DenseMammoNet: An Approach for Breast Cancer Classification in Mammograms

In women all around the world, cancer of the breast is a condition that is both prevalent and on the rise. Breast cancer can be formed due to the lumps in the mammary region in females. Early detection of breast cancer masses (BCM) can save the lives of many women. In this paper, we have proposed an automated method that it is feasible to spot cancer of the breast in its infancy from mammographic images. To validate the authenticity of the proposed work, we have experimented with the publicly available dataset, Mammography Image Analysis Society (MIAS), and achieved an accuracy of 99.4%.