Iterative Tooth Model Selection for Dental CAD Automation
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Solution Overview
Problem
Current methods for determining virtual tooth restorations in dental CAD/CAM systems are cumbersome and time-consuming, often requiring significant operator interaction and failing to effectively automate the process, leading to subjective and non-reproducible results with functional-aesthetic deficits.
Innovation Solution
A model-based method using a parameterized tooth model database with geometric transformations, where optimal tooth models are iteratively selected and adapted to scan data to meet functional-aesthetic criteria, minimizing operator interaction and ensuring high precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If model-based methods are used to automate tooth restoration determination, then productivity and objectivity are improved, but manufacturing precision and functional-aesthetic quality may deteriorate due to automated algorithm limitations
Solution Approach 1:
The system implements iterative optimization where the algorithm continuously evaluates candidate tooth models against multiple functional-aesthetic criteria, refines the selection based on quality values, and converges on optimal solutions. This feedback mechanism ensures automated determination maintains high precision by constantly comparing results against established dental standards and adjusting selections accordingly.
Solution Approach 2:
The system transforms complex functional-aesthetic criteria into quantifiable parameters and optimization functions. By converting qualitative dental requirements into measurable parameters that can be processed algorithmically, the system enables automated determination while maintaining precision through mathematical optimization rather than subjective judgment.
2Manufacturing precision
If interactive computer-aided creation is used, then manufacturing precision can be maintained through operator control, but productivity deteriorates due to time-consuming manual processes
Solution Approach 1:
The system enables self-service automated determination where the algorithm independently performs tooth restoration determination without requiring operator intervention. The system autonomously processes scan data, applies optimization criteria, and generates restoration plans, eliminating manual interaction while maintaining precision through algorithmic optimization based on established dental standards.
Solution Approach 2:
The system replaces manual interactive processes with automated computational algorithms. By substituting operator-based mechanical interaction with computer-based optimization algorithms that evaluate multiple criteria simultaneously, the system achieves both high productivity through automation and maintained precision through systematic evaluation of functional-aesthetic requirements.
3Adaptability or versatility
If geometric transformations are applied to tooth models, then adaptability to individual patient anatomy is improved, but device complexity increases due to transformation algorithms
Solution Approach 1:
The system uses parameter-based geometric transformations where tooth models are adapted through controlled modification of geometric parameters rather than complex arbitrary transformations. By changing specific parameters such as scale, rotation, and position based on patient anatomy, the system achieves high adaptability while keeping the transformation process systematic and computationally manageable.
Solution Approach 2:
The system employs universal tooth models that can be adapted to various patient anatomies through standardized geometric transformations. These multi-functional base models serve as templates that can be transformed to fit different oral structures, reducing the need for highly complex patient-specific modeling while maintaining high adaptability through systematic parameter adjustment.
Data Source
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AI summary
The invention relates to a method for determining virtual tooth restorations on the basis of scanned data (D) of oral structures, in which a model database (DB) is used, which contains a number of parameterized tooth models (M) for each of a variety tooth types, wherein the parameterization is carried out on the basis of model parameters which comprise position and/or shape parameters, and wherein each tooth model (M) is linked with a number of tooth models (M) of the same tooth type (L). For each desired tooth type, an optimal tooth model (M) is determined from the model database (DB) using an iterative method, in which initially at least one start tooth model (M) of the desired tooth type is selected from the model database (DB) and then, starting with said start tooth model (M), during each iteration step (S) a tooth model (M) is tested with respect to a quality value. The tooth model (M) to be currently tested is adapted to the scanned data (D) by varying model parameters for customization purposes, and a quality value is calculated for the customization. In addition, at least one tooth model (M) to be linked to the tooth model (M) to be tested is likewise customized, and a quality value is calculated. On the basis of the calculated quality values, optionally a new tooth model (M) to be tested of the desired tooth type is selected from the model database (DB) for the next iteration step (S). The iteration is terminated when a quality criterion is reached, and finally at least one virtual tooth restoration (R) is determined from the optimal tooth models (M) and scanned data (D). The invention further relates to a method for generating a model database (DB) for use in such a method, to a method for producing or selecting a tooth restoration part, and to a tooth restoration determination system (5) for determining virtual tooth restorations (R).