2020 SINAPSE ASM Jun 19, 2020 09:00 AM - 05:00 PM — Virtual Meeting (online)
3rd International Conference on Medical Imaging with Deep Learning Jul 06, 2020 - Jul 08, 2020 — Virtual Meeting (online)
Medical Image Understanding and Analysis Conference 2020 Jul 15, 2020 - Jul 17, 2020 — Virtual Meeting (online)
CAFACHEM 2020 Summer School on Organic & Halogen Radiochemistry Aug 25, 2020 - Aug 28, 2020 — KCL Waterloo Campus, London
Scottish Dementia Research Consortium Annual Conference 2020 [rescheduled] Sep 07, 2020 10:00 AM - 04:00 PM — Radisson Blu, 301 Argyle St, Glasgow

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

SINAPSE seed fund PhD studentship available at Glasgow

Automated analysis tools for assessing the vasculature in imaging for acute stroke

A SINAPSE seed fund PhD studentship is available at the University of Glasgow, in collaboration with industry partner Toshiba Medical Visualization Systems Europe.

Project summary:

The project concerns the development and evaluation of image analysis tools for studying the vasculature in cases of acute ischaemic stroke. A starting point would be the scoring of collateral flow in CT angiography (CTA) datasets. In acute ischaemic stroke, collateral flow via leptomeningeal vessels maintains viable brain tissue (the “ischaemic penumbra”) for a variable period of time. Treatment responses to reperfusion are better in those with good compared to poor collaterals, so collateral flow assessment may therefore be critical in the acute decision making stage after stroke.

A method of scoring has been developed at the University of Glasgow, but this involves many manual steps. To fully automate these steps, the cerebral vasculature and circulation territories need to be segmented, occlusion sites identified and careful contra-lateral analysis performed. This represents a significant image analysis challenge, possibly requiring atlas based and machine learning approaches.

Once a software tool has been developed on available acute stroke data, the automated scoring system will require testing against expert readers in observer agreement studies that can utilise CTA from the acute stroke database at the University of Glasgow. Comparison against data from acute angiograms in the PISTE multicentre trial will provide additional validation against an expert panel of readers and conventional angiography. Validation against clinical outcomes and other imaging variables, including CT perfusion, will be obtained from the South Glasgow Stroke Imaging database.

Application deadline: 24th June 2016

For more information on the project and how to apply, please visit: http://master.findaphd.com/search/ProjectDetails.aspx?PJID=73748&LID=559