Intraoral Scanner Image Selection and Illumination Correction
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Solution Overview
Problem
Modern intraoral scanners generate thousands of images during dental scanning, leading to storage, processing, and bandwidth issues due to redundant data, and often capture images under non-uniform lighting conditions, which affects image quality.
Innovation Solution
A method for selecting a subset of images based on predefined criteria, using a computing device connected to the intraoral scanner, which discards unnecessary images and performs further processing only on the selected subset, while also addressing non-uniform illumination through a uniformity correction model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all images captured by the intraoral scanner are stored and processed, then complete dental site information is preserved, but storage space, memory, and compute resources are excessively consumed
Solution Approach 1:
The system extracts and retains only the essential images that contain critical dental site information while discarding redundant images. This is achieved through automated selection criteria that identify images containing unique anatomical features or diagnostic value, thereby preserving necessary information while eliminating storage waste.
Solution Approach 2:
The system discards redundant images that do not contribute unique information to the dental site representation. By implementing intelligent selection algorithms, the system recovers and retains only the most valuable images for storage and processing, achieving efficient resource utilization without information loss.
2Reliability
If all captured images are processed, then comprehensive dental analysis is achieved, but processing time and computational resources increase significantly
Solution Approach 1:
The system extracts and processes only the essential subset of images that contain critical diagnostic information. By applying selection criteria that identify images with unique anatomical features or clinical significance, the system achieves reliable dental analysis while minimizing processing time and computational resource consumption.
3Loss of information
If all images are transmitted, then complete dental data is available remotely, but network bandwidth consumption increases
Solution Approach 1:
The system extracts and transmits only the essential images that contain critical dental information. By implementing automated selection criteria that identify images with diagnostic value or unique anatomical features, the system ensures remote availability of necessary dental data while minimizing network bandwidth consumption.
4Device complexity
If images captured under non-uniform lighting are used directly, then no additional processing is needed, but image quality and diagnostic accuracy deteriorate
Solution Approach 1:
The system performs preliminary illumination uniformity correction on images before they are used for diagnostic purposes. By applying correction algorithms that compensate for non-uniform lighting conditions, the system improves image quality and diagnostic accuracy while maintaining relatively simple overall processing complexity.
Data Source
AI summary
Embodiments relate to techniques for selecting images from a plurality of images generated by an intraoral scanner. A method includes receiving a plurality of images of a dental site generated by an intraoral scanner, identifying a subset of images from the plurality of images that satisfy one or more selection criteria, selecting the subset of images that satisfy the one or more selection criteria, and discarding or ignoring a remainder of images of the plurality of images that are not included in the subset of images.