Data Sciences and Brain Health across the Life Course session in 2020 SICSA Conference Oct 01, 2020 01:15 PM - 03:15 PM — Virtual Meeting (online)
Ophthalmic Medical Image Analysis MICCAI 2020 Workshop Oct 08, 2020 12:00 AM — Virtual Meeting (online)
Predictive Intelligence in Medicine MICCAI 2020 Workshop Oct 08, 2020 12:00 AM — Virtual Meeting (online)
PET is Wonderful Annual Meeting 2020 Oct 27, 2020 02:00 PM - 05:40 PM — Virtual Meeting (online)

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…