Polyp detection in CT colonography based on shape characteristics and Kullback-Leibler divergence

As an alternative procedure to the current methods which consider only the mean values of shape features to globally characterize a candidate shape polyps, probability density functions (PDFs) of some feature variables constructed based on Gaussian and mean curvatures are used to characterize the global shape of a candidate lesion. The decision on whether or not this candidate lesion is a polyp is made by comparing the density functions of the considered shape feature variables to reference PDFs of the same variables obtained from a preconstructed polyp/non polyp data base. The Kullback-Leibler divergence is used as a dissimilarity measure to compare these PDFs and make a decision based on closeness. Experiments carried out on real data are used to illustrate the effectiveness of the proposed method in comparison to existing ones.