Unfortunately, due to COVID19, the 2020 summer school had to be canceled. Those who registered will be reimbursed (minus the international transaction + currency conversion fees which are beyond our control). But please stay tuned! the school might very well be re-organized in 2021.
The organizing committee.
This school is intended for medical imaging beginners and experts (students, post-docs, research professionals, and professors) who are eager to discover the fundamentals of deep leanrning and how it translates to medical imaging. We will walk you through the basics of machine learning all the way to the latest deep learning breakthroughs applied to medical imaging. As shown in the planning, the school has both oral presentations (15 hours) and 3 hands-on sessions of 3 hours each. During the hands-on sessions, the participants will be guided through the dos and don'ts of machine learning programs for medical imaging. Please see the program for more details.
Should you be a machine learning / deep learning expert to attend the school? NO! That is the point of this school!
Should you be a programming expert to attend the hands-on session? NO! Only basic skills in Python programming are required.
We anticipate a maximum of 100 participants. Don't wait too long before to register!
NOTE: July 1st is a national holyday during which the ETS will be closed. We thus encourage you to visit the town that day and to join us during the in the evening at the Museum for a cocktail dinner (c.f. the program for more details).
|Before May 8, 2020||375 CAN$||475 CAN$|
|After May 8, 2020||410 CAN$||510 CAN$|
Fees include 4 days of classes and hands-on sessions, coffee breaks, lunchs, welcome cocktail and evening event at the museum
IMPORTANT NOTE : The following registration fees might be subject to slight modifications before the registration opening.
NO REFUND POLICY: Please note that we shall provide NO REFUND under any circumstances.
The first edition of the school on deep learning for medical imaging was held in 2019 at the Université de Lyon, France with the full logistic and financial support of the LabEx PRIMES and the CREATIS lab.
Fabien Millioz (Université de Lyon, CREATIS, LabEx PRIMES, France)
Ecole de technologie supérieure de Montréal
1111 Rue Notre-Dame Ouest
Canada, H3C 1K3