Journal Paper

Paper Title - Implementation And Analysis Of K- Means And Fuzzy C Means Clustering Techniques


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).


Author - Snehali D. Sable, Alpana Deshmukh

Citation - Snehali D. Sable   ,   Alpana Deshmukh   ,   Snehali D. Sable, Alpana Deshmukh " Implementation And Analysis Of K- Means And Fuzzy C Means Clustering Techniques " , International Journal of Industrial Electronics and Electrical Engineering , Volume-3, Issue-6  ( Jun, 2015 )

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| Published on 2015-06-15