A Study on Nuclei Shape Features at the Classification of Glioma Disease Stage Using CNN
Daisuke Saito, Hiroharu Kawanaka, V. B. Surya Prasath, Bruce J. Aronow · IEEJ Transactions on Electronics Information and Systems · 2020
Recently, a lot of studies using Deep Learning techniques have been reported in the field of Digital Histopathology. For instance, there are ideas using deep Convolutional Neural Network (CNN) for disease stage classification and segmentation. These methods are expected to reduce pathologists’ work and realize quantitative analysis. However, at the disease stage classification using CNN, even if we can obtain high classification accuracy, it is difficult for us to understand how CNN decides the disease stage. In this paper, we discussed the relationship between features of cell nuclei shape and the disease stage classification using CNN.