DOIONLINE

DOIONLINE NO - IJIEEE-IRAJ-DOI-2254

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International Journal of Industrial Electronics and Electrical Engineering (IJIEEE)-IJIEEE
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Volume Issue
Issue
Volume-3, Issue-6  ( Jun, 2015 )
Paper Title
Implementation And Analysis Of K- Means And Fuzzy C Means Clustering Techniques
Author Name
Snehali D. Sable, Alpana Deshmukh
Affilition
Student, M.E. (VLSI and Embedded) GHRIET, Pune India Asst. Prof. Dept of E&TC, GHRIET, Pune India
Pages
173-176
Abstract
Breast cancer is the second most common cause of cancer death in women. Mammography is the best available technique used for earlier detection. Mammography is a special case of CT scan who adopts X-ray method & uses the high resolution film so that it can detect well the tumors in the breast. Mammographic mass detection is an important task for the early diagnosis of breast cancer. However, it is difficult to distinguish masses from normal regions because of their abundant morphological characteristics and ambiguous margins. In the proposed work breast tumor detection and class of image is obtained by using fuzzy K-means & fuzzy C-means clustering technique is proposed. K Means algorithm is Centroid Based and Fuzzy C Means is Representative Object Based. These two algorithms are to be implemented and the performance is to be analyzed based on their clustering result quality. Keywords- Breast Cancer, Mammograms, Clustering Technique, Fuzzy C means (FCM), Fuzzy K Means (FKM).
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