  Computer tomographic colonography, combined with computer-aided detection, is
a promising emerging technique for colonic polyp analysis. We present a
complete pipeline for polyp detection, starting with a simple colon
segmentation technique that enhances polyps, followed by an adaptive-scale
candidate polyp delineation and classification based on new texture and
geometric features that consider both the information in the candidate polyp
location and its immediate surrounding area. The proposed system is tested with
ground truth data, including flat and small polyps which are hard to detect
even with optical colonoscopy. For polyps larger than 6mm in size we achieve
100% sensitivity with just 0.9 false positives per case, and for polyps larger
than 3mm in size we achieve 93% sensitivity with 2.8 false positives per case.
