Merging Incomplete 3D Dental Models via Geometry Alignment
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Solution Overview
Problem
Traditional dental impression methods are time-consuming and prone to errors, especially with at-home kits, which can result in incomplete or poor-quality impressions, requiring patients to return for retakes.
Innovation Solution
A computing device with a model manager, scan disposer, and merge manager that generates and merges three-dimensional models of dental impressions, aligns geometry based on common anatomical points, selects detailed geometry, and cleans the merged model to create a complete and accurate representation of the dental arch.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If at-home dental impression kits are used, then patient convenience is improved, but impression quality and completeness deteriorate
Solution Approach 1:
The system introduces a digital intermediary (3D scan merging software) between the patient's at-home impression taking and the final dental model creation. The merge manager automatically combines multiple incomplete impressions into a complete digital model, mediating the quality issue caused by patient self-administration while preserving the convenience benefit.
Solution Approach 2:
The system merges multiple incomplete dental impressions into a single complete digital model by aligning geometry based on common anatomical points and selecting the most detailed geometry from each scan. This combining process recovers completeness and quality while maintaining the at-home convenience benefit.
2Manufacturing precision
If traditional dental impression methods are used in-office, then impression quality is improved, but time consumption and patient visits increase
Solution Approach 1:
The system enables patients to perform the impression-taking process themselves at home without requiring dental professional time or in-office resources. The automated merge manager then processes the scans, completely eliminating the need for patient visits while maintaining quality through digital merging.
Solution Approach 2:
The system replaces the mechanical in-office impression-taking process with a digital workflow where patients scan their own impressions at home. The merge manager uses computational geometry alignment and selection algorithms to substitute for the traditional professional impression-taking and model-making process, saving time while maintaining quality.
3Reliability
If multiple incomplete impressions are merged, then model completeness is improved, but processing complexity increases
Solution Approach 1:
The system performs preliminary alignment of the multiple impressions by identifying common anatomical points before the actual merging process. This preliminary organization of data simplifies the subsequent merging operations and makes the overall process more manageable despite handling multiple incomplete models.
Solution Approach 2:
The merging process is divided into distinct segments: alignment based on common anatomical points, selection of detailed geometry from each scan, and final model generation. This segmentation of the complex merging task into manageable steps reduces processing complexity while ensuring model completeness.
Data Source
AI summary
Technologies for merging three-dimensional models of dental impressions include a computing device that generates multiple three-dimensional models that are each indicative of a dental impression of a user's dental arch. The models may be generated by scanning the dental impressions. The computing device determines whether a model is indicative of the complete anatomy of the user's arch and, if not, merges multiple models with a merge strategy to generate a merged model. The models may be merged by aligning geometry of the models, selecting geometry from one of the models using the merge strategy, and generating the merged model that includes the selected geometry. The merge strategy may include selecting from the model associated with the dental impression that includes the most detail of the user's anatomy or selecting from the model with the greatest depth.