Dental 3D Arch Model Correction Using 2D Image Matching
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Solution Overview
Problem
Current methods for manufacturing orthodontic appliances often result in defects in three-dimensional digital models of patients' arches due to scanner resolution and operation issues, leading to time-consuming and costly corrections, potential treatment failures, and patient inconvenience.
Innovation Solution
A method that involves acquiring two-dimensional images of the arch, searching for optimal virtual acquisition conditions to correct the digital model, and comparing these images to detect and correct defects, using metaheuristic optimization methods to refine the model quickly and accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the scanner resolution is increased to improve model accuracy, then manufacturing precision improves, but acquisition time and cost increase
Solution Approach 1:
The patent applies preliminary action by performing defect correction through image processing and virtual acquisition condition search before the orthodontic treatment manufacturing process. The system pre-identifies and corrects defects in the reference model using 2D images and computational methods, so that the corrected model is ready for manufacturing without requiring additional patient visits or rescan procedures. This preliminary correction step prevents downstream delays and ensures manufacturing precision is achieved without increasing acquisition time.
2Manufacturing precision
If manual defect correction is performed to improve model quality, then manufacturing precision improves, but productivity decreases
Solution Approach 1:
The patent replaces the manual mechanical correction process with an automated computational system. Instead of orthodontists or technicians manually inspecting and correcting 3D model defects, the system uses image processing algorithms, metaheuristic optimization methods, and virtual acquisition condition search to automatically detect and correct defects. This substitution of automated computational methods for manual operations maintains high model quality while dramatically increasing correction speed and productivity.
Solution Approach 2:
The system applies self-service by enabling the reference model to correct its own defects through automated processing. The defect correction system independently identifies errors in the 3D model, searches for optimal virtual acquisition conditions, and performs corrections without requiring external manual intervention. This self-correcting capability eliminates the need for time-consuming manual review and adjustment processes.
3Device complexity
If defects are not corrected to maintain simplicity, then device complexity remains low, but reliability decreases
Solution Approach 1:
The patent applies segmentation by dividing the defect correction process into distinct automated modules: 2D image acquisition, virtual acquisition condition search, defect detection through image comparison, and model correction. Each module performs a specific function independently, maintaining process clarity and simplicity while ensuring comprehensive defect correction. This segmented approach to automated processing preserves ease of operation while achieving high reliability through systematic error detection and correction.
Data Source
AI summary
A method of correction of a three-dimensional digital model of an arch of a patient or “reference model.” The method includes the following steps: acquisition of at least one two-dimensional image of the arch, called updated image (Ia1;Ia2), in actual acquisition conditions; search, for each updated image, of virtual acquisition conditions providing a two-dimensional image of the reference model, which maximizes the fit with the updated image, or “reference image” (Ir1;Ir2); comparison of the reference image with the updated image to detect differences; and correction of the reference model to reduce said differences to get a corrected reference model.