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8 février 2019

DeepImaging2019- Spring school on deep learning for medical imaging analysis

Catégorie : Ecole thématique


DeepImaging 2019, organized by the LabEx Primes and Creatis laboratory, is a research training event which 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 and deep learning, review the most advanced deep architectures and give an insight into the most challenging subareas of this domain with a special emphasize on the specificities of deep medical image analysis.

The summer school will take place in Lyon at INSA LYON Electrical Engineering department (see access map)  from the 15th to the 19th of April 2019. We will provide accommodation and meals on the campus and strongly encourage all participants to stay at the spring school site and to take all meals on-site!

We will be offering lectures (16 hours) and 4 hands on sessions of 4 hours each in computer labs. Lectures will be given by renowned researchers, in an informal setting.

We anticipate about 50 attendees. Due to space limitation, a selection process will be applied to attendees. Pre-registration is opened. Although the target audience is students, post-docs and researchers, it is also opened to any interested parties. There are no formal pre-requisites for attendance in terms of academic degrees but basic knowledge or practice abilities in computer science are recommended.

Interaction will be a main component of the spring school. A convivial poster session (16th of April) will give participants the opportunity to present their own work in progress. We also schedule a round table fostering clinicians, industrials and research academics (15th of April) to discuss the challenges and needs to promote this research area and transfer this technology to the clinical practice.

The pre-registration will close on February 20th 2019, all information may be found on the web site: https://deepimaging2019.sciencesconf.org/


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