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Detection of suspicious lesions in mammogram using fuzzy C-means algorithm

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dc.contributor.author Bhatt, Upendra Mohan
dc.date.accessioned 2025-01-21T05:00:54Z
dc.date.available 2025-01-21T05:00:54Z
dc.date.issued 2016-11
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/7732269
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16841
dc.description.abstract Breast cancer is one of the most incurable diseases, which leads to the death of women globally every year. For initial detection of a tumor in the breast, the most useful technique called `Mammography' is used, which is an X-ray inspection of the breast, which can be used to detect the breast tumor which may lead to breast cancer. Using Mammography, a small lump that may lead to breast cancer can be detected at the initial stage. Sometimes it is not possible to recognize very small tumors because of noisy, blurred, and fuzzy images. Therefore, they need to be enhanced to increase the contrast for better visual perception and reduce the noise from it for better diagnosis. In this work, FCM algorithm is used to detect the suspicious lesions in a mammogram. To achieve the objective of this work, MIAS (Mammographic Image Analysis Society) and INbreast databases are used, which contain 322 and 412 images of the breast (both left and right breast) respectively. In these databases, every image is examined by the expert radiologists. The effectiveness of the algorithm is measured in terms of MSE and PSNR. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEE en_US
dc.subject Mammograms en_US
dc.subject Breast cancer en_US
dc.subject Wavelet Denoising Filter en_US
dc.subject Fuzzy C-Means Algorithm en_US
dc.subject Morphological Operation en_US
dc.title Detection of suspicious lesions in mammogram using fuzzy C-means algorithm en_US
dc.type Article en_US


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