­ Computer-aided diagnosis (CAD) systems are invaluable in helping physicians better diagnose and treat diseases by using Artificial Intelligence (AI) to interpret medical images. Motivated by the early success of CAD systems, particularly those developed using deep learning algorithms, there is an intense interest in adopting them for applications...

Image analysis techniques are invaluable in helping physicians better diagnose and treat diseases and expand the utility of medical imaging. Self-supervised learning, in particular, is one of the most practical paradigms in deep learning for medical image analysis. Self-supervised learning methods are characterized by training deep models directly from...

Image analysis techniques are invaluable in helping physicians better diagnose and treat diseases and expand the utility of medical imaging. Self-supervised learning, in particular, is one of the most practical paradigms in deep learning for medical image analysis. Self-supervised learning methods are characterized by training deep models directly from...

Image analysis techniques are invaluable in helping physicians better diagnose and treat diseases and expand the utility of medical imaging. Two common image analysis techniques, convolutional neural networks (CNN) and bags of visual words (BoVW) are often thought of as competing methods, however, they could have complementary strengths. CNNs are great...