In this chapter, we propose and analyze a system that can automatically detect, localize and
classify polyps from colonoscopy videos. The detection of frames with polyps is formulated
as a few-shot anomaly classification problem, where the training set is highly imbalanced
with the large majority of frames consisting of normal images and a small minority
comprising frames with polyps. Colonoscopy videos may contain blurry images and frames
displaying feces and water jet sprays to clean the colon—such frames can mistakenly be …