MIC Symposium 2019


Machine Learning in Imaging

Confirmed Speakers:

Christine Decaestecker, University of Brussel (BE)
Segmentation of histopathological images: How to reduce the supervision needs for deep learning
Andrew Janowczyk, Lausanne University Hospital (CH)
Computational pathology: Towards precision medicine
Ender Konukoglu, ETHZ (CH)
On Bayesian models with networks for reconstruction and detection
Gergely Kovach, 3DHistech on behalf of Sysmex Suisse AG (CH)
High resolution whole tissue imaging for 3D analysis
Anna Kreshuk, EMBL (DE)
Image segmentation at scale
David Pointu,GE Healthcare Europe GmbH (CH)
Advantages of IN Carta Phenoglyphs™ HCA machine learning module
Michael Schell, Cenibra GmbH (DE)
Teacher or student? How to teach AI to pick correct confocal microscopy images
Jean-Philippe Thiran, EPFL (CH)
Inverse problems in ultrasound imaging: Efficient modeling, sparse regularization and neural networks
Inti Zlobec, University of Bern (CH)
Digital pathology in translational research

Program (238 KB)

Friday, 29 November 2019

9:30 - 17:00

UniS, University of Bern
Lecture hall A003
Schanzeneckstrasse 1
3012 Bern


Contact MIC Microscopy Imaging Center
Uni Bern
Yvonne Omara
+41 31 631 44 97

Contact Swissphotonics NTN
Dr. Christoph S. Harder
President Swissphotonics NTN
+41 79 219 90 51

31 October 2019, Beni Muller + Iris Bollinger

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