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This paper proposes a new segmentation approach by considering the non extensive property of mammograms. The novel thresholding technique is performed by Tsallis entropy characterized by one more parameter q, which depends on the nonextensiveness of mammogram. Mammograms are typical examples of image with fractal-type structures (nonextensiveness). The proposed approach has been tested on various...
This paper presents a new approach to enhance the contrast of microcalcifications in mammograms using a fuzzy algorithm based on Tsallis entropy. In phase I image is fuzzified using S membership function. In Phase II using the non-uniformity factor calculated from local information the contrast of Microcalcifications were enhanced while suppressing the background heavily. This is the first time in...
In the literature on subspace clustering, traditional clustering techniques have been extended for computing meaningful and interesting clusters in the appropriate subspaces of the high dimensional data. We present a novel algorithm to capture unobserved object relationships embedded in fuzzy subspaces. In order to model the uncertainties of fuzzy data, we propose a modification of fuzzy c-means algorithm...
Breast cancer is one of the leading causes of women death in the world. Since the causes are unknown, breast cancer cannot be prevented. Micro calcifications are the earliest signs of breast cancer and their detection is one of the most important research areas now. A novel approach for image segmentation of denser mammography images is introduced, for more accurate detection of microcalcifications...
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