Enhancement and identification of microcalcifications in mammogram images using wavelets

In this paper, we describe an algorithm for enhancement and detection of microcalcifications in digital mammograms. The microcalcifications are first enhanced by a undecimated wavelet transform and segmented by a classification based method. After spatial features are extracted from the segmented images, a neural network and a Bayes classifier are used to identify clustered microcalcifications. We have tested this algorithm on 40 regions-of-interest images extracted from the database provided by the University Hospital of Nijmegen.