Breast Cancer Image Classification using Transfer Learning and Convolutional Neural Network

Abstract

Breast cancer is the world's second most frequent cancer among women. In 2012, new cancer cases made up 12% of all new cases, with female malignancies accounting for 25% of all cancer diagnoses. These cells can be detected by an x-ray or a bump on the body. To be cancerous, a tumour must have cells that have invaded or spread to other areas of the body. Develop an algorithm that can determine whether or not a patient has breast cancer based on biopsy photos. To protect human life, the algorithm must be extremely precise. In this study, a database of breast cancer photos is used for analysis, and the categorization is done using a deep learning approach. The deep learning model is applied by implementing a Convolutional Neural Network with transfer learning. The accuracy has achieved more than 96%, which is better than other states of the art algorithms.