4th International Conference on Medical Imaging with Deep Learning Jul 07, 2021 - Jul 09, 2021 — Virtual Meeting (online)
Medical Image Understanding and Analysis Conference 2021 Jul 12, 2021 - Jul 14, 2021 — Virtual Meeting (online)
Medical Imaging Convention [rescheduled] Sep 15, 2021 - Sep 16, 2021 — National Exhibition Centre, Birmingham, England
2021 SINAPSE ASM Sep 16, 2021 - Sep 17, 2021 — Technology & Innovation Centre, University of Strathclyde, 99 George Street, Glasgow
Total Body PET 2021 conference [rescheduled] Sep 22, 2021 - Sep 24, 2021 — Virtual Meeting (online)


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 Dundee

Measuring and modeling haemodynamics and vessel stiffness in arterial disease and endovascular treatment

A SINAPSE seed fund PhD studentship is available at the University of Dundee, in collaboration with the University of Edinburgh and industry partner Vascular Flow Technologies.

Project summary:

Arterial disease is responsible for up to one third of world deaths. Arterial surgery is performed on patients at risk of clinical events such as amputation, heart attack, stroke, or to create fistula for renal dialysis. The success of the treatment and the underlying arterial disease progression is adversely affected by abnormal blood flow, arterial wall stresses and stiffness and varies significantly between patients.  Until recently there have been no means of assessing these key factors in clinical practice. Recent advances in ultrasound as a non-invasive imaging tool allows us to measure tissue stiffness, while advances in computational techniques allow is to model blood flow and the stresses on vessels. However these have not reached clinical practice

We will develop improved methods for identifying which patients will best benefit from surgery and which surgical procedures or devices are more likely to fail. We will use 3 recently available imaging-based methods for measuring the mechanical environment within arterial diseases.

We aim to test these new techniques in an important group of patients with leg arterial disease in order that we can validate the technique and assess its potential use in research and clinical practice. These patients are at risk of leg amputation.  If we can select which patents would be most suitable for a particular surgical procedure and which medical device would have the greatest chance of success we will avoid un-necessary operations and improve the outcome for patients with leg arterial disease.

Application deadline: 1st May 2016

For more information on the project and how to apply, please visit: https://www.findaphd.com/search/ProjectDetails.aspx?PJID=73879

Details of the other awarded seed fund studentships to follow: PhD Opportunities.