A complete system for candidate polyps detection in virtual colonoscopy

We present a computer-aided detection pipeline for polyp detection in Computer tomographic colonography. The first stage of the pipeline consists of a simple colon segmentation technique that enhances polyps, which is followed by an adaptive-scale candidate polyp delineation, in order to capture the appropriate polyp size. In the last step, candidates are classified based on new texture and geometric features that consider both the information in the candidate polyp location and its immediate surrounding area. The system is tested with ground truth data, including flat and small polyps which are hard to detect even with optical colonoscopy. We achieve 100% sensitivity for polyps larger than 6mm in size with just 0.9 false positives per case, and 93% sensitivity with 2.8 false positives per case for polyps larger than 3mm in size.

Duke Scholars

Author Guillermo Sapiro Electrical and Computer Engineering