Breast Cancer Classification using Capsule Network with Preprocessed Histology Images

Breast cancer is one of the most dangerous forms of cancer exists among women. The breast cancer is diagnosed using histology images. The purpose of this paper is to classify different types of breast cancer using histology images. The classification of histology images can be effectively done by image processing techniques. Among different image processing algorithms, deep learning gives the best performance for image classification applications. There are different convolutional neural network(CNN) architectures used for classification purpose such as AlexNet, Inception-Net, ResNet etc. Since conventional convolutional neural networks have lot of drawbacks, the architecture used for the current study is capsule networks, which captures the spatial and orientational information. The proposed work shows that the accuracy of Capsule Network model is improved due to the pre-processing of the histology images.