ATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAAGTAC
TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
ATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAAGTAC
TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
Deep learning for digital pathology image analysis (lectures only)
08 March 2019
For-profit: 0 CHF
No future instance of this course is planned yet
This course is now over-subscribed with a waiting list.
Overview
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.
At the bottom of this page there is a link to proceed with registration for the morning lectures only.
To register for the practicals, please follow this link.
This event is co-hosted with the Swiss Digital Pathology Consortium (SDiPath).
Audience
This course is targeted to clinicians and researchers who are interested in discovering deep learning methods for the analysis of histopathological image data.
Learning objectives
The lectures will introduce participants to the relevant topics and state-of-the-art methods for deep learning in digital pathology image analysis.
Application
Attendance to the lectures are free-of-charge, however registration is mandatory.
Venue and Time
University of Basel, Biozentrum, Klingelbergstrasse 70, Hörsaal 103.
- 9-9h10 - Welcome and introductions
- 9h10-10h10 - Raúl Catena, multi-layer tissue analysis
- 10h10-10h30 - Catered coffee break
- 10h30-11h15 - Tobias Sing and Pierre Moulin, "Pathology 2.0" and decision support in the clinic
- 11h15-12h00 - Andrew Janowcyzk, overview of deep learning and applications in research
Precise information will be provided to the participants in due time.
Additional information
Coordination: Geoffrey Fucile
You are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops, as well as all important deadlines using the form here.
For more information, please contact training@sib.swiss.