Semi-supervised learning for medical image classification using imbalanced training data

Tri Huynh, Aiden Nibali, Zhen He

Medical image classification is often challenging for two reasons: a lack of labelled examples due to expensive and time-consuming annotation protocols, and imbalanced class labels…