Early Detection of Breast Cancer using Convolution Neural Network

Breast cancer is extremely predominant in women's today. It first starts once cells within the breast begin to grow out of management. It is found that the detection of tumor at the primary stage can cure it. Manual detection of a cancer cell is a tiresome task and involves human error, and hence computer-aided mechanisms are applied to obtain better results as compared with manual pathological detection systems. In deep learning, this is generally done by extracting features through a Convolutional Neural Network (CNN) and then classifying using a fully connected network. Deep learning is extensively utilized in the medical imaging field, as it does not require prior expertise in a related field. In this paper, the proposed approach has trained a CNN and observed that classification accuracy is better compared to other approaches.