the right-side movement, the real-time three-dimensional coordinate set of the static reference point corresponding to the k4th mandibular movement is denoted as: P L，k4 ={P L1，k4 (t),P L2，k4 (t),P L3，k4 (t),P L4，k4 (t),P L5，k4 (t)} Where: k4 represents the index of the number of physiological mandibular movements during right-side movement; P L1，k4 The three-dimensional coordinates corresponding to (t) are [x (P) L1，k4 (t)),y(P L1，k4 (t)), z(P) L1，k4 (t)); P L2，k4 The three-dimensional coordinates corresponding to (t) are [x (P) L2，k4 (t)),y(P L2，k4 (t)), z(P) L2，k4 (t)); P L3，k4 The three-dimensional coordinates corresponding to (t) are [x (P) L3，k4 (t)),y(P L3，k4 (t)), z(P) L3，k4 (t)); P L4，k4 The three-dimensional coordinates corresponding to (t) are [x (P) L4，k4 (t)),y(P L4，k4 (t)), z(P) L4，k4 (t)); P L5，k4 The three-dimensional coordinates corresponding to (t) are [x (P) L5，k4 (t)),y(P L5，k4 (t)), z(P) L5，k4 (t)); In this embodiment, k4 = 1, 2, 3; P L1，k4 (t) represents the midpoint of the mandibular incisor at frame t during the k4th right-side movement; Step S2, Calculation of motion trajectory parameters: Step S2.1, through: Calculate the vertical displacement D of the midpoint of the mandibular incisor at frame t during the opening and closing motion. k1 (t): Where: z(P) L1，k1 (t) represents the z-axis coordinate of the midpoint of the mandibular incisor at frame t, z(P) L1 () represents the z-axis coordinate of the midpoint of the mandibular incisor at the position of maximum cusp intersection; The vertical displacement D of the multiple opening and closing motions is then... k1 (t) Take the average value to obtain the mean value of the vertical displacement, and denot it as DP. k1 (t); Step S2.2, Pass: Calculate the anterior-posterior displacement D of the midpoint of the mandibular incisor at frame t during the protrusion motion. k2 (t); Where: x (P) L1，k2 (t) represents the x-axis coordinate of the midpoint of the mandibular incisor at frame t, where x(P) is the x-axis coordinate of the midpoint of the mandibular incisor at frame t. L1 () represents the x-axis coordinate of the midpoint of the mandibular incisor at the position of maximum cusp intersection; The forward and backward displacement D of multiple forward extension movements is then... k2 (t) Take the average value to obtain the average displacement before and after, and denot it as DP. k2 (t); Step S2.3, Pass: Calculate the leftward displacement D of the left cheek tip at frame t during the leftward motion. k3 (t); Where: y(P) L2，k3 (t) represents the y-axis coordinate of the right cheek tip at frame t; y(P) L2 () represents the y-coordinate of the left buccal cusp at the position of maximum cusp intersection; The lateral displacement D of multiple leftward movements is then... k3 (t) Take the average value to obtain the mean value of the leftward displacement, and denote it as DP. k3 (t); Step S2.4, Pass: Calculate the rightward displacement D of the right cheek tip at frame t during the rightward motion. k4 (t); Where: y(P) L3，k4 (t) represents the y-axis coordinate of the right cheek tip at frame t; y(P) is the y-axis coordinate of the right cheek tip at frame t. L3 () represents the y-coordinate of the right buccal cusp at the position of maximum cusp intersection; The lateral displacement D of multiple right-side movements is then... k4 (t) Take the average value to obtain the mean value of the rightward displacement, and denot it as DP. k4 (t); Step S3: Construction of dynamic jaw movement model: Based on the calculated motion trajectory parameters, a dynamic jaw movement model of the patient is constructed; The average vertical displacement, average anterior-posterior displacement, average lateral displacement, and average lateral displacement are integrated into the overall motion parameters of the mandibular model ML, and denoted as the motion parameter set ML(D) = {DP}. k1 (t),DP k2 (t),DP k3 (t),DP k4 (t)}; The model building module is used to design the basic model of the restoration based on the static dentition model and to establish a virtual occlusal surface reference coordinate system. Includes the following steps: Step G1: Construction of the basic model of the restoration: Based on the point cloud data of the dentition in the patient's edentulous area, and combined with the occlusal surface morphology of the opposing dentition, a basic model of the restoration is constructed, denoted as MR; In this embodiment, the occlusal surface of the opposing dentition refers to the occlusal contact surface of the teeth on the side requiring restoration, specifically the upper / lower or left / right opposing dentition. If the restoration is in the maxilla, the mandibular dentition is the opposing dentition; if the restoration is in the mandible, the maxilla is the opposing dentition. in: The initial morphology of the occlusal surface of the basic model of the restoration is initially fitted based on the occlusal surface contour of the opposing dentition. During the fitting process, the initial coordinates of each design point on the occlusal surface of the restoration are calculated with reference to the point cloud data of the opposing dentition. For each design point on the occlusal surface of the restoration, select the 3-5 scan points closest to the design point from the scan data of the occlusal surface of the opposing dentition, calculate the average value of the three-dimensional coordinates of these scan points, and use the average value as the initial coordinates of the design point on the occlusal surface of the restoration. Step G2: Establishing the virtual occlusal surface reference coordinate system: The set of maxillary reference points P of the maxillary dentition model MU U For reference, a reference coordinate system OXYZ for the virtual occlusal surface is established; in: The origin O of the coordinate system is taken as the midpoint of the line connecting the mesiobuccal cusps of the bilateral maxillary first molars, with coordinates O( , , ); The X-axis is the direction of the line connecting the mesiobuccal cusps of the bilateral maxillary first molars, i.e., the anterior-posterior direction; The Y-axis is the horizontal direction that passes through the origin and is perpendicular to the X-axis, i.e., the left-right direction; The Z-axis is the direction that passes through the origin and is perpendicular to the XY plane, i.e., the vertical direction.

[0033] This embodiment acquires data on the dentition and edentulous areas through intraoral 3D scanning. The data is then automatically denoised and triangulated to generate a precise and smooth 3D model, effectively eliminating noise interference. Simultaneously, key anatomical sites are selected as static benchmarks to obtain stable occlusal coordinates, providing a reliable reference for restorative design. The process is highly automated, and the model is realistic and accurate, laying a solid data and modeling foundation for digital restoration.

[0034] As a second embodiment of the present invention: In specific implementation, compared with Embodiment 1, the technical solution of this embodiment differs from that of Embodiment 1 only in that this embodiment further includes: The trial fitting simulation module is used to integrate the dynamic jaw movement model with the basic model of the prosthesis and the models of the upper and lower jaw dentition to construct a dynamic virtual trial fitting scene, simulate the patient's physiological jaw movement, and detect the occlusal contact status. Includes the following steps: Step K1, Spatial Registration and Positioning: The restoration's basic model (MR), mandibular dentition model (ML), and maxillary dentition model (MU) were imported into the same virtual scene, and initial registration was performed based on static jaw position reference points. Step K1.1: The maxillary model MU is fixed in the reference coordinate system, and its static reference point coordinates are the same as the set of maxillary reference points P. U ={P U1 ,P U2 ,P U3 ,P U4 ,P U5 The corresponding three-dimensional coordinates are completely consistent; Step K1.2: The MR model of the restoration is based on the point cloud data of the edentulous area and is fitted and located with the maxillary model or mandibular model. During the fitting process, the point cloud data of the edge of the edentulous area is used as a reference benchmark to calculate the spatial distance error between each point on the edge of the restoration model and the corresponding point on the edge of the edentulous area.

[0035] Specifically, all corresponding points between the edge of the restoration model and the edge of the edentulous area are traversed, and the three-dimensional spatial distance between each pair of points is calculated one by one. This distance is used as the fitting error value of that point. After the error calculation of all points is completed, the average value of all fitting error values ​​is calculated. When the average value is less than the preset fitting error threshold, the initial spatial positioning of the restoration model and the edentulous area is determined to be complete. In this embodiment, the bonding error threshold is set to 0.01 mm; Step K1.3: The mandibular model ML is initially registered with the maxillary model MU based on the static reference point, so that the mandibular and maxillary models are in the position of maximum cusp intersection; In this embodiment, the occlusal surfaces of the prosthesis base model and the opposing dentition model are in initial contact at this time; Step K2, Dynamic Mandibular Movement Simulation: In this embodiment, when the prosthesis is located in the mandible, the mandibular model ML and the basic model of the prosthesis are driven to perform motion simulation based on the motion parameter set ML(D) of the dynamic jaw position motion model; In this embodiment, the motion simulation process is executed frame by frame according to time frames t1=1,2,......,s1: The motion simulation method is as follows: Based on the calculation logic of motion trajectory parameters, the vertical displacement D of the midpoint of the mandibular incisor at frame t1 in the opening and closing motion simulation is determined. k1 (t1) The anterior-posterior displacement D of the midpoint of the mandibular incisor at frame t1 in the protrusion motion simulation. k2 (t1) The leftward displacement D of the left cheek tip at frame t1 during leftward movement. k3 (t1) and the rightward displacement D of the right cheek tip at frame t1 of the right-side motion. k4 (t1); In the simulation of mouth opening and closing movements, the initial vertical coordinates of each point on the static mandibular model are used as the basis, and the vertical displacement D is superimposed. k1 (t1) simulates the opening and closing movements of the mandibular model; In the simulation of protrusion movement, the initial anterior-posterior coordinates of each point on the static mandibular model are used as the basis, and the anterior-posterior displacement D is superimposed. k2 (t1) simulates the forward movement of the mandibular model; In the simulation of left-side movement, the initial left-side coordinates of each point on the static mandibular model are used as the basis, and the left-side displacement D is superimposed. k3 (t1) simulates the left-side movement of the mandibular model; During the simulation of right-side motion, the initial right-side coordinates of each point on the static mandibular model are used as a basis, and the right-side displacement D is superimposed. k4 (t1) simulates the right-side movement of the mandibular model; Step K3, Dynamic Occlusal Contact Analysis: At each time frame t1, the contact state between the occlusal surface of the restoration and the occlusal surface of the opposing dentition is detected, and the occlusal contact data is determined. Occlusal contact data refers to the positional coordinates of the contact points between the occlusal surfaces of the restoration and the opposing dentition, the corresponding motion time frames, and the shortest distance between each pair of triangular facets of the occlusal surfaces of the restoration and the opposing dentition. The contact status detection method is as follows: Traverse all triangular facets of the occlusal surface of the restoration, denoted as FR={FR h1}, where h1=1,2,......,g1, g1 is the total number of triangular facets on the occlusal surface of the restoration, and each triangular facet consists of three vertices VF. R1 VF R2 VF R3 composition; Traverse all triangular facets on the occlusal surfaces of the opposing dentition, denoted as FL={FL h2}, where h2=1,2,......,g2,g2,g2 is the total number of triangular facets on the occlusal surface of the opposing dentition, and each triangular facet consists of three vertices VF.L1 VF L2 VF L3 composition; Then, for each pair of triangular facets on the occlusal surface of the restoration and the occlusal surface of the opposing dentition, take any point from all points on the triangular facet of the restoration and any point from all points on the triangular facet of the opposing dentition, and calculate the three-dimensional spatial distance between the two points. Iterate through all possible combinations of points on the pair of triangular faces, take the minimum value among them, and determine the shortest distance between the pair of triangular faces, denoted as D(FR). h1 FL h2 ); Then find the shortest distance D (FR) between each pair of triangular faces. h1 FL h2 The contact threshold DY is compared with the preset contact threshold DY. When D(FR) h1 FL h2 When ) ≤ DY, it is determined that the pair of triangular facets are in contact, and the position coordinates of the contact point and the corresponding motion time frame are recorded.

[0036] This embodiment captures the patient's actual mandibular movements, enabling dynamic virtual fitting and occlusion testing. Precise model registration is achieved through a unified reference coordinate system, simulating functional movements frame by frame and detecting occlusal contact status, thus more closely resembling clinical reality. Compared to static simulation, the fitting is more realistic and the testing is more comprehensive, accurately reflecting the occlusion of the prosthesis during functional movements.

[0037] As an embodiment of the present invention: In its specific implementation, compared to Embodiment 1 and Embodiment 2, the technical solution of this embodiment is to combine the solutions of Embodiment 1 and Embodiment 2. The difference between the technical solution of this embodiment and Embodiment 1 and Embodiment 2 lies only in that this embodiment further includes: The anomaly optimization module optimizes and adjusts the occlusal surface of the prosthesis based on occlusal contact data obtained by simulating the patient's physiological mandibular movements in a dynamic virtual fitting scenario. The optimization and adjustment methods are as follows: Step F1, Abnormal Contact Status Identification: Abnormal contact states are identified for all recorded contact point data as follows: First, the contact point that appears in the initial stage of the opening and closing motion is determined to be the early contact point; The initial stage refers to the extremely short period of movement when the mandible is in a static occlusal position with the teeth fully clenched, just beginning to open its mouth downwards and before a significant opening amplitude has been produced. The criteria for this stage is that the midpoint of the mandibular incisors has just undergone vertical displacement and the displacement amount is within a preset range; the value of the extremely short period of movement is 0.2s.

[0038] Next, during the forward or lateral movement, if the contact point is located in the non-working side area of ​​the occlusal surface of the prosthesis, and the contact point occurs during the movement, it is determined to be an occlusal interference point.

[0039] In this embodiment, when the mandible moves to one side, the side of the tooth on the same side as the direction of movement is the working side, and the opposite side is the non-working side; on the occlusal surface of the restoration, the cusp slope on the non-working side is the non-working side region. Then, the early contact points and occlusal interference points were taken as abnormal contact points, and their number and location coordinates were determined, and they were correspondingly grouped into a set of early contact points and a set of occlusal interference points. Step F2, Calculation of occlusal surface adjustment: For each abnormal contact point, by: Calculate the adjustment amount Δh of the occlusal surface of the restoration, which is the thickness of material that needs to be removed from the occlusal surface of the restoration at this contact point; in: If Δh>0, it indicates that there is excessive occlusal contact at that point, and the occlusal surface of the restoration needs to be reduced. If Δh≤0, it means there is no abnormal contact at that point and no adjustment is needed.

[0040] Step F3, Model Iteration Update: Based on the calculated adjustment amount, the basic model of the restoration on the occlusal surface is updated as follows: For each early contact point in the early contact point set, find the triangular facet in the occlusal surface model of the restoration where it is located, and simultaneously reduce the corresponding occlusal surface adjustment amount by the vertical coordinates of the three vertices of the triangular facet. For each occlusal interference point in the set of occlusal interference points, find the triangular facet in the occlusal surface model of the prosthesis, and simultaneously reduce the corresponding occlusal surface adjustment amount by adjusting the vertical coordinates of the three vertices of the triangular facet. After adjusting all abnormal contact points, regenerate the basic model of the prosthesis and repeat the above-mentioned dynamic virtual fitting and contact status detection steps until there are no premature contacts or occlusal interferences at the contact points in all time frames, thus completing the optimization and adjustment of the occlusal surface of the prosthesis.

[0041] This embodiment can automatically identify abnormalities such as premature contact and occlusal interference, and intelligently adjust the occlusal surface of the prosthesis according to the calculation results, eliminating undesirable contacts through iterative optimization. It eliminates the need for repeated manual adjustments, reduces reliance on experience, effectively avoids occlusal high points and lateral interference, improves fit and wearing comfort, reduces postoperative discomfort, and makes the prosthesis more physiologically compliant.

[0042] As an embodiment of the present invention: In specific implementation, compared with Embodiment 1, Embodiment 2 and Embodiment 3, the technical solution of this embodiment is to combine the solutions of Embodiment 1, Embodiment 2 and Embodiment 3.

[0043] This embodiment integrates all modules to form a complete closed-loop virtual fitting system. From modeling, motion simulation, dynamic fitting to automatic optimization, it is completed in an integrated manner, with a high degree of digitalization and automation. It significantly improves the accuracy and efficiency of restorations, shortens the treatment cycle, reduces the number of follow-up visits, and achieves high-precision, intelligent, and more comfortable virtual fitting and optimization of oral restorations.

[0044] It should be stated that all user data collected in this application was collected with the user's consent and authorization, and the use of user data is legal and compliant, and the use and processing of user data comply with the relevant laws, regulations and standards of the relevant regions.

[0045] Furthermore, any content not described in detail in this specification is existing technology known to those skilled in the art.

[0046] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0047] The above formulas are all dimensionless calculations. Dimensionless calculation involves introducing a reference benchmark, such as the maximum, minimum, standard deviation, or theoretical extreme value of a physical quantity, to transform the original physical quantity into a dimensionless relative value. This value is usually mapped to a specific interval, such as [0,1] or [-1,1], which eliminates the influence of units while preserving the relative size relationship of the physical quantities. The formula is derived from software simulation based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0048] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

[0049] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A virtual fitting system for dental prostheses based on three-dimensional scanning, characterized in that, include: The data acquisition module is used to collect point cloud data of the patient's upper and lower jaws, select static reference points and their coordinates from the point cloud data, and generate a static three-dimensional dental arch model. The trajectory processing module is used to collect the real-time coordinates of the static reference points of the patient's physiological mandibular movements, calculate the motion trajectory parameters, and construct a dynamic jaw position movement model. The model building module is used to design the basic model of the restoration based on the static dentition model and to establish a virtual occlusal surface reference coordinate system. The trial fitting simulation module is used to integrate the dynamic jaw movement model with the basic model of the prosthesis and the model of the maxillary and mandibular dentition to construct a dynamic virtual trial fitting scene, simulate the patient's physiological mandibular movement and determine the occlusal contact data; The anomaly optimization module is used to optimize and adjust the occlusal surface of the prosthesis based on occlusal contact data.

2. The virtual fitting system for dental prostheses based on three-dimensional scanning according to claim 1, characterized in that: In the data acquisition module, the dentition point cloud data is obtained by scanning the patient's upper and lower jaw dentition, gums and edentulous tissues using an intraoral 3D scanner; Dental point cloud data is denoted as P={P i }, i=1,2,......,n,P i For the i-th scan point, it contains static three-dimensional coordinates [x (P i ),y(P i ),z(P i )], and P∈{U=[U i1 ], L=[L i2 ]}, where U is the set of point clouds for the maxillary dentition and L is the set of point clouds for the mandibular dentition; Meanwhile, the dental point cloud data is also subjected to noise reduction and triangulation processing. The method is as follows: for each scan point P i Select a preset number of neighboring points to form a neighborhood set Q i ={P j Then, using the three-dimensional Euclidean distance formula, P is calculated. i With neighboring point P j Spatial distance L ij And find the neighborhood points P of each neighborhood. j The average value is used to obtain the average distance LP. i Then L will be satisfied. ij >LP i The neighboring points of +L0 are identified as isolated noise points and removed to obtain an effective point cloud set P1; and L0 is a preset distance threshold.

3. The virtual fitting system for dental prostheses based on three-dimensional scanning according to claim 2, characterized in that: The data acquisition module traverses the effective point cloud set P1, selects three points that are spatially adjacent and have continuous surface trends as vertices of triangular facets, generates only triangular facets with side lengths within a pre-set reasonable range, and then topologically integrates them into the maxillary model MU and the mandibular model ML after tiling them in the order from the inside to the outside of the dental facets.

4. The virtual fitting system for dental prostheses based on three-dimensional scanning according to claim 3, characterized in that: The static reference points selected by the data acquisition module include: the maxillary incisor papilla, the mesiobuccal apex of the bilateral maxillary first molars, the midpoint of the mandibular incisors, and the mesiobuccal apex of the bilateral mandibular first molars, forming the maxillary reference point set P. U With the set of mandibular reference points P L And obtain the three-dimensional static coordinates under the maximum cusp intersection position.

5. The virtual fitting system for dental prostheses based on three-dimensional scanning according to claim 4, characterized in that: The physiological mandibular movements collected by the trajectory processing module include: opening and closing movements, forward protrusion movements, left-side movements, and right-side movements; Each set of movements is repeated multiple times, and the real-time three-dimensional coordinates of the static reference point are obtained through optical motion capture equipment. The motion trajectory parameters include: vertical displacement of the midpoint of the mandibular incisor during opening and closing movements, anterior-posterior displacement of the midpoint of the mandibular incisor during protrusion movements, leftward displacement of the left buccal tip during leftward movements, and rightward displacement of the right buccal tip during rightward movements. The average value of multiple motion results is used to form the motion parameter set of the dynamic jaw position motion model.

6. The virtual fitting system for dental prostheses based on three-dimensional scanning according to claim 5, characterized in that: When constructing the basic MR model of the restoration, the model building module uses the point cloud data of the occlusal surface of the opposing dentition as a reference, selects the nearest multiple scan points of the restoration design point, and takes the average coordinate as the initial coordinate of the occlusal surface design point of the restoration. In the virtual occlusal plane reference coordinate system OXYZ, the origin O is the midpoint of the line connecting the mesiobuccal cusps of the bilateral maxillary first molars, the X-axis is the anterior-posterior direction, the Y-axis is the lateral direction, and the Z-axis is the vertical direction.

7. A virtual fitting system for dental prostheses based on three-dimensional scanning according to claim 6, characterized in that: When the trial fitting simulation module performs spatial registration and positioning, the maxillary model MU is fixed in the reference coordinate system, and the initial positioning is completed when the average fitting error between the restoration base model MR and the edge of the edentulous area is less than the preset fitting error threshold; at the same time, the mandibular model ML and the maxillary model MU are registered to the maximum cusp intersection position; During the dynamic simulation of the fitting simulation module, the corresponding displacement is superimposed frame by frame according to the time frame, which drives the mandibular model to complete the simulation of opening and closing, protrusion, left side and right side movements respectively.

8. The virtual fitting system for dental prostheses based on three-dimensional scanning according to claim 7, characterized in that: When the trial fitting simulation module detects occlusal contact, it traverses the triangular facets of the occlusal surfaces of the restoration and the opposing dentition, and calculates the shortest distance for each pair of triangular facets. When the shortest distance of the triangular facets is less than or equal to a preset contact threshold, it is determined that the restoration is in contact, and the coordinates and time frame of the contact point are recorded.

9. A virtual fitting system for dental prostheses based on three-dimensional scanning according to claim 8, characterized in that: The optimization adjustment in the anomaly optimization module is as follows: the contact point when the opening and closing movement time is less than 0.2s is identified as the early contact point, and the contact point in the non-working side area during the forward / lateral movement is identified as the occlusal interference point, and the early contact point set and the occlusal interference point set are formed respectively.

10. A virtual fitting system for dental prostheses based on three-dimensional scanning according to claim 9, characterized in that: The optimization adjustment in the anomaly optimization module also calculates the adjustment amount of the occlusal surface of the restoration by subtracting the shortest distance of the triangular facet from the preset contact threshold. Simultaneously, the vertical coordinates of the vertices of the triangular facets containing the early contact point and the occlusal interference point are reduced accordingly, and iterative optimization is performed until there is no early contact or occlusal interference.

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