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An Effective Segmentation of Breast Cancer Using Modified U-NET

During late ten years breast cancer is a major issue for women's death recently and also increased the quantity of breast cancer. There is more proof that ladies in 15–54 years of age are passed on by breast cancer. Breast cancer can't be forestalled because its main considerations have not been distinguished. Along these lines, a prior conclusion can expand the chance of progress. This work proposed a modified U-Net deep learning model-based breast cancer segmentation and classification. Information base of MIAS mammography pictures was utilized to arrange ordinary/unusual people and harmless/threatening cancer patients and the outputs of modified U-Net showed higher accuracy than existing.