A unified framework for automated colon segmentation

Abstract

This paper proposes a complete framework for 3D colon segmentation, including detection of its outer walls. Outer wall detection is a challenging problem due to its poor contrast with other structures appearing in the abdominal scans, especially small bowels and other fatty structures. Missing outer walls could severely affect detection of polyps; indicators of colon cancer. A completely automated framework was developed based on level sets as an initial phase of segmentation to extract the lumen. This phase is followed by discarding non-colonic structures. Outer walls of the colon are then detected, and finally the 3d convex active contour model is used to combine the results of both lumen and outer walls. The technique was tested on 30 colon computed tomography (CT) scans and proved effective in both outer walls and polyp detection. The accuracy of the proposed framework is up to 98.94%.