Abstract

Breast cancer is one of the preeminent impetus of deaths in India. Current Indian data show that one in 22 women develop breast cancer. Out of the two who develop it, one of them would have a higher chance of not surviving it. Breast cancer in India is different from that in the West. Here, it is affecting younger women and more than half of them present themselves in advanced stages. By 2030, breast cancer will cause maximum deaths among women in India than any other cancer. Effective and efficient early detection and classification tools are required to reduce the mortality rates due to breast cancer. Machine learning provides ways to detect and classify these early by finding some recurring patterns in the mammograms. In this research work, fuzzy c-means (FCM) clustering is presented as an approach for performing segmentation and SVM as an approach for performing classification. Image aggrandizing approaches, segmentation, feature adumbration and classification approaches have been delved into and administered on mammographic images obtained from the mini-MIAS repository(Abstract)