Facial Shape Classification for Data-Driven Denture Tooth Selection
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Solution Overview
Problem
Current methods for selecting artificial teeth for complete dentures rely heavily on user experience, leading to inconsistent results and a cumbersome process, without precise data-based selection.
Innovation Solution
A facial shape classification method and device that automatically classifies and provides optimal artificial tooth shapes based on patient-specific facial data, minimizing user manipulation and enhancing aesthetic satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If facial recognition AI is used to classify facial shapes, then design time is reduced, but the system complexity and cost increase due to requiring specialized AI hardware and large datasets
Solution Approach 1:
The patent uses 2D photographs as simplified copies of 3D facial data to train the neural network, avoiding the need for complex 3D scanning hardware. The system creates a digital model (copy) of the facial shape from 2D images, which then guides the denture design process, significantly reducing system complexity while maintaining design efficiency
Solution Approach 2:
The facial shape classification system is designed to work with multiple types of input data (2D photographs, 3D scans) and can be applied to various denture design scenarios. The neural network model serves multiple functions: facial shape recognition, classification into predefined categories, and generation of design parameters, reducing the need for separate specialized systems
2Device complexity
If traditional manual facial shape determination is used, then system complexity is low, but design time increases and design accuracy decreases
Solution Approach 1:
The system performs preliminary classification of facial shapes into predefined categories (V-shaped, square, round, etc.) using the neural network before the actual denture design process begins. This preliminary action automatically establishes key design parameters and guidelines, significantly reducing the time required for manual assessment and design planning while keeping the overall system relatively simple
3Measurement precision
If detailed 3D facial scanning is used to determine facial shape, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
The patent creates accurate 2D representations (copies) of the facial structure from photographs that capture sufficient geometric information for classification. These 2D images serve as adequate copies for the intended purpose of facial shape categorization, eliminating the need for complex 3D scanning equipment while maintaining sufficient measurement precision for denture design
Solution Approach 2:
The system extracts only the essential facial shape characteristics needed for denture design from the input images, rather than capturing and processing complete 3D facial geometry. The neural network extracts key features (jawline shape, cheekbone prominence, chin contour) and classifies them, taking out only the necessary information and avoiding the complexity of full 3D scanning systems
Data Source
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AI summary
Disclosed are a facial shape classification method and a denture design device therefor. A facial shape classification method according to an embodiment and a denture design device therefor classify and provide an artificial tooth shape according to the facial shape of a patient, and thus can minimize a user's manipulation, reduce inconvenience, and increase a patient's aesthetic satisfaction.