Three-dimensional oral model precision control method and system

Abstract

The present invention discloses a method and system for controlling the accuracy of a three-dimensional oral model, the method comprising: determining the orthodontic needs of a target user; the orthodontic needs are used to indicate the oral parts and corresponding oral problems that require orthodontic treatment; determining the accuracy requirements corresponding to different oral parts of the target user based on the orthodontic needs; obtaining CT scan image data of the target user; generating a three-dimensional oral model of the target user based on the accuracy requirements and the CT scan image data and preset accuracy control modeling rules; the three-dimensional oral model and the model portion corresponding to each of the oral parts meet the corresponding accuracy requirements. It can be seen that the present invention can generate a three-dimensional model for the user's orthodontic needs more efficiently and accurately, reduce computing costs, and provide an accurate and low-cost data foundation for the user's orthodontic treatment.

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 from 3D oral models to formulate more reasonable orthodontic treatment plans. However, when modeling and calculating 3D oral models, existing technologies do not fully consider the different orthodontic needs of users to control the accuracy of model calculation or display. Therefore, they often consume 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 precision 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:

[0005] Determine the orthodontic needs of the target user; the orthodontic needs are used to indicate the oral area requiring orthodontic treatment and the corresponding oral problems;

[0006] Determining the precision requirements corresponding to different oral areas of the target user according to the orthodontic needs;

[0007] Acquiring CT scan image data of the target user;

[0008] According to the accuracy requirements 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 requirements.

[0009] As an optional embodiment, in the first aspect of the present invention, determining the orthodontic needs of the target user includes:

[0010] Obtaining user parameters and historical medical consultation records of the target user; the user parameters include physiological parameters and oral physical parameters;

[0011] Screening out a target demand forecasting model from a plurality of candidate demand forecasting models according to the user parameters;

[0012] The historical medical consultation records are input into the target demand prediction model to obtain the orthodontic needs corresponding to the target user.

[0013] As an optional implementation, in the first aspect of the present invention, screening out a target demand forecasting model from a plurality of candidate demand forecasting models according to the user parameters includes:

[0014] For each candidate demand forecasting model, obtaining multiple forecasting records of the candidate demand forecasting model in the verification phase;

[0015] 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;

[0016] 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;

[0017] Calculating a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record;

[0018] Calculating 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;

[0019] Calculating an average value of the record priority parameters of all the prediction records of the candidate demand forecasting model to obtain a model priority parameter of the candidate demand forecasting model;

[0020] The candidate demand forecasting model with the highest model priority parameter is determined as the target demand forecasting model.

[0021] As an optional embodiment, in the first aspect of the present invention, determining the orthodontic needs of the target user includes:

[0022] Acquire multiple oral images of the target user through the image acquisition module;

[0023] Determine the oral problems of the target user based on an image recognition algorithm and the oral picture;

[0024] The orthodontic needs of the target user are determined based on the oral problems and the correspondence between the preset problems and needs.

[0025] As an optional embodiment, 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:

[0026] Determining multiple oral cavity areas of interest corresponding to the orthodontic needs based on the preset correspondence between the needs and the areas of interest;

[0027] Determining at least one associated oral region corresponding to each oral region of interest based on a preset region association rule;

[0028] 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.

[0029] As an optional embodiment, in the first aspect of the present invention, assigning an accuracy requirement to each of the oral region of interest, the associated oral region, or other oral region according to a preset accuracy value setting rule includes:

[0030] 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, the associated oral part, or the other oral part; and the center of interest is the geometric center of the positions of all the oral parts of interest;

[0031] 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 requirements of two adjacent oral parts is less than a preset difference threshold; the importance decreases in sequence when the oral part is the focus oral part, the associated oral part, and the other oral parts;

[0032] Based on a 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.

[0033] As an optional embodiment, 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 preset accuracy control modeling rules includes:

[0034] Determining, based on a transformation association algorithm and according to a scanning device lens parameter of each of the CT scan image data, an associated three-dimensional mathematical model corresponding to a plurality of the CT scan impact data;

[0035] According to a preset mathematical correspondence relationship between the oral cavity parts, determining a model portion corresponding to each of the oral cavity parts in the associated three-dimensional mathematical model;

[0036] Assigning corresponding calculation parameters to each model part according to the accuracy requirements of the oral region corresponding to each model part and the correspondence between the preset requirements and the calculation parameters; the calculation cost of the calculation parameters is proportional to the accuracy requirements;

[0037] 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.

[0038] As an optional embodiment, 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 values ​​of the calculation parameters are proportional to the value of the accuracy requirement.

[0039] A second aspect of an embodiment of the present invention discloses a three-dimensional oral model accuracy control system, the system comprising:

[0040] A first determination module is used to 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;

[0041] 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;

[0042] An acquisition module, configured to acquire CT scan image data of the target user;

[0043] A generation module is used to generate a three-dimensional oral model of the target user based on the accuracy requirements and the CT scan image data and on the basis of preset accuracy control modeling rules; the three-dimensional oral model and the model portion corresponding to each of the oral parts meet the corresponding accuracy requirements.

[0044] As an optional embodiment, 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:

[0045] Obtaining user parameters and historical medical consultation records of the target user; the user parameters include physiological parameters and oral physical parameters;

[0046] Screening out a target demand forecasting model from a plurality of candidate demand forecasting models according to the user parameters;

[0047] The historical medical consultation records are input into the target demand prediction model to obtain the orthodontic needs corresponding to the target user.

[0048] As an optional embodiment, in the second aspect of the present invention, the specific manner in which the first determination module selects the target demand forecast model from the plurality of candidate demand forecast models according to the user parameters includes:

[0049] For each candidate demand forecasting model, obtaining multiple forecasting records of the candidate demand forecasting model in the verification phase;

[0050] 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;

[0051] 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;

[0052] Calculating a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record;

[0053] Calculating 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;

[0054] Calculating an average value of the record priority parameters of all the prediction records of the candidate demand forecasting model to obtain a model priority parameter of the candidate demand forecasting model;

[0055] The candidate demand forecasting model with the highest model priority parameter is determined as the target demand forecasting model.

[0056] As an optional embodiment, 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:

[0057] Acquire multiple oral images of the target user through the image acquisition module;

[0058] Determine the oral problems of the target user based on an image recognition algorithm and the oral picture;

[0059] The orthodontic needs of the target user are determined based on the oral problems and the correspondence between the preset problems and needs.

[0060] As an optional embodiment, 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:

[0061] Determining multiple oral cavity areas of interest corresponding to the orthodontic needs based on the preset correspondence between the needs and the areas of interest;

[0062] Determining at least one associated oral region corresponding to each oral region of interest based on a preset region association rule;

[0063] 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.

[0064] As an optional embodiment, 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 region of interest, the associated oral region, or other oral region includes:

[0065] 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, the associated oral part, or the other oral part; and the center of interest is the geometric center of the positions of all the oral parts of interest;

[0066] 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 requirements of two adjacent oral parts is less than a preset difference threshold; the importance decreases in sequence when the oral part is the focus oral part, the associated oral part, and the other oral parts;

[0067] Based on a 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.

[0068] As an optional embodiment, in the second aspect of the present invention, the specific manner in which the generation module generates the three-dimensional oral model of the target user based on the accuracy requirement and the CT scan image data and preset accuracy control modeling rules includes:

[0069] Determining, based on a transformation association algorithm and according to a scanning device lens parameter of each of the CT scan image data, an associated three-dimensional mathematical model corresponding to a plurality of the CT scan impact data;

[0070] According to a preset mathematical correspondence relationship between the oral cavity parts, determining a model portion corresponding to each of the oral cavity parts in the associated three-dimensional mathematical model;

[0071] Assigning corresponding calculation parameters to each model part according to the accuracy requirements of the oral region corresponding to each model part and the correspondence between the preset requirements and the calculation parameters; the calculation cost of the calculation parameters is proportional to the accuracy requirements;

[0072] 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.

[0073] As an optional embodiment, 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 values ​​of the calculation parameters are proportional to the values ​​of the accuracy requirements.

[0074] A third aspect of the present invention discloses another three-dimensional oral model precision control system, the system comprising:

[0075] a memory storing executable program code;

[0076] a processor coupled to the memory;

[0077] 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.

[0078] 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.

[0079] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0080] 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 scan image data, thereby being able to more efficiently and accurately generate a three-dimensional model for the user's orthodontic needs, reducing computing costs, and providing an accurate and low-cost data basis for the user's orthodontic treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] 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.

[0082] 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.

[0083] 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.

[0084] 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

[0085] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0086] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different objects, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or device.

[0087] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0088] The present invention discloses a method and system for controlling the accuracy of a three-dimensional oral model. These methods can determine the accuracy requirements for different oral regions based on the orthodontic needs of the target user, and then generate a three-dimensional oral model that meets these requirements based on the accuracy requirements and CT scan image data. This allows for more efficient and accurate generation of a three-dimensional model tailored to the user's orthodontic needs, reducing computational costs and providing an accurate and low-cost data foundation for the user's orthodontic treatment. These are described in detail below.

[0089] Example 1

[0090] See also Figure 1 , Figure 1 This 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:

[0091] 101. Determine the orthodontic needs of target users.

[0092] Optionally, orthodontic needs are used to indicate the oral area requiring orthodontic treatment and the corresponding oral problems.

[0093] 102. Based on orthodontic needs, determine the accuracy requirements corresponding to different oral parts of the target user.

[0094] 103. Obtain CT scan image data of the target user.

[0095] 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.

[0096] Optionally, the three-dimensional oral model and the model portion corresponding to each oral region meet corresponding accuracy requirements.

[0097] 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.

[0098] As an optional embodiment, in the above step, determining the orthodontic needs of the target user includes:

[0099] Obtain the target user's user parameters and historical medical records; optionally, the user parameters include physiological parameters and oral physical parameters;

[0100] Screening out a target demand forecasting model from multiple candidate demand forecasting models based on user parameters;

[0101] Input historical consultation records into the target demand prediction model to obtain the orthodontic needs corresponding to the target users.

[0102] It can be seen that through the above optional embodiments, the 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 based on the user's historical medical records, and assist in more efficiently and accurately generating a three-dimensional model for the user's orthodontic needs, reducing computing costs, and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0103] 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:

[0104] For each candidate demand forecasting model, obtaining multiple forecasting records of the candidate demand forecasting model in the verification phase;

[0105] 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;

[0106] 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;

[0107] Calculating a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record;

[0108] Calculate the product of the similarity parameter corresponding to the predicted record and the prediction accuracy corresponding to the predicted record to obtain a record priority parameter of the predicted record;

[0109] Calculating an average value of the record priority parameters of all prediction records of the candidate demand forecasting model to obtain the model priority parameter of the candidate demand forecasting model;

[0110] The candidate demand forecasting model with the highest model priority parameter is determined as the target demand forecasting model.

[0111] It can be seen that through the above optional embodiments, the target demand prediction model can be screened out based on the similarity calculation between the user parameters in the prediction records of the verification stage of each candidate model and the current user, as well as the prediction accuracy calculation, so as to facilitate the accurate prediction of the target user's orthodontic needs based on the user's historical consultation records in the future, and assist in 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.

[0112] As an optional embodiment, in the above step, determining the orthodontic needs of the target user includes:

[0113] Acquire multiple oral images of the target user through the image acquisition module;

[0114] Identify the target user's oral problems based on image recognition algorithms and oral pictures;

[0115] Determine the orthodontic needs of target users based on oral problems and the correspondence between preset problems and needs.

[0116] It can be seen that through the above 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 embodiments to jointly and accurately determine the user's oral orthodontic needs, and can achieve more efficient and accurate generation of 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.

[0117] As an optional embodiment, in the above step, determining the accuracy requirements corresponding to different oral parts of the target user according to orthodontic requirements includes:

[0118] Based on the preset correspondence between needs and areas of concern, determine multiple oral areas of concern corresponding to orthodontic needs;

[0119] Determining at least one associated oral region corresponding to each oral region of interest based on a preset region association rule;

[0120] According to the preset accuracy value setting rules, the accuracy requirements are assigned to each oral part of interest or related 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 related oral parts.

[0121] 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 foundation for the user's orthodontic treatment.

[0122] As an optional embodiment, in the above steps, assigning the accuracy requirement to each oral region of interest or associated oral region or other oral region according to a preset accuracy value setting rule includes:

[0123] 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;

[0124] The set restriction conditions include that the precision requirement value of each oral part is proportional to the importance of 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 requirements of two adjacent oral parts is less than a preset difference threshold; optionally, the importance decreases in order when the oral part is a focus oral part, a related oral part, and another oral part;

[0125] 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.

[0126] It can be seen that through the above optional embodiments, the accuracy requirements of different oral parts can be iteratively calculated based on the set objective function and constraints based on the dynamic programming algorithm, so that the final accuracy requirement conditions can be greater than the basic requirement threshold on the one hand 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 users with accurate and low-cost data foundation for orthodontic treatment.

[0127] As an optional embodiment, in the above steps, generating a 3D oral model of the target user based on the accuracy requirements and the CT scan image data and preset accuracy control modeling rules includes:

[0128] Based on the transformation association algorithm, the three-dimensional mathematical model corresponding to the plurality of CT scan impact data is determined according to the scanning device lens parameters of each CT scan image data;

[0129] According to the preset mathematical correspondence between the oral cavity parts, determining the model portion corresponding to each oral cavity part in the associated three-dimensional mathematical model;

[0130] According to the accuracy requirements of the oral region 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;

[0131] Based on the adaptive iterative reconstruction algorithm, according to the calculation parameters corresponding to each model part, three-dimensional reconstruction calculation is performed on multiple CT scan impact data to obtain a three-dimensional oral model of the target user.

[0132] It can be seen that through the above 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, and 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.

[0133] 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 values ​​of the calculation parameters are proportional to the values ​​of the accuracy requirements.

[0134] It can be seen that through the above 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 a three-dimensional model can be generated more efficiently and accurately for the user's orthodontic needs, reducing computing costs and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0135] Example 2

[0136] See also Figure 2 , Figure 2 This is a schematic diagram of the structure of a three-dimensional oral model precision control system disclosed in an embodiment of the present invention. Figure 2The 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 precision control system may include:

[0137] The first determination module 201 is used to determine the orthodontic needs of the target user.

[0138] Optionally, orthodontic needs are used to indicate the oral area requiring orthodontic treatment and the corresponding oral problems.

[0139] 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.

[0140] The acquisition module 203 is used to acquire the CT scan image data of the target user.

[0141] The generation module 204 is used to generate a three-dimensional oral model of the target user based on the accuracy requirements and the CT scan image data and the preset accuracy control modeling rules.

[0142] Optionally, the three-dimensional oral model and the model portion corresponding to each oral region meet corresponding accuracy requirements.

[0143] 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.

[0144] As an optional embodiment, the specific manner in which the first determination module determines the orthodontic needs of the target user includes:

[0145] Obtain the target user's user parameters and historical medical records; optionally, the user parameters include physiological parameters and oral physical parameters;

[0146] Screening out a target demand forecasting model from multiple candidate demand forecasting models based on user parameters;

[0147] Input historical consultation records into the target demand prediction model to obtain the orthodontic needs corresponding to the target users.

[0148] It can be seen that through the above optional embodiments, the 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 based on the user's historical medical records, and assist in more efficiently and accurately generating a three-dimensional model for the user's orthodontic needs, reducing computing costs, and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0149] As an optional embodiment, the specific manner in which the first determining module selects the target demand forecasting model from multiple candidate demand forecasting models according to the user parameters includes:

[0150] For each candidate demand forecasting model, obtaining multiple forecasting records of the candidate demand forecasting model in the verification phase;

[0151] 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;

[0152] 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;

[0153] Calculating a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record;

[0154] Calculate the product of the similarity parameter corresponding to the predicted record and the prediction accuracy corresponding to the predicted record to obtain a record priority parameter of the predicted record;

[0155] Calculating an average value of the record priority parameters of all prediction records of the candidate demand forecasting model to obtain the model priority parameter of the candidate demand forecasting model;

[0156] The candidate demand forecasting model with the highest model priority parameter is determined as the target demand forecasting model.

[0157] It can be seen that through the above optional embodiments, the target demand prediction model can be screened out based on the similarity calculation between the user parameters in the prediction records of the verification stage of each candidate model and the current user, as well as the prediction accuracy calculation, so as to facilitate the accurate prediction of the target user's orthodontic needs based on the user's historical consultation records in the future, and assist in 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.

[0158] As an optional embodiment, the specific manner in which the first determination module determines the orthodontic needs of the target user includes:

[0159] Acquire multiple oral images of the target user through the image acquisition module;

[0160] Identify the target user's oral problems based on image recognition algorithms and oral pictures;

[0161] Determine the orthodontic needs of target users based on oral problems and the correspondence between preset problems and needs.

[0162] It can be seen that through the above 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 embodiments to jointly and accurately determine the user's oral orthodontic needs, and can achieve more efficient and accurate generation of 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.

[0163] As an optional embodiment, the second determination module determines the specific method of the accuracy requirements corresponding to different oral parts of the target user according to the orthodontic requirements, including:

[0164] Based on the preset correspondence between needs and areas of concern, determine multiple oral areas of concern corresponding to orthodontic needs;

[0165] Determining at least one associated oral region corresponding to each oral region of interest based on a preset region association rule;

[0166] According to the preset accuracy value setting rules, the accuracy requirements are assigned to each oral part of interest or related 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 related oral parts.

[0167] 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 foundation for the user's orthodontic treatment.

[0168] As an optional embodiment, the second determination module sets rules based on preset accuracy values, and the specific manner of assigning the accuracy requirement to each oral region of interest or associated oral region or other oral region includes:

[0169] 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;

[0170] The set restriction conditions include that the precision requirement value of each oral part is proportional to the importance of 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 requirements of two adjacent oral parts is less than a preset difference threshold; optionally, the importance decreases in order when the oral part is a focus oral part, a related oral part, and another oral part;

[0171] 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.

[0172] It can be seen that through the above optional embodiments, the accuracy requirements of different oral parts can be iteratively calculated based on the set objective function and constraints based on the dynamic programming algorithm, so that the final accuracy requirement conditions can be greater than the basic requirement threshold on the one hand 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 users with accurate and low-cost data foundation for orthodontic treatment.

[0173] As an optional embodiment, the generation module generates a 3D oral model of the target user based on the accuracy requirements and the CT scan image data and preset accuracy control modeling rules, including:

[0174] Based on the transformation association algorithm, the three-dimensional mathematical model corresponding to the plurality of CT scan impact data is determined according to the scanning device lens parameters of each CT scan image data;

[0175] According to the preset mathematical correspondence between the oral cavity parts, determining the model portion corresponding to each oral cavity part in the associated three-dimensional mathematical model;

[0176] According to the accuracy requirements of the oral region 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;

[0177] Based on the adaptive iterative reconstruction algorithm, according to the calculation parameters corresponding to each model part, three-dimensional reconstruction calculation is performed on multiple CT scan impact data to obtain a three-dimensional oral model of the target user.

[0178] It can be seen that through the above 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, and 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.

[0179] 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 values ​​of the calculation parameters are proportional to the values ​​of the accuracy requirements.

[0180] It can be seen that through the above 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 a three-dimensional model can be generated more efficiently and accurately for the user's orthodontic needs, reducing computing costs and providing an accurate and low-cost data basis for the user's orthodontic treatment.

[0181] Example 3

[0182] 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 precision control system may include:

[0183] A memory 301 storing executable program code;

[0184] a processor 302 coupled to the memory 301;

[0185] 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.

[0186] Example 4

[0187] 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.

[0188] Example 5

[0189] 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.

[0190] The foregoing description of specific embodiments of the present disclosure is intended to illustrate a method for performing a process. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0191] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having 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 smartphone, 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.

[0192] For the convenience of description, the above devices are described as being divided into 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.

[0193] 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 take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0194] 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 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.

[0195] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0196] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0197] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0198] 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. Memory is an example of a computer-readable medium.

[0199] 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. The 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 disc read-only memory (CD-ROM), digital versatile disc (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 transitory media such as modulated data signals and carrier waves.

[0200] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0201] This specification may be described in the general context of computer-executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like 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 communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media, including storage devices.

[0202] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0203] Finally, it should be noted that the three-dimensional oral model precision control method and system disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, and are only used to illustrate the technical solutions of the present invention, rather than to limit them. 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 various embodiments of the present invention.

Claims

1. A method for controlling the accuracy of a three-dimensional oral model, characterized in that: The method comprises: Determine the orthodontic needs of the target user; the orthodontic needs are used to indicate the oral area requiring 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, including: Determining multiple oral cavity areas of interest corresponding to the orthodontic needs based on the preset correspondence between the needs and the areas of interest; Determining at least one associated oral region corresponding to each oral region of interest based on a preset region association rule; The objective function is set to minimize the weighted sum of the accuracy requirements corresponding to all oral parts; 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 parts; the center of interest is the geometric center point of the positions of all the oral parts of interest; the other oral parts are oral parts in a preset set of oral parts that do not belong to the oral part of interest or the associated oral parts; 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 requirements of two adjacent oral parts is less than a preset difference threshold; the importance decreases in sequence when the oral part is the focus oral part, the associated oral part, and the other oral parts; Based on a dynamic programming algorithm, iteratively calculating the accuracy requirements of all the oral parts according to the objective function and the constraint conditions until convergence, and obtaining the accuracy requirement corresponding to each oral part; Acquiring CT scan image data of the target user; According to the accuracy requirements 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 requirements.

2. The three-dimensional oral model accuracy control method according to claim 1, characterized in that: Determining the orthodontic needs of target users includes: Obtaining 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 medical 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; 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; Calculating a weighted sum of the first similarity and the second similarity to obtain a similarity parameter corresponding to the predicted record; Calculating 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 forecasting model to obtain a model priority parameter of the candidate demand forecasting 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 target users includes: Acquire multiple oral images of the target user through the image acquisition module; Determine the oral problems of the target user based on an 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: Generating 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 includes: Determining, based on a transformation association algorithm and according to a scanning device lens parameter of each of the CT scan image data, an associated three-dimensional mathematical model corresponding to a plurality of the CT scan impact data; According to a preset mathematical correspondence relationship between the oral cavity parts, determining a model portion corresponding to each of the oral cavity parts in the associated three-dimensional mathematical model; Assigning corresponding calculation parameters to each model part according to the accuracy requirements of the oral region corresponding to each model part and the correspondence between the preset requirements and the calculation parameters; the calculation cost of the calculation parameters is proportional to the accuracy requirements; 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.

6. The three-dimensional oral model accuracy control method according to claim 5, 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 values ​​of the calculation parameters are proportional to the value of the accuracy requirement.

7. 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 area that requires orthodontic treatment and the corresponding oral problems; The second determination module is used to determine the accuracy requirements corresponding to different oral parts of the target user according to the orthodontic requirements, including: Determining multiple oral cavity areas of interest corresponding to the orthodontic needs based on the preset correspondence between the needs and the areas of interest; Determining at least one associated oral region corresponding to each oral region of interest based on a preset region association rule; The objective function is set to minimize the weighted sum of the accuracy requirements corresponding to all oral parts; 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 parts; the center of interest is the geometric center point of the positions of all the oral parts of interest; the other oral parts are oral parts in a preset set of oral parts that do not belong to the oral part of interest or the associated oral parts; 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 requirements of two adjacent oral parts is less than a preset difference threshold; the importance decreases in sequence when the oral part is the focus oral part, the associated oral part, and the other oral parts; Based on a dynamic programming algorithm, iteratively calculating the accuracy requirements of all the oral parts according to the objective function and the constraint conditions until convergence, and obtaining the accuracy requirement corresponding to each oral part; An acquisition module, configured 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 based on the accuracy requirements and the CT scan image data and on the basis of preset accuracy control modeling rules; the three-dimensional oral model and the model portion corresponding to each of the oral parts meet the corresponding accuracy requirements.

8. 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 according to any one of claims 1 to 6.

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