Medical Imaging Convention [rescheduled] Mar 09, 2021 - Mar 10, 2021 — National Exhibition Centre, Birmingham, England
9th SINAPSE Neuro-oncology Imaging Meeting [rescheduled] Mar 11, 2021 09:30 AM - 03:30 PM — West Park Conferencing & Events, 319 Perth Road, Dundee DD2 1NN
Total Body PET 2020 conference [rescheduled] Jun 05, 2021 - Jun 07, 2021 — McEwan Hall, University of Edinburgh

eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

Disentangled Representations for Efficient Algorithms for Medical data MICCAI 2020 Tutorial

Tutorial on Disentangled Representations for Efficient Algorithms for Medical data (DREAM) at MICCAI 2020
When Oct 04, 2020
from 12:00 AM to 12:00 AM
Where Virtual Meeting (online)
Contact Name
Add event to calendar vCal
iCal

UPDATE: this event is being moved to a virtual format due to spread of the COVID-19 Coronavirus.

Disentangled representation learning has been proposed as an approach to learning general representations. This can be done in the absence of annotations, or with limited annotation. A good general representation can be readily fine-tuned for new target tasks using modest amounts of data. This alleviation of the data and annotation requirements offers tantalising prospects for tractable and affordable healthcare. Finally, disentangled representations can offer model explainability, increasing their suitability for real-world deployment.

In this half-day tutorial, a satellite event in conjunction with MICCAI 2020, we will offer an overview of representation learning and disentangled representation learning and criteria, and discuss applications in medical imaging. We will conclude with open ended challenges.

More information about this event…