Breast Cancer Classification via Convolutional Neural Network
Zhengqi Yang
Union College
Class of 2018
Breast cancer is the most commonly diagnosed cancer for women. It has a higher death rate than any other types of cancers for women in the United States. Detecting tumors intheir early stages through screening examinations is key to reducing breast cancer mortality. Mammography has its limitations and might miss breast cancers in some cases. The high false positives rate of screening ultrasound results in additional imaging/biopsy and anxiety. In this work, we present an effective method to automatically classify breast cancer images using convolutional neural network (CNN). CNN is inspired by connectivity patterns between biological neurons. This is an effective method of image classification in supervised machine learning because the network has ability to learn the parameters that in traditional approaches are hand-engineered.Yang ECE499 Poster -q284u8
