BSc BE DPhil
Professor of Neuroimaging
- Head of Structural Modelling and Analysis
There are two major themes to my research: (i) multimodal modelling of populations to describe disease processes and apply to individual patient diagnoses; and (ii) structural segmentation and analysis of brain anatomy and pathology, especially sub-cortical structures, lesions and their relationship with disease.
Awards, Training and Qualifications
- 2014- 2016 Thomson Reuters' list of Highly Cited Researchers
- 2005- 2010 David Phillips Fellowship, BBSRC
- 1995- 1999 DPhil, University of Oxford
- 1989- 1993 BE - Electrical and Electronic (Hons I),University of Adelaide
- 1989- 1994 BSc (Hons I), University of Adelaide
BIANCA-MS: An optimized tool for automated multiple sclerosis lesion segmentation.
Gentile G. et al, (2023), Hum Brain Mapp
Challenges for machine learning in clinical translation of big data imaging studies.
Dinsdale NK. et al, (2022), Neuron
Integrating large-scale neuroimaging research datasets: Harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets.
Bordin V. et al, (2021), Neuroimage, 237
Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications
Boyd C. et al, (2021), DIAGNOSTICS, 11
White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.
Melazzini L. et al, (2021), Neuroimage Clin, 30