Orthodontic Treatment Planning with Augmented Visual Analysis
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Solution Overview
Problem
Current orthodontic treatment planning methods fail to effectively simulate the impact of tooth movement on facial features, leading to unrealistic previews for patients, as they lack integration of facial feature changes and rely heavily on technician skill and imagination or require perfect execution of complex virtual reconstructions.
Innovation Solution
A method that modifies digital patient pictures by incorporating tooth movement data into facial feature changes, using 3D models and pixel correspondence maps to create a realistic preview of post-treatment facial appearance, ensuring accurate color and feature alignment without subjective editing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual photo editing is used to create post-treatment previews, then facial feature changes can be visualized, but the results are subjective and limited by technician skill
Solution Approach 1:
The patent replaces the manual mechanical photo editing process with an automated computerized system. The system automatically extracts facial features from digital photos, tracks tooth movement from 3D models, and computes corresponding facial feature changes using algorithms, eliminating technician subjectivity and skill limitations while providing objective, reliable treatment previews
Solution Approach 2:
The system enables self-service by automatically performing all editing operations without human intervention. The computerized algorithm independently extracts facial features, correlates tooth movement with facial changes, and generates the final preview, making the process autonomous and eliminating dependency on technician expertise
2Adaptability or versatility
If 3-D virtual reconstruction is used to show treatment outcomes, then comprehensive facial feature changes can be displayed, but perfect execution is extremely challenging and small miscalculations can render the reconstruction unrealistic
Solution Approach 1:
The patent segments the facial reconstruction process into distinct manageable components: extracting specific facial features (eyes, nose, mouth, chin) from digital photos, separately tracking tooth movement from 3D orthodontic models, and independently computing the correlation between tooth movement and facial feature changes. This segmentation allows each component to be processed with high precision and reduces the cumulative error that plagues holistic reconstruction approaches
Solution Approach 2:
The system changes parameters by using measurable, quantifiable data from 3D orthodontic models (tooth position coordinates, movement vectors) and correlating them with measurable facial feature parameters extracted from photos. This parameter-based approach replaces subjective morphing with objective, mathematically-defined transformations that ensure manufacturing precision and eliminate unrealistic results
3Manufacturing precision
If digital 3-D tooth models are used for treatment planning, then precise tooth position control is achieved, but patients cannot visualize their facial appearance after treatment
Solution Approach 1:
The patent merges two previously separate information systems: the precise 3D orthodontic tooth models used for treatment planning and the 2D digital facial photos containing appearance information. By combining these datasets and establishing correlations between tooth movement and facial feature changes, the system simultaneously achieves precise tooth position control and comprehensive facial appearance visualization, eliminating the information loss that occurred when using tooth models alone
Data Source
AI summary
Methods for orthodontic treatment planning include modifying a digital picture of a patient based on a tooth model produced during simulated orthodontic treatment after movement of at least one model tooth to produce a modified digital image depicting the at least one model tooth after movement. The method includes matching and morphing information from the digital picture into the modified digital image. Modifying includes matching a model tooth in the T1 model to a tooth in the digital picture and morphing that information into the modified digital image. Morphing may include projecting a model tooth in the T1 model to an image plane of the digital picture and projecting a model tooth from an intermediate T model to the image plane. Parameterization of the projections of each model may be used to develop a pixel correspondence map, which is usable during rendering of a tooth in the modified digital image.