Tutorial on Deep Learning for Medical Imaging

From A(dversarials) to Z(-space)

Sunday, September 16th - MICCAI 2018 - Granada Conference Center, Spain


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.


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)


Ben Glocker, Imperial College London

Tom Vercauteren, King's College London

Jorge Cardoso, King's College London

Shadi Albarqouni, TU Munich

Anirban Mukhopadhyay, TU Darmstadt

Martin Rajchl, Imperial College London

Konstantinos Kamnitsas, Imperial College London

Ira Ktena, Imperial College London

Matt Lee, HeartFlow/Imperial College London

Nick Pawlowski, Imperial College London

Bram van Ginneken, Radboud UMC

Geert Litjens, Radboud UMC

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