An Efficient Approach for Detection and Classification of Breast Masses in Digital Mammograms

Breast Cancer is a fatal and common disease that affects thousands of women every year Worldwide. Therefore the early detection of the breast cancer plays crucial role in effective treatment and lowers the mortality rate. The breast examination is done with the help of mammograms with correct screening save lives of millions of peoples in the World. The Lobules (that produces milk) and glands that carries milk are the main two areas where breast cancer originates. The detection and classification of the masses in mammograms are still a difficult task and play a vital role to assist radiologists for accurate diagnosis. In this paper, the computer-aided approach that is based on deep learning technique is proposed. Even though most previous studies only deal with either detection or classification of masses, the proposed CAD system can handle detection and classification simultaneously in Single framework.