Title :
A fuzzy logic C-means clustering algorithm to enhance microcalcifications clusters in digital mammograms
Author :
Vivona, L. ; Cascio, D. ; Magro, R. ; Fauci, F. ; Raso, G.
Author_Institution :
Dept. of Phys., Univ. of Palermo, Palermo, Italy
Abstract :
The detection of microcalcifications is a hard task, since they are quite small and often poorly contrasted against the background of images. The Computer Aided Detection (CAD) systems could be very useful for breast cancer control. In this paper, we report a method to enhance microcalcifications cluster in digital mammograms. A Fuzzy Logic clustering algorithm with a set of features is used for clustering microcalcifications. The method described was tested on simulated clusters of microcalcifications, so that the location of the cluster within the breast and the exact number of microcalcifications is known.
Keywords :
biological organs; cancer; fuzzy logic; image enhancement; mammography; medical image processing; pattern clustering; breast cancer control; computer aided detection; digital mammograms; fuzzy logic C-means clustering algorithm; microcalcifications cluster enhancement;
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2011 IEEE
Conference_Location :
Valencia
Print_ISBN :
978-1-4673-0118-3
DOI :
10.1109/NSSMIC.2011.6152551