Prosthesis assembly effect evaluation and decision method, system, device and medium

Abstract

This invention discloses a method, system, device, and medium for evaluating and deciding on the assembly effect of prostheses, relating to the field of prosthesis data processing technology. Through three-dimensional data acquisition and intelligent fitting analysis, a multi-dimensional reference benchmark system is constructed, which can calculate precise assembly deviation values. A reference model is determined based on digital labels in the multi-dimensional benchmark model M1 and the solid reference combination model M2′; a test model is determined based on digital labels in the pre-fixation test model M3 and the post-fixation test model M4. Based on the reference model and the test model, pre-fixation assembly effect evaluation and post-fixation assembly effect evaluation are performed. This provides an intelligent multi-dimensional reference benchmark system and a hierarchical fitting strategy, enabling quantitative monitoring of the entire process of prosthesis placement, adjustment, and final fixation, covering the entire restoration process, truly reflecting its spatial assembly state within the mouth, and improving assembly accuracy.

Description

Technical Field

[0001] This invention relates to the field of assembly data processing technology, specifically to methods, systems, equipment, and media for evaluating and making decisions on the assembly effect of repairs. Background Technology

[0002] Tooth defects and missing teeth are common and frequently occurring oral diseases. They typically require restorations to reconstruct the complete shape of the damaged natural teeth and restore aesthetics, speech, and chewing function. After placement, the restoration should be in the designed position to avoid altering the occlusion and requiring additional occlusal adjustments. A "marginal-internal double seal" should be achieved to reduce the risk of microleakage, thus ensuring the long-term stability and effectiveness of the restoration. Therefore, post-placement verification of the restoration is crucial.

[0003] Traditional methods use probes or periapical radiographs to assess restoration placement. Probes have the following limitations: ① Low sensitivity: probes cannot identify potential gaps smaller than their tip diameter; ② Poor accessibility: probing angles are easily limited by tooth morphology and gingival margins, especially when the margin is subgingival; ③ Limited monitoring indicators: only marginal fit can be monitored; ④ Inappropriate probing force can easily lead to periodontal damage. Periapical radiographs have the following limitations: ① Limited shooting angle and range: when checking multiple teeth, a single imaging session cannot cover the entire upper restoration, and it is impossible to align with the long axis of all teeth; ② Limited imaging dimension: only two-dimensional images in the mesiodistal direction can be obtained, and three-dimensional placement deviation cannot be measured; ③ Image overlap: overlapping of labial (buccal) and lingual (palatal) images interferes with judgment; ④ Artifact interference: motion artifacts cause image blurring; ⑤ Low measurement efficiency: data must first be uploaded to specialized reading software, and measurements must be performed using the software's built-in tools. Therefore, traditional measurement methods are not suitable for assessing restoration placement. Summary of the Invention

[0004] The technical problems to be solved by this invention are: the probing method is limited by probe diameter, limited probing location, single monitoring indicators, and the risk of gingival injury during probing; the imaging method is limited by projection angle, image overlap, and the susceptibility to artifacts. The aim is to provide a method, system, equipment, and medium for evaluating and deciding on the fit of prostheses. Through three-dimensional data acquisition and intelligent fitting analysis, a multi-dimensional reference benchmark system is constructed, which can calculate accurate fit deviation values. By constructing reference models and test models, the fit effect is evaluated before and after fixation. An intelligent multi-dimensional reference benchmark system and hierarchical fitting strategy are provided, enabling quantitative monitoring of the entire process of prosthesis fitting, from trial fitting and adjustment to final fixation, covering the entire restoration process, truly reflecting its spatial fit status in the mouth, and improving fit accuracy.

[0005] This invention is achieved through the following technical solution: The first aspect of this invention provides a method for evaluating and deciding on the fitting effect of a prosthesis, comprising the following specific steps: Acquire preparatory body data and occlusal relationships, and construct a multidimensional baseline model M1; Obtain the solid reference state under processing and controlled assembly, and construct the solid reference combination model M2′; Based on the multidimensional benchmark model M1, a registration benchmark is established, and a pre-fixation test model M3 and a post-fixation test model M4 are constructed. Create digital labels for full anatomy, partial resection, and full resection; The reference model is determined in the multidimensional baseline model M1 and the entity reference combination model M2′ based on the digital labels; The test model is determined from the pre-fixation test model M3 and the post-fixation test model M4 based on the digital labels; Evaluation of pre-fixed assembly effect and post-fixed assembly effect based on reference model and test model; The pre-fixed assembly effect evaluation and the post-fixed assembly effect evaluation generate pre-fixed scenario decisions and post-fixed scenario decisions, respectively. The prosthesis is assembled based on the pre-fixation scenario decision and the post-fixation scenario decision.

[0006] Furthermore, the construction of the multidimensional benchmark model M1 specifically includes: Based on optical scanning to acquire pre-existing body data and occlusal relationships, a three-dimensional shape file of the restoration is designed, and three key areas of the restoration—occlusal surface, axial surface, and edge—are extracted and preset as digital evaluation benchmark areas. Associate clinically permissible tolerance rules for each region, where the target clearance for the edge region is c1, the target clearance for the axial region is c2, and the target clearance for the occlusal region is c3. The tolerance rules are automatically retrieved based on the digital tags for assembly, generating a three-dimensional file that is virtually assembled on the dental scan data according to the occlusal surface, axial surface and edge target gap, denoted as the multidimensional reference model M1.

[0007] Furthermore, the step of acquiring the entity reference state under processing and controlled assembly, and constructing the entity reference combination model M2′, specifically includes: The solid models of the restoration, the dentition, and the preparation were obtained separately. The solid models of the dentition and the preparation were optically scanned. The area of ​​the preparation exposed to the coronal aspect of the gingiva was selected for fitting to obtain the combined model M2 of the dentition and the preparation. Erase the data of the preparation area in M2, assemble the restoration onto the dental arch solid model, simulate the clinical fitting force, perform optical scanning on the controlled assembly restoration, pre-set digital evaluation benchmark areas for the restoration, and associate clinically permissible tolerance rules with each area to obtain the controlled assembly solid reference assembly model M2′. Furthermore, the construction of the pre-fixed test model M3 and test model M4 specifically includes: Call the existing digital model M1 and erase the data of the preparation area in the digital space; Before fixation, an optical scan was performed on the state of the prosthesis and the prepared body to obtain the test model M3 before fixation. After fixation is completed, the restoration area in M3 is erased, and only the fixed restoration area is optically scanned again to obtain the fixed test model M4, which includes the morphology of the fixed restoration and the prepared restoration.

[0008] Furthermore, the evaluation of the pre-assembly effect includes: When the digital label of the restoration is the full anatomical morphology: M1 is used as the reference model, M3 is used as the test model, the prepared body data in M3 is selected and the best fit is aligned with the prepared body data in M1; then the prepared body data in M3 is used as a fixed constraint to fit the restoration data in M1 and M3. When the digital label of the restoration is a partial or full resection pattern, M2′ is used as the reference model and M3 is used as the test model. The prepared body data in M3 is selected and best-fitted with the prepared body data in M2′. Then, the restored body data in M2′ and M3 are fitted with the prepared body data in M3 as a fixed constraint. Calculate the deviation between the surfaces of the prosthesis before fixation: Based on the reference model, display a color map showing the difference between the test model and the reference model. The part of the test model outside the surface of the reference model is displayed as a positive value, and the part of the test model inside the reference model is displayed as a negative value. When M1 is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M1; When M2′ is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M2′. Among them, the partition calculation and reporting of deviations for different reference models include the average deviation values ​​of three regions: edge region, axial surface and occlusal surface, which are denoted as b1, b2 and b3 respectively. Based on the sum of the average deviation value and the target gap value of the corresponding reference area, the actual gap values ​​between the restoration and the prepared body in the edge area, axial surface and occlusal surface are obtained, and are denoted as b1′, b2′ and b3′ respectively. The system automatically compares the actual gap value with the associated preset tolerance upper limit.

[0009] Furthermore, the evaluation of the assembly effect after fixation specifically includes: When the digital label of the restoration is the full anatomical morphology: M1 is used as the reference model, M4 is used as the test model, the prepared body data in M4 is selected and the best fit is aligned with the prepared body data in M1; then the prepared body data in M4 is used as a fixed constraint to fit the restoration data of M1 and M4. When the digital label of the restoration is a partial or full resection pattern, M2′ is used as the reference model and M4 is used as the test model. The prepared body data in M4 is selected and the best fit is aligned with the prepared body data in M2′. Then, the prepared body data in M4 is used as a fixed constraint to fit the restoration data in M2′ and M4. Calculate the deviation between the surfaces of the prosthesis before fixation: Based on the reference model, display a color map showing the difference between the test model and the reference model. The part of the test model outside the surface of the reference model is displayed as a positive value, and the part of the test model inside the reference model is displayed as a negative value. When M1 is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M1; When M2′ is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M2′. Among them, the partition calculation and reporting of deviations for different reference models include the average deviation values ​​of three regions: edge region, axial surface and occlusal surface, which are denoted as b1, b2 and b3 respectively. Based on the sum of the average deviation value and the target gap value of the corresponding reference area, the actual gap values ​​between the restoration and the prepared body in the edge area, axial surface and occlusal surface are obtained, and are denoted as b1′, b2′ and b3′ respectively. The system automatically compares the actual gap value with the associated preset tolerance upper limit.

[0010] Furthermore, the generation of the pre-fixed scene decision and the post-fixed scene decision specifically includes: Fixed-scene decision-making: If the actual gap values ​​of the three evaluation areas are all within the preset range, then the assembly is considered to be in place and can be prepared for fixing. If the actual gap value of at least one of the three evaluation areas exceeds the preset range, it will indicate that the assembly is not in place. The adjacent surfaces need to be checked, the actual gap adjusted, and then the scan and evaluation should be repeated until the conditions are met. Decision-making in a fixed scenario: If the actual gap values ​​of the three evaluation areas are all within the preset range, then the final assembly is determined to be in place and the restoration is successfully bonded. If the actual gap value in the edge area exceeds the preset range, it indicates that the adhesive layer is too thick. The restoration should be removed for adjustment and refixed. After adjustment, it should be scanned and evaluated again until the conditions are met. If the actual clearance value of the edge area is within the preset range, but the actual clearance of the shaft surface or / and the meshing surface exceeds the preset range, it is suggested to grind the area that exceeds the preset tolerance upper limit. The grinding amount can be calculated by the difference between the actual clearance value and the preset tolerance upper limit of the corresponding reference area. After adjustment, rescan and evaluate until the conditions are met.

[0011] The second aspect of the present invention provides a system applied to a method for evaluating and deciding on the assembly effect of a prosthesis, comprising: an intelligent design module for generating a prosthesis design file containing a threshold evaluation benchmark area and associated tolerance rules, and design morphology markers, and establishing a reference model M1 containing a preparatory body and a target gap therebetween; Data acquisition module: used to perform controlled scanning of solid models and process and generate structured solid reference combination model M2′; and to acquire pre-fixation test model M3 and post-fixation test model M4 of intraoral prosthesis; Data processing and analysis module: communicatively connected to the data acquisition module, comprising: Fitting engine: Used to automatically select a reference model based on the morphological markers of the restoration design, and execute the corresponding hierarchical constraint fitting strategy; Zoning calculation unit: used to calculate the characteristic deviation value and actual gap value of each zone based on a preset evaluation benchmark area; Rule comparison unit: used to automatically compare the calculated actual gap value with the preset tolerance rules in the design file; Decision and report generation module: Communicatively connected to the data processing and analysis module, it is used to automatically generate structured clinical decision recommendations for scenarios before and after prosthesis fixation based on rule comparison results, and output an evaluation report that integrates deviation diagrams, partitioned deviation data tables and decision recommendations.

[0012] A third aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for evaluating and deciding on the fitting effect of a prosthesis.

[0013] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for evaluating and deciding on the effect of prosthesis assembly.

[0014] Compared with the prior art, the present invention has the following advantages and beneficial effects: It can calculate precise deviation values, replacing inaccurate probing and imaging methods; by automatically comparing deviation values ​​with preset ranges, it provides clear guidance for pass / adjustment operations, optimizing the operational process; performing multiple assembly effect analyses on restorations before fixation helps avoid poor or even non-positioning caused by excessively tight contact between adjacent surfaces of the restoration; performing multiple assembly effect analyses on restorations after fixation helps avoid excessively thick adhesive layers on the tissue surface of the restoration, thereby avoiding adverse phenomena such as reduced adhesive strength and increased plaque adhesion; integrating data scanning, acquisition, loading, comparison, and decision-making into a single device increases the smoothness of the process, eliminating the need to switch between different software and platforms; assembly effect analysis is based on three-dimensional data, rather than two-dimensional projection, and the analysis scope covers the entire restoration, reflecting its true assembly deviation. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 This is a flowchart illustrating the overall process for evaluating and deciding on the prosthesis assembly effect in this invention embodiment. Figure 2 This is a diagram illustrating the structure of the prosthesis assembly effect evaluation and decision-making system in an embodiment of the present invention; Figure 3 This is a hardware structure diagram of a computer device in an embodiment of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0017] Example 1, as one possible implementation, such as Figure 1 As shown in the figure, this embodiment provides a method for evaluating and deciding on the fitting effect of a prosthesis. The specific implementation process is as follows: (1) Generate intelligent design documents and multi-dimensional reference models that bear the assessment knowledge: Based on optical scanning to acquire pre-existing prosthesis data and occlusal relationships, a three-dimensional shape file for the restoration is designed. The core innovation of this step lies in the pre-defined structured assessment knowledge, in addition to geometric structure, including: ① Embedded assessment benchmark areas: Digital assessment benchmark areas are pre-defined for the three key areas of the restoration: occlusal surface, axial surface, and margin. ② Associated tolerance rules: Associated clinically permissible tolerance rules for each region. The target gap for the edge region is c1, with an allowable range of 0.05mm to 0.12mm; the target gap for the axial surface region is c2, with an allowable range of 0.06mm to 0.15mm; and the target gap for the occlusal surface region is c3, with an allowable range of 0.06mm to 0.15mm.

[0018] ③ Labeling design morphology: Create digital labels for full anatomy, partial resection, and full resection.

[0019] ④ Generate reference model: Based on the digital tags, the tolerance rules are automatically retrieved for assembly, and a three-dimensional file of the restoration is generated that is virtually assembled on the dental arch scan data according to the target gaps of the margin, axial surface and occlusal surface. This file is denoted as reference model M1. This model includes the morphology of the restoration and the prepared restoration. (2) Obtaining the reference state of the entity under machining and controlled assembly: Computer-aided manufacturing processes were used to produce solid restorations, solid models of the dental arch, and solid models of prepared restorations.

[0020] ① Obtain the combined model M2 of the dentition and preparation: Obtain the solid models of the restoration, the dentition, and the preparation, respectively. Perform optical scanning on the solid models of the dentition and the preparation, and select the area of ​​the preparation exposed on the coronal side of the gingiva for fitting.

[0021] ② Obtaining a controlled assembly reference model: Under the guidance of a guide plate, a quantifiable light load (a clamp controlled by a 5N force sensor) is used to simulate the clinical fitting force to assemble the restoration onto the dental arch model. The restoration is fabricated using computer-aided manufacturing processes. Based on the M2 model, the data of the prepared restoration area is erased, and the controlled assembly restoration is optically scanned to obtain the dental arch model data containing the restoration.

[0022] ③ Data processing: A digital assessment benchmark area is pre-defined for the prosthesis, and clinically permissible tolerance rules are associated with each area to obtain a controlled assembly entity reference combination model M2′. A structured entity reference combination model M2′ is established, which records the real spatial relationship between the prosthesis and the prepared body under controlled conditions.

[0023] (3) Data collection during intraoral clinical assembly: Call M1, erase the prepared body data in M1, and perform an optical scan only on the restoration area: ① Before final fixation (such as bonding), perform optical scanning to obtain a pre-fixation test model M3, which includes the morphology of the pre-fixation restoration and the prepared body; ② After fixation is completed, the restoration area in M3 is erased, and only the fixed restoration area is optically scanned again to obtain the fixed test model M4. This model includes the morphology of the fixed restoration and the prepared restoration. (4) Evaluation of restoration fit based on graded fitting: ① Evaluation of the pre-assembly effect (evaluation of the placement status); Fitting strategy: a. If the restoration is identified as having a fully anatomical morphology: Using M1 as the reference model and M3 as the test model, select the prepared restoration data from M3 and perform best-fit alignment with the prepared restoration data from M1. Since the two prepared restoration data are identical, accurate fitting can be achieved. Then, using the prepared restoration data from M3 as a fixed constraint, fit the restoration data from M1 and M3.

[0024] b. If the restoration is identified as partially or fully retracted, using M2′ as the reference model and M3 as the test model, select the prepared restoration data from M3 and perform best-fit alignment with the prepared restoration data from M2′. Then, using the prepared restoration data from M3 as a fixed constraint, fit the restoration data from M2′ and M3.

[0025] Analysis and Output: a. Calculate the deviation between the surfaces of the prosthesis before fixation. Based on the reference model, display a color map showing the difference between the test model and the reference model. The part of the test model that is outside the surface of the reference model is displayed as a positive value, and the part of the test model that is inside the reference model is displayed as a negative value.

[0026] b. When M1 is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M1; when M2′ is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M2′; wherein, the deviation calculation and reporting for different reference models includes the average deviation values ​​of the three regions of edge area, axial surface and occlusal surface, which are denoted as b1, b2 and b3 respectively.

[0027] c. Sum the above deviations with the target gap values ​​of the corresponding reference areas to obtain the actual gap values ​​between the restoration and the prepared body in the edge area, axial surface, and occlusal surface, respectively, and record them as b1′, b2′, and b3′.

[0028] d. Automatically compare the actual gap values ​​calculated for the above-mentioned partitions with the associated preset tolerance upper limit. The preset tolerance upper limit can be determined according to current academic consensus: when the distance between the edge of the restoration and the prepared abutment tooth does not exceed 120μm after the restoration is in place, it is considered clinically acceptable. 120μm is the consensus description of the deviation threshold of the marginal zone. When deviation occurs in the marginal zone of the restoration, deviation will also occur on its axial and occlusal surfaces. Therefore, this plan also presets upper limits for tolerances on the axial and occlusal surfaces. However, it should be noted that with the improvement of restoration processing precision and the development of bonding technology, as well as the differences in different application scenarios, the fit of the restoration will be adjusted accordingly, that is, the deviation at the edge will also be adjusted, and the preset tolerance upper limit will also be adjusted accordingly. Therefore, no specific value is specified here.

[0029] ② Evaluation of the assembly effect after fixation (evaluate the final state and the influence of adhesive curing); Fitting strategy: a. If the restoration is identified as having a fully anatomical morphology: Using M1 as the reference model and M4 as the test model, select the prepared restoration data from M4 and perform best-fit alignment with the prepared restoration data from M1. Since the two prepared restoration data are identical, accurate fitting can be achieved. Then, using the prepared restoration data from M4 as a fixed constraint, fit the restoration data from M1 and M4.

[0030] b. If the restoration is identified as partially or fully retracted, using M2′ as the reference model and M4 as the test model, select the prepared restoration data from M4 and perform best-fit alignment with the prepared restoration data from M2′. Then, using the prepared restoration data from M4 as a fixed constraint, fit the restoration data from M2′ and M4.

[0031] Analysis and Output: a. Calculate the deviation between the surfaces of the fixation prosthesis. Based on the reference model, display a color map showing the difference between the test model and the reference model. The part of the test model that is outside the surface of the reference model is displayed as a positive value, and the part of the test model that is inside the reference model is displayed as a negative value.

[0032] b. When M1 is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M1; when M2′ is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M2′; wherein, the deviation calculation and reporting for different reference models includes the average deviation values ​​of the three regions of edge area, axial surface and occlusal surface, which are denoted as b1, b2 and b3 respectively.

[0033] c. Sum the above deviations with the target gap values ​​of the corresponding reference areas to obtain the actual gap values ​​between the restoration and the prepared body in the edge area, axial surface, and occlusal surface, respectively, and record them as b1′, b2′, and b3′.

[0034] d. Automatically compare the actual gap values ​​calculated for the above partitions with the associated preset tolerance upper limit.

[0035] (5) Rule-based intelligent decision-making methods: The decision is generated based on the automated comparison results between the actual gap value data of the structured partition and the preset tolerance rules in step (4).

[0036] ① Decisions made in the current context; a. If the actual gap values ​​of the three evaluation areas are all within the preset range, then it is determined that "the assembly is in place and can be prepared for fixing".

[0037] b. If the actual gap value of at least one of the three assessment areas exceeds the preset range, which could be any one, two, or all of the marginal area, axial surface, and occlusal surface, the message "Not properly assembled; check adjacent surfaces and make adjustments" will be displayed. After adjustment, rescan and assess until the conditions are met. The preset range refers to the interval from 0 to the preset upper tolerance limit. When the deviations of the three assessment areas (marginal area, axial surface, and occlusal surface) are all within the preset range, it indicates that none of the deviations exceed the preset upper tolerance limit, which is considered clinically acceptable. The specific values ​​are determined based on the actual clinical situation.

[0038] ② Decision-making in a fixed scenario; a. If the actual gap values ​​of the three assessment areas are all within the preset range, then it is determined that "the final assembly is in place and the restoration is successfully bonded".

[0039] b. If the actual gap value in the edge area exceeds the upper limit, the message "Adhesive layer too thick, it is recommended to remove the restoration, clean it, reduce the amount of adhesive used, and refix it" will be displayed. After adjustment, rescan and evaluate until the conditions are met.

[0040] c. If the actual clearance value of the edge area is within the preset range, but the actual clearance of the shaft surface or (and) the mating surface exceeds the preset range, a message will be displayed: "It is recommended to grind the area exceeding the preset tolerance upper limit." The grinding amount can be calculated by the difference between the actual clearance value and the preset tolerance upper limit of the corresponding reference area. After adjustment, rescan and evaluate until the conditions are met.

[0041] In some possible embodiments, the restoration can be a natural tooth or implant-supported post, post core, post core crown, crown, bridge, veneer, inlay, partial crown, or implant-supported abutment, abutment-integrated crown, or pre-bonded adhesive-screw composite retention crown.

[0042] In some possible embodiments, when the prosthesis is an implant-supported abutment, an integrated abutment crown, or a pre-bonded adhesive-screw composite retention crown, the deviations b1, b2, and b3 of the three regions of the edge, axial surface, and occlusal surface can be directly used for judgment, and the target gap value is set to 0.

[0043] In some possible embodiments, the reference model M2′ can also be loaded and compared in the following ways.

[0044] Method (1): After the restoration is assembled onto the model entity, it is used as a preoperative scan for optical scanning; after the restoration is assembled into the intraoral dentition, the order is called, the existing scan data of the restoration location is deleted, and optical scanning is performed again; data matching is performed by the common tooth morphological features of the intraoral dentition and the model to obtain composite data of the fused model entity and the intraoral assembled restoration; the restoration model assembly state in the preoperative scan is the reference model, and the restoration intraoral assembly state in the subsequent scan is the test model; the surface deviation of the restoration in the two models is compared.

[0045] Method (2): After the restoration is assembled onto the model entity, it is used as a working jaw for optical scanning; after the restoration is assembled onto the intraoral dentition, it is used as an opposing jaw for optical scanning; in the occlusal scanning module, data matching is performed based on the common tooth morphological features of the intraoral dentition and the model; the surface deviation of the restoration is calculated using the occlusal space monitoring function.

[0046] Example 2, as a possible implementation, provides a method for evaluating and deciding on the fit of a prosthesis based on the assessment and decision-making process applied to the final state of the injectable body. When this method is applied to the assessment and decision-making of the final state of the injectable body, since the injectable body is directly fixed inside the mouth, only the evaluation of the post-fixation scenario needs to be performed. It mainly includes: (1) Generate intelligent design documents and multi-dimensional reference models that bear the assessment knowledge: Based on the raw tooth data and occlusal relationship obtained from optical scanning, a three-dimensional shape file for the restoration is designed. The core innovation of this step lies in the pre-defined structured assessment knowledge, in addition to the geometric structure, including: ① Embedded assessment benchmark areas: Digital assessment benchmark areas are pre-defined for the three key areas of the restoration: occlusal surface, axial surface, and margin. ② Associated tolerance rules: Associated clinically permissible tolerance rules for each region. The target gaps for the marginal zone, axial surface, and occlusal surface are all set to 0. The permissible range for the marginal zone and axial surface is set to 0 to 50 μm, and the permissible range for the occlusal surface is set to 0 to 10 μm.

[0047] ③ Marking the design morphology: The injection body is generally in its full anatomical form, so a corresponding numerical label is directly created.

[0048] ④ Generate reference model: Generate a 3D file of the restoration virtually assembled on the dental scan data according to the target gaps of the margins, axial surfaces and occlusal surfaces, denoted as reference model M1. This model contains the restoration and the original tooth morphology. (2) Data collection during intraoral clinical assembly: Call M1, erase the original tooth data in M1, and after fixation, perform optical scanning only on the restoration area to obtain the post-fixation test model M4, which includes the post-fixation restoration and the original tooth morphology. (3) Evaluation of restoration fitting effect based on hierarchical fitting: Evaluation of the assembly effect after fixation (evaluation of the final state and the impact of the cured injection body); Fitting strategy: The restorations were identified as having a full anatomical morphology: using M1 as the reference model and M4 as the test model, the original tooth data from M4 was selected and best-fitted with the original tooth data from M1. Since the original teeth in both datasets are the same, accurate fitting can be achieved based on this. Then, using the original tooth data from M4 as a fixed constraint, the restoration data from M1 and M4 were fitted.

[0049] Analysis and Output: a. Calculate the deviation between the surfaces of the fixation prosthesis. Based on the reference model, display a color map showing the difference between the test model and the reference model. The part of the test model that is outside the surface of the reference model is displayed as a positive value, and the part of the test model that is inside the reference model is displayed as a negative value.

[0050] b. The system calculates and reports the deviations based on the preset evaluation reference area in M1, including the average deviation values ​​of the three areas: the edge area, the axial surface, and the occlusal surface, which are recorded as b1, b2, and b3, respectively.

[0051] c. Sum the above deviations with the target gap values ​​of the corresponding reference areas to obtain the actual gap values ​​between the restoration and the prepared body in the edge area, axial surface, and occlusal surface, respectively, and record them as b1′, b2′, and b3′.

[0052] d. Automatically compare the actual gap values ​​calculated for the above partitions with the associated tolerance rules.

[0053] (4) Rule-based intelligent decision-making methods: The decision in the fixed scenario is invoked, and the automatic comparison results of the actual gap value data of the structured partition in step (3) and the preset tolerance rules are generated.

[0054] a. If the actual gap values ​​of the three assessment areas are all within the preset range, then it is determined that "the final assembly is in place and the prosthesis injection is successful".

[0055] b. If the actual gap value in the edge area exceeds the upper limit, the message "Injection body too thick; it is recommended to grind the area exceeding the preset tolerance upper limit" will be displayed. The grinding amount can be calculated by the difference between the actual gap value and the corresponding reference area's preset tolerance upper limit. After adjustment, rescan and evaluate until the conditions are met.

[0056] (5) Complete the assembly of the prosthesis; Based on the decision-making system's conclusion that "final assembly is in place and prosthesis injection is successful," the final clinical treatment of the prosthesis is completed.

[0057] Example 3, as one possible implementation, such as Figure 2 As shown, this embodiment provides a system applied to the evaluation and decision-making method of prosthesis assembly effect, including: Intelligent design module: used to generate restoration design files containing threshold evaluation benchmark areas and associated tolerance rules, design morphology markers, and to establish a reference model M1 containing a preparatory body and a target gap set therewith.

[0058] Data acquisition module: used to perform controlled scanning of solid models and process and generate structured solid reference combination model M2′; and to acquire pre-fixation test model M3 and post-fixation test model M4 of intraoral prosthesis; Data processing and analysis module: communicatively connected to the data acquisition module, comprising: Fitting Engine: Used to automatically select a reference model (M1 or M2′) based on the morphological markers of the prosthesis design, and execute the corresponding hierarchical constraint fitting strategy.

[0059] Zonal Calculation Unit: Used to calculate the characteristic deviation value and actual gap value of each zone based on a preset evaluation benchmark area.

[0060] Rule comparison unit: used to automatically compare the calculated actual gap value with the preset tolerance rules in the design file.

[0061] The decision and report generation module communicates with the data processing and analysis module and is used to automatically generate structured clinical decision recommendations based on the rule comparison results. For scenarios before restoration fixation, the recommendations include "Assembled in place, ready for fixation" and "Not assembled in place, need to check adjacent surfaces and adjust if necessary". For scenarios after restoration fixation, the recommendations include "Final assembly in place, restoration successfully bonded", "Adhesive layer too thick, it is recommended to remove the restoration, clean it, reduce the amount of adhesive, and re-fix it", and "It is recommended to grind down areas exceeding the preset tolerance limit". The module also outputs an evaluation report that integrates deviation diagrams, zonal deviation data tables, and decision recommendations.

[0062] Example 4, as a possible implementation, provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a method for evaluating and deciding on the effect of prosthesis assembly.

[0063] Example 5, as a possible implementation, provides a computer-readable storage medium storing a computer program thereon. When the program is executed by a processor, it implements a method for evaluating and deciding on the fitting effect of a prosthesis. The storage medium can be any entity or terminal capable of storing program code, such as ROM, RAM, disk, optical disk, flash memory, etc.

[0064] Example 6, as Figure 3 As shown, this embodiment provides a computer hardware device, which is a hardware entity used to implement the aforementioned method for evaluating and deciding on the fitting effect of prosthesis. Its core includes: (1) Processor: The computing and control core of the device, used to execute computer program instructions stored in the memory, specifically to run the "prosthetic assembly effect evaluation and decision-making program", thereby completing all logical operations from data comparison, deviation calculation to effect evaluation and decision-making.

[0065] (2) Memory: Used to store program instructions and data. Includes: Read-only memory / firmware: Basic instructions for the storage system.

[0066] Random Access Memory (RAM): Serves as temporary storage and working space for programs during system operation.

[0067] Storage media (disk, flash memory, etc.): used to persistently store the "Prosthesis Assembly Effect Evaluation and Decision-Making Procedure" and related three-dimensional data (reference models M1, M2′, test models M3, M4), configuration parameters (tolerance rules) and calculation results (calculated deviations b1, b2, b3 and actual gap values ​​b1′, b2′, b3′ for different reference areas).

[0068] (3) System bus: connects the processor, memory and various interfaces, and is responsible for the transmission of data, address and control signals between components.

[0069] (4) Input / output interface: Connects various peripherals, such as optical scanners for acquiring 3D scanning data, display devices for displaying evaluation results (color maps, reports), and input devices such as keyboards and mice.

[0070] (5) Network interface: Optional component, used to connect to the network, enabling data exchange with cloud servers or databases, facilitating remote access to reference data or storage of evaluation reports.

[0071] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating and deciding on the fit of a prosthesis, characterized in that, The specific steps include the following: Acquire preparatory body data and occlusal relationships, and construct a multidimensional baseline model M1; Obtain the solid reference state under processing and controlled assembly, and construct the solid reference combination model M2′; Based on the multidimensional benchmark model M1, a registration benchmark is established, and a pre-fixation test model M3 and a post-fixation test model M4 are constructed. Create digital labels for full anatomy, partial resection, and full resection; The reference model is determined in the multidimensional baseline model M1 and the entity reference combination model M2′ based on the digital labels; The test model is determined from the pre-fixation test model M3 and the post-fixation test model M4 based on the digital labels; Evaluation of pre-fixed assembly effect and post-fixed assembly effect based on reference model and test model; Based on the pre-fixed assembly effect evaluation and the post-fixed assembly effect evaluation, the pre-fixed scenario decision and the post-fixed scenario decision are generated respectively. The prosthesis is assembled based on the pre-fixation scenario decision and the post-fixation scenario decision.

2. The method for evaluating and deciding on the fitting effect of the prosthesis according to claim 1, characterized in that, The construction of the multidimensional baseline model M1 specifically includes: Based on optical scanning to acquire pre-existing body data and occlusal relationships, a three-dimensional shape file of the restoration is designed, and three key areas of the restoration—occlusal surface, axial surface, and edge—are extracted and preset as digital evaluation benchmark areas. Associate clinically permissible tolerance rules for each region, where the target clearance for the edge region is c1, the target clearance for the axial region is c2, and the target clearance for the occlusal region is c3. The tolerance rules are automatically retrieved based on the digital tags for assembly, generating a three-dimensional file that is virtually assembled on the dental scan data according to the occlusal surface, axial surface and edge target gap, denoted as the multidimensional reference model M1.

3. The method for evaluating and deciding on the fitting effect of the prosthesis according to claim 1, characterized in that, The process of acquiring the entity reference state under processing and controlled assembly, and constructing the entity reference combination model M2′, specifically includes: The solid models of the restoration, the dentition, and the preparation were obtained separately. The solid models of the dentition and the preparation were optically scanned. The area of ​​the preparation exposed to the coronal aspect of the gingiva was selected for fitting to obtain the combined model M2 of the dentition and the preparation. Erase the data of the preparation area in M2, assemble the restoration onto the dental arch solid model, simulate the clinical fitting force, perform optical scanning on the controlled assembly restoration, pre-define the digital evaluation benchmark area for the restoration, and associate each area with clinically permissible tolerance rules to obtain the controlled assembly solid reference assembly model M2′.

4. The method for evaluating and deciding on the fitting effect of the prosthesis according to claim 1, characterized in that, The construction of the pre-fixed test model M3 and test model M4 specifically includes: Call the existing digital model M1 and erase the data of the preparation area in the digital space; Before fixation, an optical scan was performed on the state of the prosthesis and the prepared body to obtain the test model M3 before fixation. After fixation is completed, the restoration area in M3 is erased, and only the fixed restoration area is optically scanned again to obtain the fixed test model M4, which includes the morphology of the fixed restoration and the prepared restoration.

5. The method for evaluating and deciding on the fitting effect of the prosthesis according to claim 1, characterized in that, The evaluation of the pre-assembly effect includes: When the digital label of the restoration is the full anatomical morphology: M1 is used as the reference model, M3 is used as the test model, the prepared body data in M3 is selected and the best fit is aligned with the prepared body data in M1; then the prepared body data in M3 is used as a fixed constraint to fit the restoration data in M1 and M3. When the digital label of the restoration is a partial or full resection pattern, M2′ is used as the reference model and M3 is used as the test model. The prepared body data in M3 is selected and best-fitted with the prepared body data in M2′. Then, the restored body data in M2′ and M3 are fitted with the prepared body data in M3 as a fixed constraint. Calculate the deviation between the surfaces of the prosthesis before fixation: Based on the reference model, display a color map showing the difference between the test model and the reference model. The part of the test model outside the surface of the reference model is displayed as a positive value, and the part of the test model inside the reference model is displayed as a negative value. When M1 is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M1; When M2′ is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M2′. Among them, the partition calculation and reporting of deviations for different reference models include the average deviation values ​​of three regions: edge region, axial surface and occlusal surface, which are denoted as b1, b2 and b3 respectively. Based on the sum of the average deviation value and the target gap value of the corresponding reference area, the actual gap values ​​between the restoration and the prepared body in the edge area, axial surface and occlusal surface are obtained, and are denoted as b1′, b2′ and b3′ respectively. The system automatically compares the actual gap value with the associated preset tolerance upper limit.

6. The method for evaluating and deciding on the fitting effect of the prosthesis according to claim 5, characterized in that, The evaluation of the post-fixation assembly effect specifically includes: When the digital label of the restoration is the full anatomical morphology: M1 is used as the reference model, M4 is used as the test model, the prepared body data in M4 is selected and the best fit is aligned with the prepared body data in M1; then the prepared body data in M4 is used as a fixed constraint to fit the restoration data of M1 and M4. When the digital label of the restoration is a partial or full resection pattern, M2′ is used as the reference model and M4 is used as the test model. The prepared body data in M4 is selected and the best fit is aligned with the prepared body data in M2′. Then, the prepared body data in M4 is used as a fixed constraint to fit the restoration data in M2′ and M4. Calculate the deviation between the surfaces of the prosthesis before fixation: Based on the reference model, display a color map showing the difference between the test model and the reference model. The part of the test model outside the surface of the reference model is displayed as a positive value, and the part of the test model inside the reference model is displayed as a negative value. When M1 is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M1; When M2′ is used as the reference model, the deviation is calculated and reported according to the preset evaluation benchmark area in M2′. Among them, the partition calculation and reporting of deviations for different reference models include the average deviation values ​​of three regions: edge region, axial surface and occlusal surface, which are denoted as b1, b2 and b3 respectively. Based on the sum of the average deviation value and the target gap value of the corresponding reference area, the actual gap values ​​between the restoration and the prepared body in the edge area, axial surface and occlusal surface are obtained, and are denoted as b1′, b2′ and b3′ respectively. The system automatically compares the actual gap value with the associated preset tolerance upper limit.

7. The method for evaluating and deciding on the fitting effect of the prosthesis according to claim 6, characterized in that, The generation of the pre-fixed scenario decision and the post-fixed scenario decision specifically includes: Fixed-scene decision-making: If the actual gap values ​​of the three evaluation areas are all within the preset range, then the assembly is considered to be in place and can be prepared for fixing. If the actual gap value of at least one of the three evaluation areas exceeds the preset range, it will indicate that the assembly is not in place. The adjacent surfaces need to be checked, the actual gap adjusted, and then the scan and evaluation should be repeated until the conditions are met. Decision-making in a fixed scenario: If the actual gap values ​​of the three evaluation areas are all within the preset range, then the final assembly is determined to be in place and the restoration is successfully bonded. If the actual gap value in the edge area exceeds the preset range, it indicates that the adhesive layer is too thick. The restoration should be removed for adjustment and refixed. After adjustment, it should be scanned and evaluated again until the conditions are met. If the actual clearance value of the edge area is within the preset range, but the actual clearance of the shaft surface or / and the meshing surface exceeds the preset range, it is suggested to grind the area that exceeds the preset tolerance upper limit. The grinding amount can be calculated by the difference between the actual clearance value and the preset tolerance upper limit of the corresponding reference area. After adjustment, rescan and evaluate until the conditions are met.

8. A system applied to the method for evaluating and deciding on the fit of a prosthesis as described in any one of claims 1 to 7, characterized in that, include: Intelligent design module: used to generate restoration design files containing threshold evaluation benchmark areas and associated tolerance rules, design morphology markers, and to establish a reference model M1 containing the preparatory body and the target gap set therewith; Data acquisition module: used to perform controlled scanning of solid models and process and generate structured solid reference combination model M2′; and to acquire pre-fixation test model M3 and post-fixation test model M4 of intraoral prosthesis; Data processing and analysis module: communicatively connected to the data acquisition module, comprising: Fitting engine: Used to automatically select a reference model based on the morphological markers of the restoration design, and execute the corresponding hierarchical constraint fitting strategy; Zoning calculation unit: used to calculate the characteristic deviation value and actual gap value of each zone based on a preset evaluation benchmark area; Rule comparison unit: used to automatically compare the calculated actual gap value with the preset tolerance rules in the design file; Decision and report generation module: Communicatively connected to the data processing and analysis module, it is used to automatically generate structured clinical decision recommendations for scenarios before and after prosthesis fixation based on rule comparison results, and output an evaluation report that integrates deviation diagrams, partitioned deviation data tables and decision recommendations.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the restoration assembly effect evaluation and decision-making method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the restoration assembly effect evaluation and decision-making method as described in any one of claims 1 to 7.

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