3D Scanning Proficiency Evaluation System
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Solution Overview
Problem
In the field of 3D scanning and modeling, particularly in dental industries, there is a need to evaluate user proficiency effectively, as handheld scanners require training and lack practical evaluation methods for obtaining precise 3D data of oral cavities.
Innovation Solution
A data processing method that involves loading sample data of a training model into a user interface, matching scan data with sample data, and evaluating the scan data to improve user proficiency through qualitative and quantitative assessments, with adjustable difficulty levels and marker units for guided training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a handheld type scanner is used to obtain 3D data, then portability and flexibility are improved, but scanning precision deteriorates because user proficiency directly affects data quality
Solution Approach 1:
The system provides real-time feedback by comparing user-acquired scan data with reference data from expert scans. The comparison results, including similarity metrics and visual overlays, guide users to improve their scanning technique iteratively, thereby enhancing scanning precision while maintaining handheld portability
Solution Approach 2:
Reference scan data from experts is pre-acquired and stored in the system before actual use. This preliminary preparation of high-quality reference data enables immediate comparison and guidance during user scanning operations, eliminating the need for users to independently achieve expert-level precision
2Productivity
If users scan actual patient oral cavities to improve proficiency, then practical experience is gained, but the ability to objectively evaluate scanning proficiency deteriorates
Solution Approach 1:
Instead of relying on actual patient scans for evaluation, the system uses copied reference data from expert scans of training models. These reference copies provide standardized benchmarks that enable objective proficiency evaluation without requiring real patient involvement in the training process
Solution Approach 2:
Training models serve as intermediaries between users and actual patient scans. Users practice on training models with objective evaluation, then apply skills to real patients. The training model acts as a mediator that provides measurable feedback without the complexity and variability of actual patient oral cavities
3Speed
If scan data is evaluated without reference to sample data, then scanning speed is improved, but evaluation accuracy deteriorates
Solution Approach 1:
Reference scan data is pre-acquired and pre-processed before actual evaluation operations. This preliminary preparation enables rapid comparison and accurate evaluation during actual scanning operations, as the reference data is already ready for immediate use
Solution Approach 2:
The system replaces manual expert evaluation with automated computer-based comparison algorithms. The automated system objectively compares scan data with reference data using computational methods, providing both speed and accuracy without requiring manual review of each scan
Data Source
AI summary
A data processing method according to the present invention comprises the step of: loading at least a part of sample data corresponding to a training model into a user interface; matching the sample data with scan data obtained by scanning the training model; and assessing the scan data on the basis of a result of the matching between the scan data and the sample data.