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Fuzzy c-means Segmentation on Enhanced Mammograms Using CLAHE and Fourth Order Complex Diffusion

Publication Type : Conference Paper

Publisher : 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), IEEE

Source : 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), IEEE, Erode, India, India (2020)

Url : https://ieeexplore.ieee.org/document/9076402

Campus : Amritapuri

School : Department of Computer Science and Engineering, School of Engineering

Center : Computer Vision and Robotics

Department : Computer Science

Year : 2020

Abstract : Cancer statistics all around the globe are rising day by day, out of which breast cancer is the dominating one in women. Mammography is used to detect the presence of cancerous cells and computer-aided detection technologies are used to get more accurate results. There are different image processing techniques which are applied for cancer detection in mammograms. In this work, a combined methodology is used for enhancing the contrast of the mammogram which includes contrast limited histogram equalization (CLAHE), morphological gradient and fourth order nonlinear complex diffusion based unsharpening. The enhanced mammogram is then segmented using fuzzy c-means. An analysis is done on each of the following cases with Fuzzy-c means segmentation: CLAHE enhanced, morphologicall gradient enhanced, fourth order nonlinear complex diffusion enhanced and combined enhanced image using the above methods.

Cite this Research Publication : M. Mohan, L. T., P., and Lekha S. Nair, “Fuzzy c-means Segmentation on Enhanced Mammograms Using CLAHE and Fourth Order Complex Diffusion”, in 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, India, 2020.

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