Detection of microcalcifications in mammograms using nonlinear subband decomposition and outlier labeling

Abstract

Computer-aided diagnosis will be an important feature of the next generation picture archiving and communication systems. In this paper, computer-aided detection of microcalcifications in mammograms using a nonlinear subband decomposition and outlier labeling is examined. The mammogram image is first decomposed into subimages using a nonlinear subband decomposition filter bank. A suitably identified subimage is divided into overlapping square regions in which skewness and kurtosis as measures of the asymmetry and impulsiveness of the distribution are estimated. A region with high positive skewness and kurtosis is marked as a region of interest. Finally, an outlier labeling method is used to find the locations of microcalcifications in these regions. Simulation studies are presented.