Convolution Neural Networks for diagnosing colon and lung cancer histopathological images

Image classification is a challenging task for the visual content, particularly microscopic images for example histopathological images due to high convolution of inter-intraclass dependencies. The underlying structures are complex and interwoven due to similar structural morphological textures. Figure 1 presents some of the complex textures present in histopathology of images. Deep learning is prevalent due to its ability to learn features directly from the input, providing us a window to avoid arduous feature extraction processes Bengio et al.. One of the key features of deep learning is to discover abstract level features and then deep dive for extracting structural semantics in the feature map.