Predicting the histology of colorectal lesions in a probabilistic framework

In this paper, we present a novel approach to predict the histological diagnosis of colorectal lesions from high-magnification colonoscopy images by means of Pit Pattern analysis. Motivated by the shortcomings of discriminant classifier approaches, we present a generative model based strategy which is closely related to content-based image retrieval (CBIR) systems. The ingredients of the approach are the Dual-Tree Complex Wavelet Transform (DTCWT) and the mathematical construct of copulas. Our experimental study on a set of 627 images confirms, that the joint statistical model leads to impressive prediction results compared to previous work.