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Indian Journal of Public Health Research & Development
Year : 2018, Volume : 9, Issue : 12
First page : ( 327) Last page : ( 333)
Print ISSN : 0976-0245. Online ISSN : 0976-5506.
Article DOI : 10.5958/0976-5506.2018.01856.9

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.

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Keywords

Breast cancer, diagnosis, digital mammogram, pre-processing, Butterworth bandpass filter, segmentation, fusion, FCM, K-means, Cluster, morphology.

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