A shape cognitron neural network for breast cancer detection

A Neocognition-like neural network built with universal feature planes, called Shape Cognitron (S-Cognitron) is introduced to classify clustered microcalcifications (MCC's). The S-Cognitron is composed of two modules. The first module consists of (a) a shape orientation layer, to convert first-order shape orientations into numeric values, and (b) a complex layer to extract second-order shape features. Followed is a 3-D figure layer to extract the shape curvatures. It is then followed by a second module made up of a feature formation layer and a probabilistic neural network (PNN)-based classification layer, to construct "potential" high-order shape features and perform the classification. The experimental results show the promising of the system.