Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis.
Résumé
Colorectal cancer is the second cause of cancer death in
United States: precursor lesions (polyps) detection is key for patient
survival. Though colonoscopy is the gold standard screening tool, some
polyps are still missed. Several computational systems have been pro-
posed but none of them are used in the clinical room mainly due to com-
putational constraints. Besides, most of them are built over still frame
databases, decreasing their performance on video analysis due to the lack
of output stability and not coping with associated variability on image
quality and polyp appearance. We propose a strategy to adapt these
methods to video analysis by adding a spatio-temporal stability mod-
ule and studying a combination of features to capture polyp appearance
variability. We validate our strategy, incorporated on a real-time detec-
tion method, on a public video database. Resulting method detects all
polyps under real time constraints, increasing its performance due to our
adaptation strategy.