Scope

This half-day tutorial will cover important aspects of deep learning with a particular focus on medical imaging applications. The tutorial aims to provide an introduction to the basics and fundamental concepts of deep learning, practical advice for the use of deep learning for medical imaging tasks, and gives an overview of latest developments and opportunities for future research. The tutorial is targeted at all levels and for any researcher interested in deep learning. The first lectures are tailored for people new to the field (e.g., first year PhD students), while later lectures cover more advanced topics and latest developments which should be of interest to anyone already working with deep learning methods.

Schedule

09:30 Introduction to deep learning by Geert Litjens and Bram van Ginneken (PDF slides)

10:00 Semantic deep learning: segmentation and regression by Jorge Cardoso and Tom Vercauteren (PDF slides)

10:30 Architectures and optimization by Martin Rajchl, Nick Pawlowski, Matt Lee (PDF slides)

11:00 Coffee break

11:30 Generative adversarial networks by Anirban Mukhopadhyay and Shadi Albarqouni (PDF slides)

12:00 Learning useful information from unlabeled data by Konstantinos Kamnitsas (PDF slides)

12:30 Deep learning on graphs by Ira Ktena (PDF slides)