Intraoral Image Processing for Automatic Prosthesis-Target Tooth Selection
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Solution Overview
Problem
Existing dental CAD/CAM systems require manual user selection of prosthesis target teeth, which is inefficient and time-consuming.
Innovation Solution
A method and apparatus that automatically recognize and select a prosthesis target tooth from intraoral images using a margin line, eliminating the need for manual user selection by processing first and second intraoral images to generate outer and inner surfaces of the prosthesis model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual user selection of prosthesis target teeth is used, then user control and accuracy are improved, but operation time and efficiency deteriorate
Solution Approach 1:
The system performs preliminary actions by automatically extracting the margin line from the prepared tooth surface and pre-calculating the prosthesis target tooth region before user intervention is needed. The margin line extraction and tooth region identification are completed in advance, allowing the user to simply confirm or make minimal adjustments rather than performing manual selection from scratch.
Solution Approach 2:
The system serves itself by automatically identifying and selecting the prosthesis target tooth based on the margin line and prepared tooth surface data. The computer system independently performs the complex tasks of margin line extraction, normal vector calculation, and tooth region segmentation without requiring continuous user guidance or manual selection input.
2Productivity
If automatic tooth selection based on margin line is implemented, then operation efficiency is improved, but system complexity increases
Solution Approach 1:
The complex automatic tooth selection process is segmented into distinct manageable steps: margin line extraction from prepared tooth surface, normal vector calculation at margin points, intersection point determination with pre-prepared tooth surface, and tooth region identification based on curvature values. Each step processes a specific aspect of the data independently, making the overall complex system more manageable and maintainable.
Solution Approach 2:
The margin line serves as an intermediary element that bridges the prepared tooth surface data and the pre-prepared tooth surface data. By using the margin line as a reference mediator, the system can automatically transfer information between the two data sources to identify the target tooth region, simplifying the complex relationship between the two datasets.
3Measurement precision
If automatic recognition using curvature values and normal vectors is used, then selection accuracy is improved, but processing time increases
Solution Approach 1:
The system uses partial action by calculating curvature values and normal vectors only at specific critical points (margin line intersection points and selected surface points) rather than performing comprehensive calculations across the entire tooth surface. This selective calculation approach maintains sufficient accuracy for reliable tooth identification while significantly reducing the overall processing time required.
Data Source
AI summary
A method and apparatus for processing an intraoral image are disclosed. The method of processing an intraoral image includes obtaining a first intraoral image including pre-preparation tooth data and a second intraoral image including preparation tooth data, obtaining a margin line based on the preparation tooth data, and automatically recognizing and selecting a prosthesis target tooth from at least one of the first intraoral image and the second intraoral image based on the margin line.