An Application of Topological Median on Detection and Clustering of Microcalcification in Digital Mammograms

Existence of microcalcification clusters on mammograms is one of the earliest signs of breast cancers. In this study, a method that is based on topological median filters is proposed for the automated detection of microcalcifications. The proposed algorithm consists of two steps. First, probable microcalcification pixels in the mammograms are segmented out by using topological top-hat transform. Then, individual microcalcifications are clustered by using a subtractive clustering algorithm. The method has been applied to nijmegen database of 34 mammograms with a total of 72 microcalcification clusters. The results show that the proposed algorithm has a success rate of 93%.