A neural network based technique to locate and classify microcalcifications in digital mammograms

This paper proposes a technique that extracts suspicious areas containing microcalcifications in digital mammograms and classifies them into two categories whether they contain benign or malignant clusters. The centroids and radiuses provided by expert radiologist are being used to locate and extract suspicious areas. Neural network's generalisation abilities are used to classify them into benign or malignant. The technique has been implemented in C++ on the SP2 supercomputer. The database from the Department of Radiology at the University of Nijmegen and Lawrence Livermore National Laboratory has been used for the experiments. The preliminary results are very promising. Some of them are presented in this paper.