Upcoming Events

ERASMUS Course on MRI: Basic MRI Physics Sep 25, 2017 - Sep 29, 2017 — Ninewells Hospital Medical School, Dundee
7th SINAPSE-SANON Meeting Sep 28, 2017 09:30 AM - 04:00 PM — Wellcome Rooms, Royal Society of Edinburgh, 22-26 George Street, Edinburgh
ECCOMAS VipIMAGE 2017 Oct 18, 2017 - Oct 20, 2017 — Porto, Portugal
ESMRMB 2017 Congress Oct 19, 2017 - Oct 21, 2017 — Fira de Barcelona, Barcelona, Spain
NRS Mental Health Network Annual Scientific Meeting Oct 25, 2017 09:00 AM - 05:00 PM — Teaching & Learning Centre, Queen Elizabeth University Hospital Glasgow

Mr Shaun R. Stone

Position: PhD Candidate - Medical Imaging

Interests:

Shaun has recently started his PhD studentship in Medical Imaging at the University of Aberdeen. His project is titled, “Prediction Models of Dementia Risk from Brain MR Images and Proxies of Cognitive Reserve” with Professor Alison D. Murray (University of Aberdeen), Dr Roger Staff (NHS), Professor Joanna Wardlaw, Professor Craig Ritchie (University of Edinburgh) and Dr Robin Wolz (IXICO). His project is funded by SINAPSE and industry partners IXICO. Shaun completed his undergraduate (BSc) degree in Psychology with Neuroscience, and postgraduate (MSc) degree in Neuroimaging at Bangor University, North Wales - where he gained experience using a range of neuroimaging techniques (namely, fMRI). Shaun continues to learn, using his neuro-background to transfer into a medical and diagnostic imaging domain and is looking forward to his future career in research or industry, thanks to this opportunity.
Institute: Aberdeen Biomedical Imaging Centre (ABIC)

Department: School of Medicine


Research Themes

The project aims to identify the most important life-course factors and brain biomarkers that influence differences in cognitive reserve and cognitive resilience. These proxies of cognitive decline will then be incorporated into machine learning algorithms for automatic detection and classification of dementia risk from a brain scan. Such machine learning models may be able to quantify the discrepancy between the amount of disease present (MR images) and cognitive symptoms and relate this to life-course determinants. That is, given the life-course of an individual, what are the imaging characteristics that allow us to predict cognitive decline and therefore future dementia risk? Providing these models are accurate in predicting patient pathology, these approaches will be extremely useful for both clinical/pharmaceutical trials and for earlier diagnosis of patients with dementia in the NHS - improving the accuracy of diagnosis and more importantly earlier diagnosis for more appropriate intervention and care.


Collaborators

IXICO: Innovative Technologies for Treating Serious Diseases

Software Expertise

IBM's SPSS Statistics Software

MathWork's MATLAB

RStudio

FMRIB Software Library (FSL)

Statistical Parametric Mapping (SPM)