An Automatic Algorithm for Tracking Small Intestine in CT Enterography

Abstract

In this paper we present an automatic algorithm to segment and track small intestine from CT enterography. The algorithm can handle noisy thin-slice data and is adaptable to the greatly varying spatial structure of the organ. Our approach automatically segments all well-distended parts and performs tracking of the intestinal path. Pre-filtered data are segmented with watershed segmentation and then a kNN-based probability function enhances whole parts of the lumen. Post-process based on a robust form of region growing is then used for path tracking.