A Note on Feature Selection for Polyp Detection in CT Colonography

In this paper we describe a computer aided detection (CAD) algorithm for robust detection of polyps in computed tomography (CT) colonography. The devised algorithm identifies suspicious polyp candidate surfaces using the surface normal intersection, Hough transform, 3D histogram analysis, region growing and a convexity test. From these detected surfaces we extract statistical and morphological features in order to evaluate if the surface in question is a polyp or fold. In order to devise the optimal classification scheme the performance of two different classifiers are evaluated when the algorithm is applied to synthetic and real patient data. The experimental results indicate that the overall polyp detection performance shows sensitivity higher than 92% for polyps larger than 5mm with an average of 4.7 to 6.0 false positives per dataset.