Towards automatic polyp detection with a polyp appearance model

This work aims at automatic polyp detection by using a model of polyp appearance in the context of the analysis of colonoscopy videos. Our method consists of three stages: region segmentation, region description and region classification. The performance of our region segmentation method guarantees that if a polyp is present in the image, it will be exclusively and totally contained in a single region. The output of the algorithm also defines which regions can be considered as non-informative. We define as our region descriptor the novel Sector Accumulation-Depth of Valleys Accumulation (SA-DOVA), which provides a necessary but not sufficient condition for the polyp presence. Finally, we classify our segmented regions according to the maximal values of the SA-DOVA descriptor. Our preliminary classification results are promising, especially when classifying those parts of the image that do not contain a polyp inside.

► Definition of a general model of polyp appearance.
► Extension on the definition of the depth of valleys image.
► Development of an accurate region segmentation scheme.
► Integrate information from depth of valleys image in the novel SADOVA descriptor.
► Promising results on region-based and frame-based classification.