Three-dimensional oral cavity model precision control method and system

Abstract

The invention discloses a three-dimensional oral cavity model precision control method and system. The method comprises the following steps: determining an orthodontic demand of a target user; the orthodontic requirement is used for indicating an oral cavity part needing orthodontic treatment and a corresponding oral cavity problem; according to the orthodontic requirements, determining precision requirements corresponding to different oral cavity parts of the target user; acquiring CT scanning image data of the target user; according to the precision requirement and the CT scanning image data, generating a three-dimensional oral cavity model of the target user based on a preset precision control modeling rule; the three-dimensional oral cavity model and the model part corresponding to each oral cavity part meet the corresponding precision requirements. Therefore, the three-dimensional model aiming at the orthodontic requirements of the user can be more efficiently and accurately generated, the calculation cost is reduced, and an accurate and low-cost data basis is provided for orthodontic treatment of the user.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a three-dimensional oral cavity model precision control method and system. Background Art

[0002] 3D oral model technology has begun to be frequently used in medical fields such as orthodontics. 3D oral models can accurately represent the exact conditions of different tissue structures inside the oral cavity. When correcting teeth and improving maxillofacial irregularities, orthodontics can use the data of 3D oral models to formulate more reasonable orthodontic treatment plans. However, when modeling and calculating 3D oral models, the existing technology does not fully consider the different orthodontic needs of users to control the accuracy of model calculation or display. Therefore, it often consumes a lot of computing costs to model oral positions that do not match the needs. The modeling efficiency is low, the cost is too high, and the auxiliary effect on treatment is not good. It can be seen that the existing technology has defects that need to be solved urgently. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a three-dimensional oral model accuracy control method and system, which can more efficiently and accurately generate a three-dimensional model for the user's orthodontic needs, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0004] In order to solve the above technical problems, the first aspect of the present invention discloses a method for controlling the accuracy of a three-dimensional oral model, the method comprising: Determine the orthodontic needs of the target user; the orthodontic needs are used to indicate the oral area that requires orthodontic treatment and the corresponding oral problems; According to the orthodontic needs, determining the accuracy requirements corresponding to different oral parts of the target user; Acquire CT scan image data of the target user; According to the accuracy requirement and the CT scan image data, a three-dimensional oral model of the target user is generated based on preset accuracy control modeling rules; the three-dimensional oral model and the model part corresponding to each oral part meet the corresponding accuracy requirement.

[0005] As an optional implementation, in the first aspect of the present invention, determining the orthodontic needs of the target user includes: Acquire the user parameters and historical medical consultation records of the target user; the user parameters include physiological parameters and oral physical parameters; Screening out a target demand forecasting model from a plurality of candidate demand forecasting models according to the user parameters; The historical consultation records are input into the target demand prediction model to obtain the orthodontic needs corresponding to the target user.

[0006] As an optional implementation, in the first aspect of the present invention, selecting a target demand forecasting model from a plurality of candidate demand forecasting models according to the user parameters comprises: For each candidate demand forecasting model, obtaining multiple forecasting records of the candidate demand forecasting model in the verification phase; For each of the prediction records, calculating a first similarity between a user physiological parameter of a prediction user corresponding to the prediction record and the physiological parameter of the target user; Calculate a second similarity between the oral physical parameter of the predicted user corresponding to the prediction record and the oral physical parameter of the target user; Calculating a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record; Calculate the product of the similarity parameter corresponding to the predicted record and the prediction accuracy rate corresponding to the predicted record to obtain a record priority parameter of the predicted record; Calculating an average value of the record priority parameters of all the prediction records of the candidate demand prediction model to obtain a model priority parameter of the candidate demand prediction model; The candidate demand forecasting model with the highest model priority parameter is determined as the target demand forecasting model.

[0007] As an optional implementation, in the first aspect of the present invention, determining the orthodontic needs of the target user includes: Acquire multiple oral cavity pictures of the target user through the image acquisition module; Determine the oral problem of the target user based on the image recognition algorithm and the oral picture; The orthodontic needs of the target user are determined based on the oral problems and the correspondence between the preset problems and needs.

[0008] As an optional implementation, in the first aspect of the present invention, determining the accuracy requirements corresponding to different oral parts of the target user according to the orthodontic requirements includes: Based on the preset correspondence between the needs and the focus areas, determining a plurality of focus oral areas corresponding to the orthodontic needs; Based on a preset part association rule, determining at least one associated oral part corresponding to each oral part of interest; According to the preset accuracy value setting rules, the accuracy requirements are assigned to each of the oral parts of interest or the associated oral parts or other oral parts; the other oral parts are oral parts in the preset oral part set that do not belong to the oral parts of interest or the associated oral parts.

[0009] As an optional embodiment, in the first aspect of the present invention, the setting rule of the preset accuracy value to assign the accuracy requirement to each of the oral cavity parts of interest or the associated oral cavity parts or other oral cavity parts includes: The objective function is set to minimize the weighted sum of the accuracy requirements corresponding to all oral parts; wherein the weight corresponding to each oral part is inversely proportional to the distance of the oral part from the center of interest; the oral part is the oral part of interest or the associated oral part or the other oral part; the center of interest is the geometric center of the positions of all the oral parts of interest; The setting restriction conditions include that the precision requirement value of each oral part is proportional to the importance corresponding to the oral part, the precision requirement value of each oral part is not less than a preset precision requirement threshold, and the difference between the precision requirement values ​​of two adjacent oral parts is less than a preset difference threshold; the importance decreases in sequence when the oral part is the concerned oral part, the associated oral part, and the other oral parts; Based on the dynamic programming algorithm, the accuracy requirements of all the oral parts are iteratively calculated according to the objective function and the constraint conditions until convergence, so as to obtain the accuracy requirement corresponding to each oral part.

[0010] As an optional implementation, in the first aspect of the present invention, generating the three-dimensional oral model of the target user based on the accuracy requirement and the CT scan image data and based on a preset accuracy control modeling rule includes: Based on the transformation association algorithm, according to the scanning device lens parameters of each of the CT scan image data, determining the associated three-dimensional mathematical models corresponding to the plurality of CT scan impact data; According to the preset mathematical correspondence relationship of the oral cavity parts, determining the model part corresponding to each of the oral cavity parts in the associated three-dimensional mathematical model; According to the accuracy requirement of the oral cavity corresponding to each model part, and the correspondence between the preset requirement and the calculation parameter, a corresponding calculation parameter is assigned to each model part; the calculation cost of the calculation parameter is proportional to the accuracy requirement; Based on an adaptive iterative reconstruction algorithm, a three-dimensional reconstruction calculation is performed on the plurality of CT scan impact data according to the calculation parameters corresponding to each of the model parts to obtain a three-dimensional oral model of the target user.

[0011] As an optional implementation, in the first aspect of the present invention, the calculation parameters include the number of calculation iterations, the number of images used in the calculation and the calculation interpolation accuracy; the value of the calculation parameter is proportional to the value of the accuracy requirement.

[0012] A second aspect of an embodiment of the present invention discloses a three-dimensional oral model accuracy control system, the system comprising: A first determination module is used to determine the orthodontic needs of the target user; the orthodontic needs are used to indicate the oral parts that need orthodontic treatment and the corresponding oral problems; A second determination module is used to determine the accuracy requirements corresponding to different oral parts of the target user according to the orthodontic requirements; An acquisition module, used to acquire CT scan image data of the target user; A generation module is used to generate a three-dimensional oral model of the target user according to the accuracy requirement and the CT scan image data based on preset accuracy control modeling rules; the three-dimensional oral model and the model part corresponding to each oral part meet the corresponding accuracy requirement.

[0013] As an optional implementation, in the second aspect of the present invention, the specific manner in which the first determination module determines the orthodontic needs of the target user includes: Acquire the user parameters and historical medical consultation records of the target user; the user parameters include physiological parameters and oral physical parameters; Screening out a target demand forecasting model from a plurality of candidate demand forecasting models according to the user parameters; The historical consultation records are input into the target demand prediction model to obtain the orthodontic needs corresponding to the target user.

[0014] As an optional implementation, in the second aspect of the present invention, the specific manner in which the first determination module selects the target demand forecasting model from the plurality of candidate demand forecasting models according to the user parameters includes: For each candidate demand forecasting model, obtaining multiple forecasting records of the candidate demand forecasting model in the verification phase; For each of the prediction records, calculating a first similarity between a user physiological parameter of a prediction user corresponding to the prediction record and the physiological parameter of the target user; Calculate a second similarity between the oral physical parameter of the predicted user corresponding to the prediction record and the oral physical parameter of the target user; Calculating a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record; Calculate the product of the similarity parameter corresponding to the predicted record and the prediction accuracy rate corresponding to the predicted record to obtain a record priority parameter of the predicted record; Calculating an average value of the record priority parameters of all the prediction records of the candidate demand prediction model to obtain a model priority parameter of the candidate demand prediction model; The candidate demand forecasting model with the highest model priority parameter is determined as the target demand forecasting model.

[0015] As an optional implementation, in the second aspect of the present invention, the specific manner in which the first determination module determines the orthodontic needs of the target user includes: Acquire multiple oral cavity pictures of the target user through the image acquisition module; Determine the oral problem of the target user based on the image recognition algorithm and the oral picture; The orthodontic needs of the target user are determined based on the oral problems and the correspondence between the preset problems and needs.

[0016] As an optional implementation, in the second aspect of the present invention, the second determination module determines the specific manner in which the accuracy requirements corresponding to different oral parts of the target user are determined according to the orthodontic requirements, including: Based on the preset correspondence between the needs and the focus areas, determining a plurality of focus oral areas corresponding to the orthodontic needs; Based on a preset part association rule, determining at least one associated oral part corresponding to each oral part of interest; According to the preset accuracy value setting rules, the accuracy requirements are assigned to each of the oral parts of interest or the associated oral parts or other oral parts; the other oral parts are oral parts in the preset oral part set that do not belong to the oral parts of interest or the associated oral parts.

[0017] As an optional implementation, in the second aspect of the present invention, the second determination module sets a rule according to a preset accuracy value, and the specific manner of assigning the accuracy requirement to each of the oral cavity parts of interest or the associated oral cavity parts or other oral cavity parts includes: The objective function is set to minimize the weighted sum of the accuracy requirements corresponding to all oral parts; wherein the weight corresponding to each oral part is inversely proportional to the distance of the oral part from the center of interest; the oral part is the oral part of interest or the associated oral part or the other oral part; the center of interest is the geometric center of the positions of all the oral parts of interest; The setting restriction conditions include that the precision requirement value of each oral part is proportional to the importance corresponding to the oral part, the precision requirement value of each oral part is not less than a preset precision requirement threshold, and the difference between the precision requirement values ​​of two adjacent oral parts is less than a preset difference threshold; the importance decreases in sequence when the oral part is the concerned oral part, the associated oral part, and the other oral parts; Based on the dynamic programming algorithm, the accuracy requirements of all the oral parts are iteratively calculated according to the objective function and the constraint conditions until convergence, so as to obtain the accuracy requirement corresponding to each oral part.

[0018] As an optional implementation, in the second aspect of the present invention, the specific manner in which the generating module generates the three-dimensional oral model of the target user according to the accuracy requirement and the CT scan image data and based on a preset accuracy control modeling rule includes: Based on the transformation association algorithm, according to the scanning device lens parameters of each of the CT scan image data, determining the associated three-dimensional mathematical models corresponding to the plurality of CT scan impact data; According to the preset mathematical correspondence relationship of the oral cavity parts, determining the model part corresponding to each of the oral cavity parts in the associated three-dimensional mathematical model; According to the accuracy requirement of the oral cavity corresponding to each model part, and the correspondence between the preset requirement and the calculation parameter, a corresponding calculation parameter is assigned to each model part; the calculation cost of the calculation parameter is proportional to the accuracy requirement; Based on an adaptive iterative reconstruction algorithm, a three-dimensional reconstruction calculation is performed on the plurality of CT scan impact data according to the calculation parameters corresponding to each of the model parts to obtain a three-dimensional oral model of the target user.

[0019] As an optional implementation, in the second aspect of the present invention, the calculation parameters include the number of calculation iterations, the number of images used in the calculation and the calculation interpolation accuracy; the value of the calculation parameter is proportional to the value of the accuracy requirement.

[0020] The third aspect of the present invention discloses another three-dimensional oral model accuracy control system, the system comprising: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute part or all of the steps in the three-dimensional oral model accuracy control method disclosed in the first aspect of the present invention.

[0021] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all of the steps in the three-dimensional oral model accuracy control method disclosed in the first aspect of the present invention.

[0022] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: The present invention can determine the accuracy requirements corresponding to different oral parts according to the orthodontic needs of the target user, and then generate a three-dimensional oral model that meets the accuracy requirements through the accuracy requirements and CT scanning image data, thereby being able to more efficiently and accurately generate a three-dimensional model for the user's orthodontic needs, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 It is a flow chart of a method for controlling the accuracy of a three-dimensional oral model disclosed in an embodiment of the present invention.

[0025] Figure 2 It is a structural schematic diagram of a three-dimensional oral model precision control system disclosed in an embodiment of the present invention.

[0026] Figure 3 It is a structural schematic diagram of another three-dimensional oral model precision control system disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or equipment.

[0029] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0030] The present invention discloses a 3D oral model accuracy control method and system, which can determine the accuracy requirements corresponding to different oral parts according to the orthodontic needs of the target user, and then generate a 3D oral model that meets the accuracy requirements through the accuracy requirements and CT scanning image data, so as to more efficiently and accurately generate a 3D model for the user's orthodontic needs, reduce the calculation cost, and provide an accurate and low-cost data basis for the user's orthodontic treatment. The following are detailed descriptions.

[0031] Embodiment 1 See also Figure 1 , Figure 1 : is a flow chart of a method for controlling the accuracy of a three-dimensional oral model disclosed in an embodiment of the present invention. Figure 1 The described three-dimensional oral model accuracy control method can be applied to a data processing system / data processing device / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 1 As shown, the three-dimensional oral model accuracy control method may include the following operations: 101. Determine the orthodontic needs of target users.

[0032] Optionally, orthodontic needs are used to indicate the oral area and corresponding oral problems that require orthodontic treatment.

[0033] 102. According to orthodontic needs, determine the accuracy requirements for different oral parts of the target user. 103. Obtain CT scan image data of the target user. 104. According to the accuracy requirements and CT scan image data, a three-dimensional oral model of the target user is generated based on the preset accuracy control modeling rules.

[0034] Optionally, the three-dimensional oral model and the model portion corresponding to each oral part meet the corresponding accuracy requirements.

[0035] It can be seen that the above-mentioned embodiments of the invention can determine the accuracy requirements corresponding to different oral parts according to the orthodontic needs of the target user, and then generate a three-dimensional oral model that meets the accuracy requirements through the accuracy requirements and CT scan image data, thereby being able to more efficiently and accurately generate a three-dimensional model for the user's orthodontic needs, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0036] As an optional embodiment, in the above step, determining the orthodontic needs of the target user includes: Obtain user parameters and historical medical records of the target user; optionally, the user parameters include physiological parameters and oral physical parameters; Screening out a target demand forecasting model from multiple candidate demand forecasting models according to user parameters; Input historical consultation records into the target demand prediction model to obtain the orthodontic needs corresponding to the target users.

[0037] It can be seen that through the above-mentioned optional embodiments, a target demand prediction model can be screened out from multiple candidate demand prediction models based on user parameters, so as to accurately predict the orthodontic needs of the target user according to the user's historical medical records, and assist in more efficiently and accurately generating a three-dimensional model for the user's orthodontic needs, thereby reducing computing costs and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0038] As an optional embodiment, in the above step, selecting a target demand forecasting model from a plurality of candidate demand forecasting models according to user parameters includes: For each candidate demand forecasting model, obtaining multiple forecasting records of the candidate demand forecasting model in the verification phase; For each prediction record, calculating a first similarity between a user physiological parameter of a prediction user corresponding to the prediction record and a physiological parameter of a target user; Calculating a second similarity between the oral physical parameters of the predicted user corresponding to the prediction record and the oral physical parameters of the target user; Calculate a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record; Calculate the product of the similarity parameter corresponding to the predicted record and the prediction accuracy rate corresponding to the predicted record to obtain a record priority parameter of the predicted record; Calculate the average value of the record priority parameters of all prediction records of the candidate demand prediction model to obtain the model priority parameter of the candidate demand prediction model; The candidate demand forecasting model with the highest model priority parameter is determined as the target demand forecasting model.

[0039] It can be seen that through the above-mentioned optional embodiments, the target demand prediction model can be screened out based on the similarity calculation between the user parameters and the current user in the prediction records of the verification stage of each candidate model, as well as the prediction accuracy calculation, so as to facilitate the subsequent accurate prediction of the target user's orthodontic needs based on the user's historical consultation records, and assist in achieving more efficient and accurate generation of three-dimensional models for the user's orthodontic needs, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0040] As an optional embodiment, in the above step, determining the orthodontic needs of the target user includes: Acquire multiple oral cavity pictures of the target user through the image acquisition module; Determine the target user’s oral problems based on image recognition algorithms and oral pictures; Determine the orthodontic needs of the target users based on oral problems and the correspondence between preset problems and needs.

[0041] It can be seen that through the above-mentioned optional embodiments, it is possible to obtain the user's oral cavity picture through a camera or other image acquisition module, and then determine the possible problems in the oral cavity based on the algorithm, and then determine the user's orthodontic needs based on this. In some optional schemes, this demand determination method can also be combined with the results of the model prediction method in the above-mentioned embodiments to jointly and accurately determine the user's oral orthodontic needs, which can achieve more efficient and accurate generation of three-dimensional models for the user's orthodontic needs, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0042] As an optional embodiment, in the above steps, determining the accuracy requirements corresponding to different oral parts of the target user according to orthodontic requirements includes: Based on the correspondence between preset needs and areas of concern, multiple oral areas of concern corresponding to orthodontic needs are determined; Determine at least one associated oral part corresponding to each oral part of interest based on a preset part association rule; According to the preset accuracy value setting rules, the accuracy requirements are assigned to each oral part of interest or associated oral part or other oral part; other oral parts are oral parts in the preset oral part set that do not belong to the oral part of interest or the associated oral part.

[0043] It can be seen that through the above-mentioned optional embodiments, it is possible to determine multiple types of oral parts that need to be paid attention to for orthodontic needs based on the correspondence between preset needs and parts of concern, and then determine the oral parts of concern that need to be paid attention to in general or in specific orthodontic treatment scenarios based on the part association rules that can be set through historical data or physician experience, and finally set the accuracy for each oral part based on the preset accuracy value setting rules, so as to achieve more efficient and accurate generation of three-dimensional models for user orthodontic needs in the future, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0044] As an optional embodiment, in the above steps, according to a preset accuracy value setting rule, the accuracy requirement is assigned to each oral part of interest or associated oral part or other oral part, including: The objective function is set to minimize the weighted sum of the accuracy requirements corresponding to all oral parts; optionally, the weight corresponding to each oral part is inversely proportional to the distance of the oral part from the center of interest; the oral part is the oral part of interest or the associated oral part or other oral part; the center of interest is the geometric center point of the positions of all the oral parts of interest; The setting restriction conditions include that the accuracy requirement value of each oral part is proportional to the importance of the oral part, the accuracy requirement value of each oral part is not less than a preset accuracy requirement threshold, and the difference between the accuracy requirements of two adjacent oral parts is less than a preset difference threshold; optionally, the importance decreases in sequence when the oral part is a focus oral part, an associated oral part, and another oral part; Based on the dynamic programming algorithm, the accuracy requirements of all oral parts are iteratively calculated according to the objective function and constraints until convergence, and the accuracy requirements corresponding to each oral part are obtained.

[0045] It can be seen that through the above-mentioned optional embodiments, the accuracy requirements of different parts of the oral cavity can be iteratively calculated based on the dynamic programming algorithm based on the set objective function and constraints, so as to achieve the final accuracy requirement conditions. On the one hand, it can be greater than the basic requirement threshold and will not be too vague. On the other hand, it can have higher accuracy for important parts, and the overall accuracy value will not be too high to reduce costs, so as to achieve more efficient and accurate generation of three-dimensional models for user orthodontic needs in the future, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0046] As an optional embodiment, in the above steps, according to the accuracy requirement and the CT scan image data, based on the preset accuracy control modeling rules, a three-dimensional oral model of the target user is generated, including: Based on the transformation association algorithm, according to the scanning equipment lens parameters of each CT scanning image data, the associated three-dimensional mathematical model corresponding to the multiple CT scanning impact data is determined; According to the preset mathematical correspondence relationship of the oral cavity parts, determine the model part corresponding to each oral cavity part in the associated three-dimensional mathematical model; According to the accuracy requirements of the oral part corresponding to each model part, and the correspondence between the preset requirements and the calculation parameters, corresponding calculation parameters are assigned to each model part; optionally, the calculation cost of the calculation parameters is proportional to the accuracy requirements; Based on the adaptive iterative reconstruction algorithm, according to the calculation parameters corresponding to each model part, a three-dimensional reconstruction calculation is performed on multiple CT scan impact data to obtain a three-dimensional oral model of the target user.

[0047] It can be seen that through the above-mentioned optional embodiments, it is possible to determine the associated three-dimensional mathematical model corresponding to multiple CT scan impact data based on the transformation association algorithm, and then assign calculation parameters to the model part corresponding to each oral part, so as to realize the calculation of the oral part with corresponding accuracy based on the corresponding calculation parameters during three-dimensional reconstruction, thereby achieving more efficient and accurate generation of three-dimensional models for the user's orthodontic needs, reducing computing costs, and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0048] As an optional embodiment, in the above steps, the calculation parameters include the number of calculation iterations, the number of images used in the calculation and the calculation interpolation accuracy; the value of the calculation parameter is proportional to the value of the accuracy requirement.

[0049] It can be seen that through the above-mentioned optional embodiments, the content of the calculation parameters and the specific numerical relationship between them and the accuracy requirements are clarified, so that the corresponding accuracy of the oral parts can be calculated based on the corresponding calculation parameters during three-dimensional reconstruction, and the three-dimensional model for the user's orthodontic needs can be generated more efficiently and accurately, reducing the computing cost and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0050] Embodiment 2 See also Figure 2 , Figure 2 Schematic diagram of a three-dimensional oral model precision control system disclosed in an embodiment of the present invention. Figure 2 The three-dimensional oral model accuracy control system described can be applied to a data processing system / data processing device / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 2 As shown, the three-dimensional oral model accuracy control system may include: The first determination module 201 is used to determine the orthodontic needs of the target user.

[0051] Optionally, orthodontic needs are used to indicate the oral area and corresponding oral problems that require orthodontic treatment.

[0052] The second determination module 202 is used to determine the accuracy requirements corresponding to different oral parts of the target user according to orthodontic requirements. The acquisition module 203 is used to acquire the CT scan image data of the target user. The generation module 204 is used to generate a three-dimensional oral model of the target user according to the accuracy requirements and the CT scan image data based on the preset accuracy control modeling rules.

[0053] Optionally, the three-dimensional oral model and the model portion corresponding to each oral part meet the corresponding accuracy requirements.

[0054] It can be seen that the above-mentioned embodiments of the invention can determine the accuracy requirements corresponding to different oral parts according to the orthodontic needs of the target user, and then generate a three-dimensional oral model that meets the accuracy requirements through the accuracy requirements and CT scan image data, thereby being able to more efficiently and accurately generate a three-dimensional model for the user's orthodontic needs, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0055] As an optional embodiment, the specific manner in which the first determination module determines the orthodontic needs of the target user includes: Obtain user parameters and historical medical records of the target user; optionally, the user parameters include physiological parameters and oral physical parameters; Screening out a target demand forecasting model from multiple candidate demand forecasting models according to user parameters; Input historical consultation records into the target demand prediction model to obtain the orthodontic needs corresponding to the target users.

[0056] It can be seen that through the above-mentioned optional embodiments, a target demand prediction model can be screened out from multiple candidate demand prediction models based on user parameters, so as to accurately predict the orthodontic needs of the target user according to the user's historical medical records, and assist in more efficiently and accurately generating a three-dimensional model for the user's orthodontic needs, thereby reducing computing costs and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0057] As an optional embodiment, the specific manner in which the first determining module selects the target demand forecasting model from a plurality of candidate demand forecasting models according to the user parameters includes: For each candidate demand forecasting model, obtaining multiple forecasting records of the candidate demand forecasting model in the verification phase; For each prediction record, calculating a first similarity between a user physiological parameter of a prediction user corresponding to the prediction record and a physiological parameter of a target user; Calculating a second similarity between the oral physical parameters of the predicted user corresponding to the prediction record and the oral physical parameters of the target user; Calculate a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record; Calculate the product of the similarity parameter corresponding to the predicted record and the prediction accuracy rate corresponding to the predicted record to obtain a record priority parameter of the predicted record; Calculate the average value of the record priority parameters of all prediction records of the candidate demand prediction model to obtain the model priority parameter of the candidate demand prediction model; The candidate demand forecasting model with the highest model priority parameter is determined as the target demand forecasting model.

[0058] It can be seen that through the above-mentioned optional embodiments, the target demand prediction model can be screened out based on the similarity calculation between the user parameters and the current user in the prediction records of the verification stage of each candidate model, as well as the prediction accuracy calculation, so as to facilitate the subsequent accurate prediction of the target user's orthodontic needs based on the user's historical consultation records, and assist in achieving more efficient and accurate generation of three-dimensional models for the user's orthodontic needs, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0059] As an optional embodiment, the specific manner in which the first determination module determines the orthodontic needs of the target user includes: Acquire multiple oral cavity pictures of the target user through the image acquisition module; Determine the target user’s oral problems based on image recognition algorithms and oral pictures; Determine the orthodontic needs of the target users based on oral problems and the correspondence between preset problems and needs.

[0060] It can be seen that through the above-mentioned optional embodiments, it is possible to obtain the user's oral cavity picture through a camera or other image acquisition module, and then determine the possible problems in the oral cavity based on the algorithm, and then determine the user's orthodontic needs based on this. In some optional schemes, this demand determination method can also be combined with the results of the model prediction method in the above-mentioned embodiments to jointly and accurately determine the user's oral orthodontic needs, which can achieve more efficient and accurate generation of three-dimensional models for the user's orthodontic needs, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0061] As an optional embodiment, the second determination module determines the specific manner of the accuracy requirements corresponding to different oral parts of the target user according to the orthodontic requirements, including: Based on the correspondence between preset needs and areas of concern, multiple oral areas of concern corresponding to orthodontic needs are determined; Determine at least one associated oral part corresponding to each oral part of interest based on a preset part association rule; According to the preset accuracy value setting rules, the accuracy requirements are assigned to each oral part of interest or associated oral part or other oral part; other oral parts are oral parts in the preset oral part set that do not belong to the oral part of interest or the associated oral part.

[0062] It can be seen that through the above-mentioned optional embodiments, it is possible to determine multiple types of oral parts that need to be paid attention to for orthodontic needs based on the correspondence between preset needs and parts of concern, and then determine the oral parts of concern that need to be paid attention to in general or in specific orthodontic treatment scenarios based on the part association rules that can be set through historical data or physician experience, and finally set the accuracy for each oral part based on the preset accuracy value setting rules, so as to achieve more efficient and accurate generation of three-dimensional models for user orthodontic needs in the future, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0063] As an optional embodiment, the second determination module sets a rule according to a preset accuracy value, and the specific manner of assigning the accuracy requirement to each oral part of interest or associated oral part or other oral part includes: The objective function is set to minimize the weighted sum of the accuracy requirements corresponding to all oral parts; optionally, the weight corresponding to each oral part is inversely proportional to the distance of the oral part from the center of interest; the oral part is the oral part of interest or the associated oral part or other oral part; the center of interest is the geometric center point of the positions of all the oral parts of interest; The setting restriction conditions include that the accuracy requirement value of each oral part is proportional to the importance of the oral part, the accuracy requirement value of each oral part is not less than a preset accuracy requirement threshold, and the difference between the accuracy requirements of two adjacent oral parts is less than a preset difference threshold; optionally, the importance decreases in sequence when the oral part is a focus oral part, an associated oral part, and another oral part; Based on the dynamic programming algorithm, the accuracy requirements of all oral parts are iteratively calculated according to the objective function and constraints until convergence, and the accuracy requirements corresponding to each oral part are obtained.

[0064] It can be seen that through the above-mentioned optional embodiments, the accuracy requirements of different parts of the oral cavity can be iteratively calculated based on the dynamic programming algorithm based on the set objective function and constraints, so as to achieve the final accuracy requirement conditions. On the one hand, it can be greater than the basic requirement threshold and will not be too vague. On the other hand, it can have higher accuracy for important parts, and the overall accuracy value will not be too high to reduce costs, so as to achieve more efficient and accurate generation of three-dimensional models for user orthodontic needs in the future, reduce computing costs, and provide an accurate and low-cost data basis for the user's orthodontic treatment.

[0065] As an optional embodiment, the generation module generates a specific method of a 3D oral model of a target user according to the accuracy requirement and the CT scan image data based on a preset accuracy control modeling rule, including: Based on the transformation association algorithm, according to the scanning equipment lens parameters of each CT scanning image data, the associated three-dimensional mathematical model corresponding to the multiple CT scanning impact data is determined; According to the preset mathematical correspondence relationship of the oral cavity parts, determine the model part corresponding to each oral cavity part in the associated three-dimensional mathematical model; According to the accuracy requirements of the oral part corresponding to each model part, and the correspondence between the preset requirements and the calculation parameters, corresponding calculation parameters are assigned to each model part; optionally, the calculation cost of the calculation parameters is proportional to the accuracy requirements; Based on the adaptive iterative reconstruction algorithm, according to the calculation parameters corresponding to each model part, a three-dimensional reconstruction calculation is performed on multiple CT scan impact data to obtain a three-dimensional oral model of the target user.

[0066] It can be seen that through the above-mentioned optional embodiments, it is possible to determine the associated three-dimensional mathematical model corresponding to multiple CT scan impact data based on the transformation association algorithm, and then assign calculation parameters to the model part corresponding to each oral part, so as to realize the calculation of the oral part with corresponding accuracy based on the corresponding calculation parameters during three-dimensional reconstruction, thereby achieving more efficient and accurate generation of three-dimensional models for the user's orthodontic needs, reducing computing costs, and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0067] As an optional embodiment, the calculation parameters include the number of calculation iterations, the number of images used in the calculation and the calculation interpolation accuracy; the value of the calculation parameter is proportional to the value of the accuracy requirement.

[0068] It can be seen that through the above-mentioned optional embodiments, the content of the calculation parameters and the specific numerical relationship between them and the accuracy requirements are clarified, so that the corresponding accuracy of the oral parts can be calculated based on the corresponding calculation parameters during three-dimensional reconstruction, and the three-dimensional model for the user's orthodontic needs can be generated more efficiently and accurately, reducing the computing cost and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0069] Embodiment 3 See also Figure 3 , Figure 3 This is another three-dimensional oral model precision control system disclosed in an embodiment of the present invention. Figure 3 The three-dimensional oral model accuracy control system described is applied to a data processing system / data processing device / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 3 As shown, the three-dimensional oral model accuracy control system may include: A memory 301 storing executable program codes; a processor 302 coupled to the memory 301; The processor 302 calls the executable program code stored in the memory 301 to execute the steps of the three-dimensional oral model accuracy control method described in the first embodiment.

[0070] Embodiment 4 An embodiment of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the three-dimensional oral model accuracy control method described in the first embodiment.

[0071] Embodiment 5 An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the three-dimensional oral model accuracy control method described in Example 1.

[0072] The above describes specific embodiments of the present specification, and other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily have to be performed in the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0073] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0074] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0075] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification may be in the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the embodiments of this specification may be in the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0076] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0077] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0079] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0080] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0081] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0082] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0083] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0084] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0085] Finally, it should be noted that the three-dimensional oral model accuracy control method and system disclosed in the embodiment of the present invention discloses only the preferred embodiments of the present invention, which are only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A three-dimensional oral model accuracy control method, characterized in that: The method comprises: Determine the orthodontic needs of the target user; the orthodontic needs are used to indicate the oral area that requires orthodontic treatment and the corresponding oral problems; According to the orthodontic needs, determining the accuracy requirements corresponding to different oral parts of the target user; Acquire CT scan image data of the target user; According to the accuracy requirement and the CT scan image data, a three-dimensional oral model of the target user is generated based on preset accuracy control modeling rules; the three-dimensional oral model and the model part corresponding to each oral part meet the corresponding accuracy requirement.

2. The three-dimensional oral model accuracy control method according to claim 1, characterized in that: Determining the orthodontic needs of the target user includes: Acquire the user parameters and historical medical consultation records of the target user; the user parameters include physiological parameters and oral physical parameters; Screening out a target demand forecasting model from a plurality of candidate demand forecasting models according to the user parameters; The historical consultation records are input into the target demand prediction model to obtain the orthodontic needs corresponding to the target user.

3. The three-dimensional oral model accuracy control method according to claim 2, characterized in that: The step of selecting a target demand forecasting model from a plurality of candidate demand forecasting models according to the user parameters includes: For each candidate demand forecasting model, obtaining multiple forecasting records of the candidate demand forecasting model in the verification phase; For each of the prediction records, calculating a first similarity between a user physiological parameter of a prediction user corresponding to the prediction record and the physiological parameter of the target user; Calculate a second similarity between the oral physical parameter of the predicted user corresponding to the prediction record and the oral physical parameter of the target user; Calculating a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record; Calculate the product of the similarity parameter corresponding to the predicted record and the prediction accuracy rate corresponding to the predicted record to obtain a record priority parameter of the predicted record; Calculating an average value of the record priority parameters of all the prediction records of the candidate demand prediction model to obtain a model priority parameter of the candidate demand prediction model; The candidate demand forecasting model with the highest model priority parameter is determined as the target demand forecasting model.

4. The three-dimensional oral model accuracy control method according to claim 1, characterized in that: Determining the orthodontic needs of the target user includes: Acquire multiple oral cavity pictures of the target user through the image acquisition module; Determine the oral problem of the target user based on the image recognition algorithm and the oral picture; The orthodontic needs of the target user are determined based on the oral problems and the correspondence between the preset problems and needs.

5. The three-dimensional oral model accuracy control method according to claim 1, characterized in that: Determining the accuracy requirements corresponding to different oral parts of the target user according to the orthodontic requirements includes: Based on the preset correspondence between the needs and the focus areas, determining a plurality of focus oral areas corresponding to the orthodontic needs; Based on a preset part association rule, determining at least one associated oral part corresponding to each oral part of interest; According to the preset accuracy value setting rules, the accuracy requirements are assigned to each of the oral parts of interest or the associated oral parts or other oral parts; the other oral parts are oral parts in the preset oral part set that do not belong to the oral parts of interest or the associated oral parts.

6. The three-dimensional oral model accuracy control method according to claim 5, characterized in that: The step of assigning a precision requirement to each of the oral cavity parts of interest or the associated oral cavity parts or other oral cavity parts according to a preset precision value setting rule includes: The objective function is set to minimize the weighted sum of the accuracy requirements corresponding to all oral parts; wherein the weight corresponding to each oral part is inversely proportional to the distance of the oral part from the center of interest; the oral part is the oral part of interest or the associated oral part or the other oral part; the center of interest is the geometric center of the positions of all the oral parts of interest; The setting restriction conditions include that the precision requirement value of each oral part is proportional to the importance corresponding to the oral part, the precision requirement value of each oral part is not less than a preset precision requirement threshold, and the difference between the precision requirement values ​​of two adjacent oral parts is less than a preset difference threshold; the importance decreases in sequence when the oral part is the concerned oral part, the associated oral part, and the other oral parts; Based on the dynamic programming algorithm, the accuracy requirements of all the oral parts are iteratively calculated according to the objective function and the constraint conditions until convergence, so as to obtain the accuracy requirement corresponding to each oral part.

7. The three-dimensional oral model accuracy control method according to claim 1, characterized in that: The step of generating a three-dimensional oral model of the target user according to the accuracy requirement and the CT scan image data based on a preset accuracy control modeling rule includes: Based on the transformation association algorithm, according to the scanning device lens parameters of each of the CT scan image data, determining the associated three-dimensional mathematical models corresponding to the plurality of CT scan impact data; According to the preset mathematical correspondence relationship of the oral cavity parts, determining the model part corresponding to each of the oral cavity parts in the associated three-dimensional mathematical model; According to the accuracy requirement of the oral cavity corresponding to each model part, and the correspondence between the preset requirement and the calculation parameter, a corresponding calculation parameter is assigned to each model part; the calculation cost of the calculation parameter is proportional to the accuracy requirement; Based on an adaptive iterative reconstruction algorithm, a three-dimensional reconstruction calculation is performed on the plurality of CT scan impact data according to the calculation parameters corresponding to each of the model parts to obtain a three-dimensional oral model of the target user.

8. The three-dimensional oral model accuracy control method according to claim 7, characterized in that: The calculation parameters include the number of calculation iterations, the number of images used in the calculation and the calculation interpolation accuracy; the value of the calculation parameter is proportional to the value of the accuracy requirement.

9. A three-dimensional oral model precision control system, characterized in that: The system comprises: A first determination module is used to determine the orthodontic needs of the target user; the orthodontic needs are used to indicate the oral parts that need orthodontic treatment and the corresponding oral problems; A second determination module is used to determine the accuracy requirements corresponding to different oral parts of the target user according to the orthodontic requirements; An acquisition module, used to acquire CT scan image data of the target user; A generation module is used to generate a three-dimensional oral model of the target user according to the accuracy requirement and the CT scan image data based on preset accuracy control modeling rules; the three-dimensional oral model and the model part corresponding to each oral part meet the corresponding accuracy requirement.

10. A three-dimensional oral model precision control system, characterized in that: The system comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the three-dimensional oral model accuracy control method as described in any one of claims 1-8.

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