Convolutional Neural Networks for Breast Cancer Histopathological Image Classification
Sandeep Angara, Melvin Robinson, Pablo Guillén-Rondon · 2018
Breast cancer is the second leading cause of cancer death among women. Breast cancer is not a single disease, but rather is comprised of many different biological entities with distinct pathological features and clinical implications. Pathologists face a substantial increase in workload and complexity of digital pathology in cancer diagnosis due to the advent of personalized medicine, and diagnostic protocols have to focus equally on efficiency and accuracy. Computerized image processing technology has been shown to improve efficiency, accuracy and consistency in histopathology evaluations, and can provide decision support to ensure diagnostic consistency. We show that convolutional neural networks (CNN) can be an effective tool in classifying breast cancer histopathological images and evaluate its performance as a binary classifier in the field of breast cancer diagnosis using whole slide imaging.