Segmentation of mammography calcifications using fusion of fuzzy C-means and K-means algorithm Poonguzhali S1,*, Sheshasaayee Ananthi2 1Research Scholar, Bharathiar University, Coimbatore 2Associate Professor & HOD, Research & PG Department of Computer Science& Applications, Quaid-E-Milleth College for Women, Chennai, Tamilnadu, India 3Assistant Professor, Department of Computer Applications, VISTAS, Chennai *Corresponding author: S Poonguzhali, Research Scholar, Bharathiar University, Coimbatore & Assistant Professor, Department of Computer Applications, VISTAS, Chennai, E-mail: poonguzhali.research@gmail.com, ananthi.research@gmail.com
Online published on 9 January, 2019. Abstract Breast cancer is the most life-threatening disease among women. The best way to decrease the mortality is early detection of cancer from digital mammogram. The diagnosis can be successful if the pre-processing and segmentation of the digital mammograms identifies the suspicious area correctly. In this paper, the Butterworth bandpass filter along with fusion of FCM and K-means clustering followed by morphological operations is used for the segmentation of calcification areas from the mammogram images. Top Keywords Breast cancer, diagnosis, digital mammogram, pre-processing, Butterworth bandpass filter, segmentation, fusion, FCM, K-means, Cluster, morphology. Top |