Computer-aided diagnosis scheme applying GRNN neural network

In this paper, we present a Computer Aided Diagnosis (CAD) system that has been developed for Microcalcifications (MCs) Identification in Digitized Mammography. It combines Multiscale Image Processing and Artificial Neural Networks (ANNs). In mammography diagnosis, Generalized Regression Neural Network (GRNN) is a succesful novelty. A number of relevant features are extracted from Regions of Interest (ROI) to reduce the classifier complexity. We compared our results with a Feed Forward Neural Networks (FFNNs). Our performance results successfully compete with classical FFNNs and present a much faster training phase, overcoming also minima problem.