Key information


School accessible from several part of the world. See program section for the timetable depending on your time zone.

Given the success of the first edition of this school held in 2019, and the cancellation of the second edition due to Covid-19 in 2020, the organisers have decided to hold a new Covid-proof edition in 2021 completely virtual. Basis of deep learning will be taught as well as complementary aspects compared with the 2019 edition. This training event will cover the main aspects of the critical and fast developing area of deep learning for medical image analysis. We will provide the fundamental principles of machine learning, review the most advanced deep architectures and give insight into the most challenging subareas of this domain with a special emphasis on the specificities of deep medical image analysis.

The spring school will be organised from April 19 to 24.

We will offer lectures and 4 hands on sessions.

50 attendees will be accepted, following a selection process. Although the target audience is students, post-docs and researchers, it will be opened to any interested parties. No formal pre-requisite for attendance in terms of academic degrees is expected, but basic knowledge or practice abilities in computer science is recommended.

Convivial virtual moments will be organised each day and a round table on hot topics will be held.

More information will be soon available.

Important dates

Pre-registration is closed
12th of February 2021                                 pre-registration closing
5th of March 2021                                         participants selection ending, poster submission opening
12th of April 2021                                       online registration (for selected participants) and payment closing

 The registration is only open to preregistered selected candidates

Scientific organisation committee

Olivier Bernard (CREATIS), Suzanne Bussod (CREATIS), Christian Desrosiers (ETS MONTREAL), José Dolz (ETS, MONTREAL), Nicolas Duchateau (CREATIS), Rémi Emonet (LabHC), Thomas Grenier (CREATIS), Pierre-Marc Jodoin (SHERBROOKE) Carole Lartizien (CREATIS), Odyssée Merveille (CREATIS), Fabien Millioz (CREATIS), Bruno Montcel (CREATIS), Emmanuel Roux (CREATIS), Michaël Sdika (CREATIS)



This school is organised by the LabEx PRIMES with members from the CREATIS and LabHC laboratories, the University of Sherbrook and the ETS of Montréal



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