Automated frame selection process for analyzing high resolution microendoscope images

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.