This course is now over-subscribed with a waiting list.
There is a confluence of ongoing revolutions in biomedical image acquisition, computational methods, and technologies for extracting and integrating relevant data in the construction of diagnostic and prognostic models of disease. In particular, deep learning methods are rapidly expanding the range and accuracy of tools for pathologists and researchers.
The aim of this course is two-fold: discuss applications of state-of-the art deep learning methods in digital pathology, and provide practical training in these methods. The course will consist of a half-day of lectures followed by an optional half-day of practicals. The practicals will be based on the PyTorch framework (please see course prerequisites below).
At the bottom of this page there is a link to proceed with registration for the practicals and lectures.
To register for just the lectures, please follow this link.
This event is co-hosted with the Swiss Digital Pathology Consortium (SDiPath).
This course is targeted to clinicians and researchers who are interested in discovering deep learning methods for the analysis of histopathological image data.
Participants will be introduced to the relevant topics and state-of-the-art methods for deep learning in digital pathology image analysis. Those participating in the practical session will be able to:
Participants should be comfortable working with Python and Linux/UNIX, having completed at least introductory courses in these topics (eg Python, UNIX). Participants should also have taken at least introductory training in general statistics.
Participants should bring a laptop with wireless connectivity. Windows users must have software installed for establishing remote ssh connections (eg MobaXterm).
The registration fees for academics are 60 CHF. This includes course content material and coffee breaks. Fees for participants from non-academic institutions are 300 CHF.
Deadline for registration and free-of-charge cancellation is set is set to [08/03/2019]. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to our general conditions.
You will be informed by email of your registration confirmation.
University of Basel, Biozentrum, Klingelbergstrasse 70, Hörsaal 103 (morning lectures) and Seminarraum 104 (afternoon practicals)
Precise information will be provided to the participants in due time.
Coordination: Geoffrey Fucile
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