Dr Tom MacGillivray
Senior Research Fellow & Image Analysis Core Laboratory Manager

- Edinburgh Clinical Research Facility
- Edinburgh Imaging
- Centre for Clinical Brain Sciences
Contact details
- Tel: +44 (0)131 465 9565
- Email: T.J.MacGillivray@ed.ac.uk
Background
- Specialises in the field of image processing and analysis for clinical research
- My team staffs the Image Analysis Core laboratory of the Edinburgh Imaging QMRI facility joint with the Edinburgh Clinical Research Facility
- The laboratory provides specialist support to investigators accessing data from a variety of modalities including MR, CT, PET, ultrasound and retinal imaging
- Experience facilitating research that features retinal imaging and includes studies on stroke, cardiovascular disease, MS, and cognitive change with age
- Co-ordinates an interdisciplinary initiative called VAMPIRE (Vascular Assessment and Measurement Platform for Images of the REtina) - aim is efficient, semi-automatic analysis of retinal images
Qualifications
Bachelor of Science, University of Edinburgh
Master of Science, University of Edinburgh: Acoustic pulse reflectometry for the measurement of tubular structures
Doctor of Philosophy (PhD), University of Edinburgh: The application of laser anemometry in acoustic measurement standards
Postgraduate Diploma, University of Edinburgh: Academic Practice
Research summary
Image analysis allow the identification of biomarkers to aid in diagnosis, quantify disease progress, assess treatment response and inform decision making in drug discovery. In addition it is increasingly possible to relate imaging to genetic traits in individual and population studies. My team’s expertise helps to ensure that the appropriate imaging data are acquired, interpreted and analysed correctly in order to access their full potential.
Current research interests
Development of novel image processing algorithms for use in cutting-edge medical imaging and clinical research. Multi-modal retinal scanning - fundus camera, Scanning Laser Ophthalmoscope, OCT, Auto Fluorescence. Advance retinal analysis algorithm development - see VAMPIRE project for more details - http://vampire.computing.dundee.ac.uk/. Retinal imaging derived biomarker identification for neurodegeneration and systemic disease. Engaging with Industry to improve the acquisition and broadening the application of retinal imaging.-
Corrigendum to "Novel retinal vascular phenotypes for the potential assessment of long-term risk in living kidney donors." Kidney Int. 2022;102:661-665
(2 pages)
In:
Kidney International, vol. 103, pp. 429-430
DOI: https://doi.org/10.1016/j.kint.2022.12.001
Research output: Contribution to Journal › Article (Published) -
Retinal Vascular Changes in Alzheimer's Dementia and Mild Cognitive Impairment: A Pilot Study Using Ultra-Widefield Imaging
In:
Translational Vision Science & Technology, vol. 12, pp. 13
DOI: https://doi.org/10.1167/tvst.12.1.13
Research output: Contribution to Journal › Article (Published) -
A novel deep learning method for large-scale analysis of bone marrow adiposity using UK Biobank Dixon MRI data
DOI: https://doi.org/10.1101/2022.12.06.22283151
Research output: › Preprint (Published) -
Multi-modal retinal scanning to measure retinal thickness and peripheral blood vessels in multiple sclerosis
In:
Scientific Reports, vol. 12, pp. 20472
DOI: https://doi.org/10.1038/s41598-022-24312-4
Research output: Contribution to Journal › Article (Published) -
Retinal capillary microvessel morphology changes are associated with vascular damage and dysfunction in cerebral small vessel disease
In:
Journal of Cerebral Blood Flow and Metabolism
DOI: https://doi.org/10.1177/0271678X221135658
Research output: Contribution to Journal › Article (E-pub ahead of print)