3D Interproximal Modeling with Non-Structured Light Imaging
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Solution Overview
Problem
Intraoral scanners face challenges in accurately scanning and modeling interproximal regions between teeth, resulting in lower resolution and incomplete 3D models due to the limitations of structured light imaging.
Innovation Solution
Utilizing non-structured light illumination, such as white light or near-IR imaging, to enhance 3D models by aligning camera positions with structured light images, correcting surface holes and gaps through alignment transforms and radial basis functions, and integrating these methods into intraoral scanners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If structured light imaging is used for rapid 3D modeling, then scanning speed is improved, but measurement precision deteriorates in interproximal regions
Solution Approach 1:
The patent combines structured light imaging with non-structured light imaging to create a hybrid system. The structured light provides rapid scanning capability while the non-structured light supplements detail in interproximal regions, merging the advantages of both methods to resolve the contradiction between speed and precision.
Solution Approach 2:
The non-structured light images serve as an intermediary to fill gaps in the structured light point cloud. By using the non-structured light data as a mediator, the system recovers missing surface details in interproximal regions without sacrificing the rapid scanning capability of structured light.
2Productivity
If structured light imaging is used, then scanning efficiency is improved, but manufacturing precision deteriorates due to surface holes in 3D models
Solution Approach 1:
The system performs preliminary action by capturing non-structured light images during the scanning process to identify regions with surface holes. This preliminary data collection enables subsequent recovery and correction of missing surface information, ensuring manufacturing precision without reducing scanning efficiency.
Solution Approach 2:
The system uses feedback by analyzing the structured light point cloud to identify surface holes, then retrieving corresponding non-structured light images to correct these deficiencies. This feedback loop ensures that the final 3D model achieves manufacturing precision while maintaining the efficiency of structured light scanning.
3Area of stationary object
If multiple cameras are used simultaneously, then imaging coverage is improved, but measurement precision deteriorates in recessed regions
Solution Approach 1:
The patent adds another dimension by incorporating non-structured light imaging data alongside the multi-camera structured light system. This additional dimensional information from non-structured light helps resolve ambiguities in recessed regions where multiple structured light cameras may have limited viewing angles, thereby improving measurement precision without reducing coverage.
Data Source
AI summary
Methods and apparatuses that may improve the accuracy of three-dimensional models from interproximal regions of intraoral scan data using non-structured light illumination images (e.g., white light, near-infrared light, fluorescent light, etc.). These methods and apparatuses may correct irregularities (e.g., holes, gaps, etc.) in the 3D digital model of the subject's teeth and may enhance treatment planning and the accuracy and effectiveness of dental appliances.