Symposium of the Microscopy Imaging Center if the University of Bern
Machine learning in imaging
PROGRAM
09:30 Welcome coffee and registration
10:30 Welcome: Hans-Uwe Simon, Dean of the Medical Faculty David Spreng, Dean of the Vetsuisse Faculty Britta Engelhardt, President of the MIC
Session 1. Chairs: Inti Zlobec, Raphael Sznitman
10:35 Machine learning at the University of Bern An overview presented by the scientific committee
10:45 Jean-Philippe Thiran (EPFL, Lausanne, CH) Keynote Inverse problems in ultrasound imaging: Efficient modeling, sparse regularization and neural networks
11:30 Anna Kreshuk (EMBL, Heidelberg, DE) Image segmentation at scale
12:00 Michael Schell (Cenibra GmbH, DE) Teacher or student? How to teach AI to pick correct confocal microscopy images
12:15 Lunch and industry exhibition
Session 2. Chairs: Guillaume Witz, Mauricio Reyes
13:45 Inti Zlobec (University of Bern, CH) Digital pathology in translational research
14:15 Andrew Janowczyk (Lausanne Univ. Hospital, CH) Computational pathology: Towards precision medicine
14:45 Gergely Kovach (Sysmex Suisse AG, CH) High resolution whole tissue imaging for 3D analysis
15:00 Coffee and industry exhibition
Session 3. Chairs: Mauricio Reyes, Raphael Sznitman
15:30 David Pointu (GE Healthcare AG, CH) Advantages of IN Carta Phenoglyphs™ HCA machine learning module
15:45 Ender Konukoglu (ETH Zürich, CH) On Bayesian models with networks for reconstruction and detection
16:15 Christine Decaestecker (University of Brussel, BE) Segmentation of histopathological images: How to reduce the supervision needs for deep learning
16:45 Conclusions and farewell
REGISTRATION
http://www.mic.unibe.ch/ symposium_registration.php