Feature Extraction and Unsupervised Clustering of Histopathological Images of Pancreatic Cancer Using Information Maximization
Mahfujul Islam Rumman, Naoaki Ono, Kenoki Ohuchida, Md. Altaf‐Ul‐Amin, Ming Huang, Shigehiko Kanaya · 2022 IEEE 11th Global Conference on Consumer Electronics (GCCE) · 2022
In recent years, computer-aided diagnosis based on deep learning concepts has become an attractive research topic in medical imaging. Most of these works utilized supervised learning methods that required prior pathological knowledge. However, it is necessary to extract potential features in images, based on unsupervised learning in order to obtain new pathological findings. For this reason, we implemented unsupervised cluster analysis based on maximization of mutual information to classify pathological images of pancreatic cancer into discrete categories.