Gap Detection in 3D Dental Meshes for Ectopic and Missing Teeth
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Solution Overview
Problem
Existing dental scan technologies struggle to accurately identify and number ectopic and missing teeth in 3D dental mesh models, leading to misidentification or omission of these abnormal teeth during orthodontic diagnostics and treatment planning.
Innovation Solution
A processor-based system that automatically detects gaps between adjacent teeth, determines if a tooth is missing or ectopic by exceeding a threshold, and renumbers the teeth to account for these abnormalities, using buccal/lingual and mesial/distal positions, and creates an orthodontic treatment plan to reposition the teeth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated tooth segmentation systems are used to identify teeth in 3D dental mesh models, then the efficiency and productivity of orthodontic diagnostics is improved, but ectopic and missing teeth are misidentified or missed entirely, reducing measurement precision
Solution Approach 1:
The system segments the dental arch into multiple regions and analyzes each region separately to identify teeth. This allows the system to detect gaps between teeth and determine whether teeth are missing or ectopic by comparing the segmented regions against expected tooth positions, thereby improving both efficiency and accuracy.
Solution Approach 2:
The system uses gap detection as an intermediary step between raw 3D mesh data and final tooth identification. By detecting gaps between adjacent teeth and using this information to inform the numbering process, the system can identify ectopic and missing teeth that conventional direct segmentation methods miss.
2Speed
If conventional digital scanning technologies perform optical scans and generate 3D dental mesh models, then the speed of capturing dental data is improved, but the ability to detect abnormal teeth positioning is reduced
Solution Approach 1:
The system performs preliminary gap detection and analysis before final tooth numbering and identification. By pre-processing the 3D mesh data to identify potential gaps and abnormal positions, the system prepares the data structure to facilitate accurate detection of ectopic and missing teeth in subsequent processing stages.
Solution Approach 2:
The system uses feedback from gap detection results to adjust the tooth numbering process. When gaps exceeding thresholds are detected, the system modifies its identification algorithm to account for potential ectopic or missing teeth, creating a feedback loop that improves detection accuracy without requiring manual intervention.
3Ease of operation
If automated systems number teeth sequentially in 3D dental mesh models, then the simplicity and ease of operation is improved, but the reliability of tooth numbering in the presence of missing or ectopic teeth deteriorates
Solution Approach 1:
The tooth numbering process is made dynamic and adaptive rather than purely sequential. The system adjusts the numbering sequence based on detected gaps and abnormal positions, automatically modifying its behavior to account for missing or ectopic teeth while maintaining automated operation. This dynamic approach preserves ease of use while improving reliability.
Solution Approach 2:
The system changes key parameters such as gap thresholds and numbering step sizes based on detected dental conditions. When ectopic or missing teeth are suspected, the system modifies its detection and numbering parameters to improve accuracy, allowing it to maintain simple automated operation while adapting to complex dental scenarios.
Data Source
AI summary
Systems and methods for detecting missing or ectopic teeth. Methods may include accessing a digital model of a dental arch that includes tooth identifiers assigned to teeth of the dental arch based on tooth type. Methods may include detecting a missing or ectopic tooth in the digital model by identifying one or both of: a gap that exceeds a gap threshold between adjacent teeth of the dental arch, and tooth identifiers of adjacent teeth of the dental arch that do not match corresponding adjacent teeth of an ideal dental model. The methods may include re-assigning the tooth identifiers to the teeth of the digital model to account for the detected missing or ectopic tooth.