Orientational coherence metrics: classification of colonic cancer images based on human form perception

A number of quantitative techniques for the analysis of histopathological images used in the diagnosis of colonic cancer have been researched in the literature. While these methods have led to significant advances in the development of automated techniques, manual processing by a clinical expert remains the standard against which results are assessed. Here we explicitly attempt to build our understanding of human form perception, implemented at a neural level, into metrics that give us a measure of the extent to which the structure in an image displays a coherent orientational specificity. We describe the derivation of these metrics and consider their application to typical images of normal colon, dysplastic specimens, and moderately and poorly differentiated adenocarcinoma of colon. Preliminary results evaluating the effectiveness of the total activation ratio and the orthogonal activation ratio suggest that they are capable of separating images of normal colon tissue from those of moderately and poorly differentiated adenocarcinoma of colon.