Automated Tooth Type Detection Using 3D Scanning and Classifiers
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Solution Overview
Problem
Current methods for determining tooth type and eruption status in pediatric orthodontic cases are manual and time-consuming, requiring physical inspections or image/scans, which can be costly and inefficient.
Innovation Solution
An automated system that uses 3D scanning and machine learning algorithms, such as PCA and binary classifiers, to accurately predict tooth type and eruption status, enabling the generation of orthodontic treatment plans and aligner design without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection methods are used to determine tooth type and eruption status, then the system can identify tooth characteristics, but the process is time-consuming and costly
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated image processing system that uses computer vision algorithms to detect tooth characteristics. The system automatically analyzes dental images to determine tooth type and eruption status, eliminating the need for manual physical inspection while maintaining detection accuracy.
Solution Approach 2:
The system creates digital copies of dental images and processes these copies through automated algorithms. By working with digital representations rather than directly manipulating physical teeth, the system enables rapid, repeatable analysis without time-consuming manual intervention.
2Measurement precision
If manual inspection methods are used, then tooth characteristics can be identified, but the process is expensive
Solution Approach 1:
The patent replaces expensive manual inspection processes with automated digital image analysis. The system uses computer-based algorithms to determine tooth characteristics, eliminating the need for costly manual procedures while maintaining or improving detection accuracy through standardized computational methods.
Solution Approach 2:
The system performs self-service analysis by automatically processing dental images and generating treatment recommendations without requiring expensive manual expert intervention. The automated system independently completes the evaluation process, reducing overall costs while maintaining professional-level accuracy.
3Productivity
If automated detection systems are implemented, then time and cost are reduced, but the system complexity increases
Solution Approach 1:
The patent divides the complex detection task into separate functional modules: image acquisition, tooth segmentation, feature extraction, and classification. By segmenting the system into manageable components, the patent reduces overall complexity while maintaining high productivity through automated processing of each stage.
Solution Approach 2:
The system uses a universal image processing framework that can handle multiple tooth types and eruption statuses through a single integrated algorithm. This multi-functional approach simplifies the system structure compared to having separate specialized systems, while maintaining high detection speed and accuracy.
Data Source
AI summary
Methods and systems for automatically determining an eruption status and/or primary or permanent tooth type of a target tooth. Methods may include determining tooth shape features of the target tooth from a 3D model of the patient's teeth. The methods may also include normalizing at least some of the tooth shape features using the tooth shape features of one or more reference teeth. The normalized tooth shape features may be applied to a classifier. Applying the normalized tooth shape features to the classifier may include applying either a first level binary classifier or a first level binary classifier and a second level binary classifier to the normalized tooth shape features.