A graph-theoretical clustering method for detecting clusters of micro-calcifications in mammographic images

In this paper we propose a method based on a graph-theoretical cluster analysis for automatically finding cluster of micro-calcifications in mammographic images. It is applied to the image after a micro-calcification detection phase and is able to cope with the unavoidable false positives that each automatic detection algorithm produces. The proposed approach has been tested on a standard database of 40 mammographic images and revealed to be very effective even when the detection phase gives rise to several false positives.