Photo-realistic Dental Aligner Visualization via 2D Template Mapping
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Solution Overview
Problem
Patients undergoing dental aligner treatment cannot visualize the planned final outcome of their treatment plan without 3D representations of their teeth, making it difficult to appreciate the benefits of the treatment.
Innovation Solution
A method and system that generate photo-realistic images of repositioned teeth by receiving a 2D image of a patient's dentition, using a template dentition, and applying machine learning models to determine tooth movements from initial to final positions, allowing for the creation of a visual treatment plan without the need for initial 3D scans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D representations of patient teeth are used to formulate a treatment plan, then the accuracy of the planned final outcome visualization is improved, but the complexity of the procedure and time required increase due to the need for professional 3D scanning and processing
Solution Approach 1:
The patent uses a template dentition as a standardized copy or model that can be applied to patient-specific 2D images. Instead of creating custom 3D representations for each patient, the system uses pre-defined template teeth that are mapped onto the patient's 2D image, significantly reducing procedural complexity while maintaining visualization accuracy
Solution Approach 2:
The patent extracts only the essential information needed for visualization from the patient's dentition by working with 2D images rather than requiring complete 3D scans. This extraction approach focuses on the critical visual elements needed to show treatment outcomes without the overhead of full 3D data acquisition and processing
2Measurement precision
If 3D representations of patient teeth are obtained through professional scanning, then the realism and accuracy of the final outcome visualization is improved, but the time required for the procedure increases
Solution Approach 1:
The system uses template dentition models that have been pre-rendered with realistic appearance. These templates can be quickly applied to patient 2D images without requiring time-consuming 3D scanning and rendering processes, thus maintaining visual realism while dramatically reducing processing time
Solution Approach 2:
The template dentition models are prepared in advance with realistic textures, lighting, and anatomical details. This preliminary preparation allows the system to skip the time-consuming steps of 3D scanning, processing, and rendering during the actual treatment planning session, delivering realistic visualizations immediately
3Measurement precision
If dental professionals perform 3D scanning and treatment planning, then the accuracy of the treatment plan is improved, but the ease of operation for patients increases when using simple 2D image uploads
Solution Approach 1:
The system creates an accurate treatment plan by mapping template teeth onto patient 2D images, preserving the accuracy normally associated with professional 3D scanning. Patients can simply upload photos, making the process as easy as possible while the backend maintains professional-grade planning accuracy
Solution Approach 2:
The system acts as an intermediary that processes simple patient-uploaded 2D images into accurate treatment plans using template-based algorithms. This intermediary approach bridges the gap between simple patient input and professional-grade output, eliminating the need for patients to undergo complex scanning procedures while maintaining plan accuracy
Data Source
AI summary
A method to generate a photo realistic dentition image includes receiving a 2D image of a patient dentition including a plurality of patient teeth. The method includes obtaining a template dentition including a plurality of template teeth that correspond with a subset of the patient teeth. The method includes generating a tooth location input to position the plurality of template teeth relative to the subset of the plurality of patient teeth. The method includes identifying an area of generation in the 2D image including a plurality of pixels and contextual information. The method includes generating new photo realistic teeth based on the tooth location input, the contextual information, and the area of generation. The method includes disposing the photo realistic teeth in the 2D image.