A digital dental restoration three-dimensional color prediction method, system, device, medium and product
By establishing a color-thickness function model and using experimental data to regress and calculate the color parameters of the restoration, the problem of quantitative prediction of restoration color in the design stage was solved, and the accurate prediction and adjustment of restoration color in digital design and manufacturing was realized.
Patent Information
- Application Number
- CN202610790202.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-03
- Publication Date
- 2026-08-25
AI Technical Summary
In existing technologies, it is difficult to accurately predict the color of restorations during the design phase. In particular, there is a lack of quantitative prediction methods for the impact of thickness changes on color parameters, and the reliance on complex artificial intelligence models or experience-based judgments makes it difficult to integrate into the digital design process.
A color-thickness function model is established to predict color parameters by calculating the thickness parameters of the restoration. The model coefficients are calculated by regression analysis using experimental data to achieve quantitative prediction of restoration color during the design phase and generate instructions for thickness adjustment or external staining modification.
It improves the accuracy of restoration color prediction and the controllability of digital processes, reduces reliance on experience-based judgment and repeated trial and error, and ensures the precision and consistency of color design and manufacturing.
Smart Images
Figure CN122636751A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of digital oral healthcare technology, and in particular to a method, system, device, medium, and product for predicting the three-dimensional color of digital dental prostheses. Background Technology
[0002] With the development of digital dental restoration technology, computer-aided design and manufacturing (CAD / CAM) restorations are widely used due to their high efficiency and repeatability. However, in the current digital restoration process, the final color of the restoration is still difficult to predict accurately during the design stage.
[0003] In related technologies, the color of restorations is typically influenced by various factors such as material type, thickness variation, and surface condition, with thickness variation having a significant impact on color parameters. However, in clinical practice, adjustments to restoration thickness often occur during the design or fabrication stage, and a method is lacking that can quantitatively predict the final color change at this stage.
[0004] In addition, some technologies rely on complex artificial intelligence models or experience-based judgments, which may result in problems such as uninterpretable models, large data requirements, or difficulty in directly integrating them into the digital design process.
[0005] Therefore, it is necessary to propose a three-dimensional color prediction method for dental prostheses to solve the problems of unpredictable prosthesis color and lack of quantitative basis in the design stage in the existing technology. Summary of the Invention
[0006] The purpose of this application is to provide a method, system, device, medium, and product for predicting the three-dimensional color of digital dental prostheses, thereby improving the accuracy of color prediction for dental prostheses and the controllability of the digital process.
[0007] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a method for predicting the three-dimensional color of a digital dental prosthesis, the method comprising: A three-dimensional morphological model of the patient's target oral prosthesis is established, and the thickness parameters of the target oral prosthesis are calculated based on the three-dimensional morphological model. The thickness parameters are input into a pre-established color-thickness function model to calculate the predicted values of the color parameters of the target dental prosthesis under the corresponding thickness conditions. The color-thickness function model is used to characterize the mathematical relationship between the thickness parameters and color parameters of the prosthesis. The color parameters include: lightness parameters, red-green axis parameters, and yellow-blue axis parameters. The predicted values of the color parameters are output and used in the color design, adjustment, or manufacturing decision-making process of the target dental prosthesis.
[0008] In one embodiment, a three-dimensional morphological model of the target dental prosthesis for the patient is established, and the thickness parameters of the target dental prosthesis are calculated based on the three-dimensional morphological model, specifically including: A three-dimensional digital model of the patient's dental arch is obtained using an oral scanning device, and the contralateral tooth corresponding to the missing tooth is identified in the three-dimensional digital model. The three-dimensional model of the contralateral tooth with the same name is mirrored to generate a mirror-symmetric tooth model, and the mirror-symmetric tooth model is used as the initial morphological model of the target oral restoration. The initial morphological model is locally adjusted to obtain a three-dimensional morphological model of the target oral prosthesis; the three-dimensional morphological model of the target oral prosthesis conforms to the occlusal and adjoint relationships. The thickness of the target dental prosthesis is calculated by performing a three-dimensional morphological model on the prosthesis.
[0009] In one embodiment, the three-dimensional model of the contralateral tooth of the same name is mirrored to generate a mirror-symmetric tooth model, specifically including: Using the patient's dental arch midline or dental arch midline as a mirror symmetry plane, a spatial coordinate reflection calculation is performed on the three-dimensional model of the contralateral corresponding tooth to obtain an initial morphological model of the target oral restoration that matches the position of the missing tooth.
[0010] In one embodiment, the thickness of the three-dimensional morphological model of the target dental prosthesis is calculated to obtain the thickness parameters of the target dental prosthesis, specifically including: The thickness of the three-dimensional morphological model is calculated to obtain at least one of the following thickness parameters: The overall average thickness of the target dental prosthesis; Local thickness values of different areas of the target dental prosthesis; Thickness distribution information between the external and internal surfaces of the target oral restoration; Thickness information of the labial region of the target dental prosthesis; Thickness information of the lingual region of the target dental prosthesis; The thickness information of the labial region and the lingual region of the target oral prosthesis is calculated from the spatial distance between the outer and inner surfaces of the prosthesis.
[0011] In one embodiment, the expression for the color-thickness function model is: ; ; ; in, This refers to the brightness parameter; For the red and green axis parameters; For the yellow and blue axis parameters; , , , , , , , , , , , These are the model coefficients obtained through regression calculations using experimental data; This refers to the thickness parameter of the dental prosthesis.
[0012] In one embodiment, the method further includes: Obtain the predicted value of the set color parameters; The predicted value of the color parameter is compared with the expected value of the set color parameter to calculate the color deviation; When the color deviation exceeds a preset threshold, a thickness adjustment or external dyeing modification instruction is automatically generated. According to the thickness adjustment instructions, the three-dimensional morphological model of the target oral prosthesis is locally thickened or thinned to adjust the thickness parameters of the target oral prosthesis, or external staining is guided based on the fabrication of the prosthesis.
[0013] Secondly, this application provides a digital dental prosthesis three-dimensional color prediction system, which is used to implement the aforementioned digital dental prosthesis three-dimensional color prediction method. The digital dental prosthesis three-dimensional color prediction system includes: The model building and thickness parameter determination unit is used to build a three-dimensional morphological model of the patient's target oral prosthesis and calculate the thickness parameters of the target oral prosthesis based on the three-dimensional morphological model. The prediction unit is used to input the thickness parameters into a pre-established color-thickness function model to calculate the predicted value of the color parameters of the target dental prosthesis under the corresponding thickness conditions; the color-thickness function model is used to characterize the mathematical relationship between the thickness parameters and color parameters of the prosthesis; the color parameters include: lightness parameters, red-green axis parameters, and yellow-blue axis parameters; The result output unit is used to output the predicted value of the color parameter and use the predicted value of the color parameter in the color design, adjustment or manufacturing decision-making process of the target dental prosthesis.
[0014] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for predicting the three-dimensional color of digital dental prostheses.
[0015] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned method for predicting the three-dimensional color of digital dental prostheses.
[0016] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned three-dimensional color prediction method for digital dental prostheses.
[0017] According to the specific embodiments provided in this application, this application has the following technical effects: This application discloses a method, system, device, medium, and product for predicting the three-dimensional color of digital dental prostheses. It establishes a three-dimensional morphological model of the patient's target dental prosthesis and calculates the thickness parameters accordingly. These thickness parameters are then input into a pre-established color-thickness function model to quantitatively calculate the predicted color values. Finally, the predicted color values are output for use in the color design, adjustment, or manufacturing decisions of the prosthesis. This achieves quantitative prediction of the final color of the prosthesis during the digital design or manufacturing stage, replacing the traditional method that relies on experience-based judgment or complex, uninterpretable AI models with a clear mathematical function relationship. This eliminates the need for later trial and error or subjective estimation in color prediction. Furthermore, since the thickness parameters can be directly obtained from the three-dimensional morphological model, and the predicted color values can be directly output and fed back to the design adjustment process, it can be seamlessly integrated into existing CAD / CAM digital workflows. This solves the technical problems of related technologies, such as the lack of methods for quantitatively predicting color changes during the design or manufacturing stage, reliance on experience or black-box models, and difficulty in integrating into digital processes. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a schematic diagram of a three-dimensional color prediction method for digital dental prostheses provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation
[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0022] In one exemplary embodiment, such as Figure 1 As shown, a three-dimensional color prediction method for digital dental prostheses is provided. This method is executed by a computer device, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is described using a server as an example, and includes the following steps: Step S1: Establish a three-dimensional morphological model of the patient's target oral prosthesis, and calculate the thickness parameters of the target oral prosthesis based on the three-dimensional morphological model.
[0023] As an optional implementation method, step S1 specifically includes: Step S11: A three-dimensional digital model of the patient's dentition is acquired using an oral scanning device, and the contralateral corresponding tooth of the missing tooth is identified in the three-dimensional digital model. The three-dimensional morphological data of the contralateral corresponding tooth is read by a computer device and used as a reference model for the design of the target oral prosthesis.
[0024] Step S12: Perform mirror transformation on the three-dimensional model of the contralateral tooth to generate a mirror-symmetric tooth model, and use the mirror-symmetric tooth model as the initial morphological model of the target oral restoration.
[0025] Step S13: The initial morphological model is locally adjusted to obtain the three-dimensional morphological model of the target oral prosthesis; the three-dimensional morphological model of the target oral prosthesis conforms to the occlusal relationship and the adjoint relationship.
[0026] After the initial morphological model is generated, it can be locally adjusted in computer-aided design software to obtain the final prosthesis morphological model (i.e., the three-dimensional morphological model of the target oral prosthesis) that conforms to the occlusal and adjoint relationships.
[0027] Step S14: Calculate the thickness of the three-dimensional morphological model of the target dental prosthesis to obtain the thickness parameters of the target dental prosthesis.
[0028] As an optional implementation, in step S12, the three-dimensional model of the contralateral tooth of the same name is mirrored to generate a mirror-symmetric tooth model, specifically including: Using the patient's dental arch midline or dental arch midline as a mirror symmetry plane, a spatial coordinate reflection calculation is performed on the three-dimensional model of the contralateral corresponding tooth to obtain an initial morphological model of the target oral restoration that matches the position of the missing tooth.
[0029] As an optional implementation, step S14 specifically includes: The thickness of the three-dimensional morphological model is calculated to obtain at least one of the following thickness parameters: The overall average thickness of the target dental prosthesis.
[0030] Local thickness values of different areas of the target dental prosthesis.
[0031] Information on the thickness distribution between the external and internal surfaces of the target oral prosthesis.
[0032] Thickness information of the labial region of the target oral prosthesis.
[0033] Thickness information of the lingual region of the target dental prosthesis; The thickness information of the labial region and the lingual region of the target oral prosthesis is calculated from the spatial distance between the outer and inner surfaces of the prosthesis.
[0034] Specifically, a three-dimensional morphological model of the target oral prosthesis is established and generated by a dental prosthesis design program in a computer device.
[0035] Step S2 involves inputting the thickness parameters into a pre-established color-thickness function model to calculate the predicted color parameters of the target dental prosthesis under the corresponding thickness conditions. The color-thickness function model characterizes the mathematical relationship between the prosthesis's thickness parameters and color parameters. The color parameters include: lightness parameters, red-green axis parameters, and yellow-blue axis parameters. The color parameters are represented based on the CIELab color space established by the International Commission on Illumination (ICI). The predicted color parameters of the target dental prosthesis under the corresponding thickness conditions are used to characterize the prosthesis's color performance during molding or wearing.
[0036] As an optional implementation, in step S2, the expression for the color-thickness function model is: (1) (2) (3) in, This refers to the brightness parameter; For the red and green axis parameters; For the yellow and blue axis parameters; , , , , , , , , , , , These are the model coefficients obtained through regression calculations using experimental data; This refers to the thickness parameter of the dental prosthesis.
[0037] Specifically, the thickness parameter and color parameter of the restoration satisfy a cubic function relationship, as shown in equations (1) to (3) above.
[0038] The model coefficients are determined by computer equipment using regression analysis based on experimental measurement data. Corresponding color-thickness function model parameters can be established under different repair material conditions; the color-thickness function model can be implemented using different mathematical function forms, or a corresponding function model can be established based on different experimental data, without any restrictions.
[0039] Step S3: Output the predicted value of the color parameter and use the predicted value of the color parameter in the color design, adjustment or manufacturing decision-making process of the target dental prosthesis.
[0040] Specifically, the predicted color parameters are used for at least one of the following purposes: As a reference for the color design of digital restorations; Used for color adjustment or thickness optimization of restorations; Used for color control during the manufacturing process of prostheses.
[0041] As an optional implementation, the method further includes: Step S4: Obtain the predicted value of the set color parameters.
[0042] Step S5: Compare the predicted value of the color parameter with the expected value of the set color parameter to calculate the color deviation.
[0043] Step S6: When the color deviation exceeds a preset threshold, a thickness adjustment command or an external dyeing modification command is automatically generated.
[0044] Step S7: According to the thickness adjustment instruction, locally thicken or thin the three-dimensional morphological model of the target oral prosthesis to adjust the thickness parameters of the target oral prosthesis, or, based on the fabrication of the prosthesis, perform external staining treatment guidance.
[0045] Beneficial effects: 1) Improve the accuracy of restoration color prediction By establishing a functional relationship between restoration thickness and color parameters, and performing calculations using computer equipment, quantitative prediction of the final color is achieved during the restoration design or manufacturing stage. This reduces the uncertainty of relying on experience for color judgment and abandons the traditional practice of relying on technicians' personal experience, visual comparison, or repeated trial and error sintering to determine the color. It transforms the originally subjective, vague, and unquantifiable color judgment into objective, accurate, and reproducible numerical calculations. Since the thickness parameter is derived from the actual three-dimensional geometric data of the restoration, the function model is based on experimental regression, and the computer calculation process is not affected by human factors, the accuracy of color prediction is significantly improved, and color deviation caused by experience differences or visual errors is reduced. This provides a reliable data foundation for subsequent color design, adjustment, and manufacturing.
[0046] 2) Improve the controllability and consistency of the digital repair process. By employing a color-thickness function model, this application enables the quantification of color variations in restorations, achieving predictability and adjustability of color during the design phase, as well as repeatability of color results under different conditions. Thickness parameters are directly obtained from the CAD model, and predicted values are directly output to the design or manufacturing stages without data conversion or manual intervention, allowing for seamless integration into existing digital workflows. Since color deviations can be detected in advance during the design phase and corrected through thickness optimization, repeated sintering or rework due to color issues in traditional processes is avoided, significantly reducing restoration rework rates and improving the overall process controllability and consistency.
[0047] Based on the same inventive concept, this application also provides a digital dental prosthesis three-dimensional color prediction system for implementing the aforementioned digital dental prosthesis three-dimensional color prediction method. The solution provided by this system is similar to the implementation scheme described in the above method; therefore, the specific limitations of one or more embodiments of the digital dental prosthesis three-dimensional color prediction system provided below can be found in the limitations of the digital dental prosthesis three-dimensional color prediction method described above, and will not be repeated here.
[0048] In one exemplary embodiment, a digital dental prosthesis three-dimensional color prediction system is provided, comprising: The model building and thickness parameter determination unit is used to build a three-dimensional morphological model of the patient's target oral prosthesis and calculate the thickness parameters of the target oral prosthesis based on the three-dimensional morphological model. The prediction unit is used to input the thickness parameters into a pre-established color-thickness function model to calculate the predicted value of the color parameters of the target dental prosthesis under the corresponding thickness conditions; the color-thickness function model is used to characterize the mathematical relationship between the thickness parameters and color parameters of the prosthesis; the color parameters include: lightness parameters, red-green axis parameters, and yellow-blue axis parameters; The result output unit is used to output the predicted value of the color parameter and use the predicted value of the color parameter in the color design, adjustment or manufacturing decision-making process of the target dental prosthesis.
[0049] In one exemplary embodiment, a computer device is provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a three-dimensional color prediction method for digital dental prostheses.
[0050] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements a method for predicting the three-dimensional color of digital dental prostheses.
[0051] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements a three-dimensional color prediction method for digital dental prostheses.
[0052] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 2 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a three-dimensional color prediction method for digital dental prostheses.
[0053] Those skilled in the art will understand that Figure 2The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0054] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.
[0055] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).
[0056] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based digital dental logic devices, etc., but are not limited to these.
[0057] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0058] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods, systems, and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for predicting the three-dimensional color of digital dental prostheses, characterized in that, The digital dental prosthesis three-dimensional color prediction method includes: A three-dimensional morphological model of the patient's target oral prosthesis is established, and the thickness parameters of the target oral prosthesis are calculated based on the three-dimensional morphological model. The thickness parameters are input into a pre-established color-thickness function model to calculate the predicted values of the color parameters of the target dental prosthesis under the corresponding thickness conditions. The color-thickness function model is used to characterize the mathematical relationship between the thickness parameters and color parameters of the prosthesis. The color parameters include: lightness parameters, red-green axis parameters, and yellow-blue axis parameters. The predicted values of the color parameters are output and used in the color design, adjustment, or manufacturing decision-making process of the target dental prosthesis.
2. The method for predicting the three-dimensional color of digital dental prostheses according to claim 1, characterized in that, A three-dimensional morphological model of the patient's target dental prosthesis is established, and the thickness parameters of the target dental prosthesis are calculated based on the three-dimensional morphological model, specifically including: A three-dimensional digital model of the patient's dental arch is obtained using an oral scanning device, and the contralateral tooth corresponding to the missing tooth is identified in the three-dimensional digital model. The three-dimensional model of the contralateral tooth with the same name is mirrored to generate a mirror-symmetric tooth model, and the mirror-symmetric tooth model is used as the initial morphological model of the target oral restoration. The initial morphological model is locally adjusted to obtain a three-dimensional morphological model of the target oral prosthesis; the three-dimensional morphological model of the target oral prosthesis conforms to the occlusal and adjoint relationships. The thickness of the target dental prosthesis is calculated by performing a three-dimensional morphological model on the prosthesis.
3. The method for predicting the three-dimensional color of digital dental prostheses according to claim 2, characterized in that, The three-dimensional model of the contralateral tooth of the same name is mirrored to generate a mirror-symmetric tooth model, specifically including: Using the patient's dental arch midline or dental arch midline as a mirror symmetry plane, a spatial coordinate reflection calculation is performed on the three-dimensional model of the contralateral corresponding tooth to obtain an initial morphological model of the target oral restoration that matches the position of the missing tooth.
4. The method for predicting the three-dimensional color of digital dental prostheses according to claim 2, characterized in that, Thickness calculations are performed on the three-dimensional morphological model of the target dental prosthesis to obtain its thickness parameters, specifically including: The thickness of the three-dimensional morphological model is calculated to obtain at least one of the following thickness parameters: The overall average thickness of the target dental prosthesis; Local thickness values of different areas of the target dental prosthesis; Thickness distribution information between the external and internal surfaces of the target oral restoration; Thickness information of the labial region of the target dental prosthesis; Thickness information of the lingual region of the target dental prosthesis; The thickness information of the labial region and the lingual region of the target oral prosthesis is calculated from the spatial distance between the outer and inner surfaces of the prosthesis.
5. The method for predicting the three-dimensional color of digital dental prostheses according to claim 1, characterized in that, The expression for the color-thickness function model is: ； ； ； in, This refers to the brightness parameter; For the red and green axis parameters; For the yellow and blue axis parameters; , , , , , , , , , , , These are the model coefficients obtained through regression calculations using experimental data; These are the thickness parameters at various points on the dental prosthesis.
6. The method for predicting the three-dimensional color of digital dental prostheses according to claim 1, characterized in that, The method further includes: Obtain the predicted value of the set color parameters; The predicted value of the color parameter is compared with the expected value of the set color parameter to calculate the color deviation; When the color deviation exceeds a preset threshold, a thickness adjustment or external dyeing modification instruction is automatically generated. According to the thickness adjustment instructions, the three-dimensional morphological model of the target oral prosthesis is locally thickened or thinned to adjust the thickness parameters of the target oral prosthesis, or external staining is guided based on the fabrication of the prosthesis.
7. A digital three-dimensional color prediction system for dental prostheses, characterized in that, The digital dental prosthesis three-dimensional color prediction system is used to implement the digital dental prosthesis three-dimensional color prediction method according to any one of claims 1-6, and the digital dental prosthesis three-dimensional color prediction system includes: The model building and thickness parameter determination unit is used to build a three-dimensional morphological model of the patient's target oral prosthesis and calculate the thickness parameters of the target oral prosthesis based on the three-dimensional morphological model. The prediction unit is used to input the thickness parameters into a pre-established color-thickness function model to calculate the predicted value of the color parameters of the target dental prosthesis under the corresponding thickness conditions; the color-thickness function model is used to characterize the mathematical relationship between the thickness parameters and color parameters of the prosthesis; the color parameters include: lightness parameters, red-green axis parameters, and yellow-blue axis parameters; The result output unit is used to output the predicted value of the color parameter and use the predicted value of the color parameter in the color design, adjustment or manufacturing decision-making process of the target dental prosthesis.
8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the three-dimensional color prediction method for digital dental prostheses according to any one of claims 1-6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the three-dimensional color prediction method for digital dental prostheses as described in any one of claims 1-6.
10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the three-dimensional color prediction method for digital dental prostheses as described in any one of claims 1-6.