Deep Learning and Medical Applications

January 27 - 31, 2020

Overview

P0_wl (002)Rapid advances in deep learning techniques are starting to revolutionize medical imaging. Radiology, disease detection, and tissue imaging are all expected to be facilitated by automated image analysis programs in the near future. Many new interdisciplinary research questions arise; finding solutions with practical significance requires input from mathematicians, bio-physicists, and computational engineers. This workshop aims to bring together researchers from different backgrounds to explore this new frontier of science. 

The workshop will include a poster session; an announcement for posters will be sent to registered participants in advance of the workshop.

Program Flyer PDF

Organizing Committee

Ben Glocker (Imperial College, Department of Computing)
Gitta Kutyniok (Technische Universität Berlin, Program in Applied and Computational Mathematics)
Marc Niethammer (University of North Carolina, Computer Science)
Stanley Osher (University of California, Los Angeles (UCLA), Mathematics)
Daniel Rueckert (Imperial College)
Jin Keun Seo (Yonsei University, Computational Science & Engineering)
Michael Unser (École Polytechnique Fédérale de Lausanne (EPFL), Biomedical Imaging Group)
Jong Chul Ye (Korea Advanced Institute of Science and Technology (KAIST), Bio and Brain Engineering/Mathematics)