1. Automated frame selection process for analyzing high resolution microendoscope images
- Author
-
Rebecca Richards-Kortum, Ann M. Gillenwater, Nadarajah Vigneswaran, Richard A. Schwarz, Ayumu Ishijima, and Sharon Mondrik
- Subjects
Artifact (error) ,Computer science ,business.industry ,Frame (networking) ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Process (computing) ,High resolution ,Video sequence ,Fully automated ,Computer vision ,Artificial intelligence ,business ,Selection algorithm ,Selection (genetic algorithm) - Abstract
We developed an automated frame selection algorithm for high resolution microendoscope images. The algorithm rapidly selects a representative frame with minimal motion artifact from a short video sequence, enabling fully automated image analysis at the point-of-care. The performance of the algorithm was evaluated by comparing automatically selected frames to manually selected frames using quantitative image parameters. The implementation of fully automated high-resolution microendoscopy at the point-of-care has the potential to reduce the number of biopsies needed for accurate diagnosis of precancer and cancer in low-resource settings, where there may be limited infrastructure and personnel for standard histologic analysis.
- Published
- 2014
- Full Text
- View/download PDF