Dental Arch 3D Model Generation from 2D Images
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Solution Overview
Problem
Current methods for generating three-dimensional models of dental arches for manufacturing dental aligners are time-consuming, prone to errors, and require specialized equipment, such as dental impressions or intraoral scans.
Innovation Solution
A method and system that use a model generation system to receive two-dimensional images of a dental arch, generate a point cloud, and create a three-dimensional model, allowing for the manufacturing of custom dental aligners without the need for traditional impression kits or intraoral scans, leveraging a pre-trained image detector and model generation engine with LSTM encoder and decoder to refine the point cloud and produce accurate 3D models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional dental impressions or intraoral scans are used to generate 3D models, then measurement precision is improved, but device complexity and time consumption increase
Solution Approach 1:
The patent uses 2D photographs as simple copies of the dental arch instead of requiring complex 3D scanning equipment. The machine learning model processes these 2D image copies to reconstruct the 3D model, eliminating the need for specialized intraoral scanners while maintaining sufficient accuracy for dental aligner manufacturing
Solution Approach 2:
The patent replaces the mechanical 3D scanning system with a computational approach using machine learning. Instead of physically scanning the teeth with specialized equipment, the system uses 2D images processed through trained neural networks to generate the 3D model, substituting mechanical measurement with algorithmic reconstruction
2Manufacturing precision
If traditional dental impressions or intraoral scans are used, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary 3D model generation directly from 2D images without requiring preliminary dental impressions or office visits. Users can capture images at home and the system generates the 3D model immediately, eliminating the time loss associated with scheduling and attending appointments for traditional impressions
Solution Approach 2:
The patent enables users to perform the dental impression function themselves by taking photographs with their own devices. This self-service approach eliminates the need for professional operators to take impressions in the office, significantly reducing the time loss associated with appointments while maintaining manufacturing precision through the machine learning reconstruction
3Measurement precision
If specialized equipment is used for dental scanning, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent makes the dental measurement system universal by using common 2D imaging devices that everyone already possesses (smartphones, cameras) instead of specialized medical equipment. The machine learning model is trained to extract precise dental measurements from these universal devices, making the system accessible to any user without requiring professional equipment or training
Data Source
AI summary
A method includes receiving, by a model generation engine, an image of a dental arch of a user, executing, by the model generation engine, a machine learning model that is trained to receive the image and output a representation of the image, where in at least one iteration during training, the machine learning model determines a difference between one or more features extracted from an iteration of the representation of the image and a corresponding one or more features extracted from the image, and the method further includes outputting, by the model generation engine, an output representation of the image.