Developing ASL (arterial spin labelling) biomarkers for neurodegenerative disease -- in particular, dementia.
Studying how ASL models can be better linked to underlying tissue/pathology.
Investigating coupled statistical models and fitting methods for analysis of multi-modal imaging data.
Making imaging protocols more intelligent with optimal design theory.
- Melbourne, A.; Pratt, R.; Sokolska, M.; Owen, D.; Bainbridge, A.; Atkinson, D.; Kendall, G.; Deprest, J.; Vercauteren, T.; David, A.; Ourselin, S. DECIDE: Diffusion-rElaxation Combined Imaging for Detailed Placental Evaluation. ISMRM 2017.
- Owen, D.; Melbourne, A.; Sokolska, M.; Thomas, D. L.; Rohrer, J.; Ourselin, S. Bayesian experimental design for multi-parametric T1/T2 relaxometry and diffusion. ISMRM 2017.
- Owen, D.; Melbourne, A.; Thomas, D. L.; Beckmann, J.; Rohrer, J.; Marlow, N.; Ourselin, S. ADRIMO: Anatomy-DRIiven MOdelling of spatial correlation to improve analysis of arterial spin labelling data. ISMRM 2017. Awarded a trainee stipend on the basis of these two abstracts.
- Owen, D.; Melbourne, A.; Thomas, D. L.; De Vita, E.; Rohrer, J.; Ourselin, S. Optimisation of arterial spin labelling using Bayesian experimental design. MICCAI 2016. Student Travel Award given for this work.
- Melbourne, A.; Pratt, R.; Owen, D.; Sokolska, M.; Bainbridge, A.; Atkinson, D.; Kendall, G.; Deprest, J.; Vercauteren, T.; Atkinson, D.; Ourselin, S. Placental Image Analysis using Coupled Diffusion-Weighted and Multi-Echo T2 MRI and a Multi-Compartment Model. Perinatal, Preterm and Paediatric Image Analysis Workshop, MICCAI 2016.
- Melbourne, A.; Toussaint, N.; Owen, D.; Simpson, I.; Anthopoulos, T.; De Vita, E.; Atkinson, D.; Ourselin, S. NiftyFit: A software package for multi-parametric model-fitting of 4D magnetic resonance imaging data. Neuroinformatics, 2016. Accompanying open-source software release.
- Owen, D. Supervised by Ourselin, S.; Melbourne, A.; Thomas, D. & Rohrer, J. Towards Intelligent Imaging of Perfusion Using Arterial Spin Labelling. MRes thesis, UCL Centre for Doctoral Training in Medical Imaging.
- Owen, D. Supervised by Chappell, M. Fast Bayesian Analysis of Clinical Signals. MEng thesis, University of Oxford Department of Engineering Science.
Example changes in cerebral blood flow (CBF) and arterial transit time (Δt) posterior standard deviation,
comparing an optimised acquisition to a standard acquisition in a single gray matter slice.
My first degree was in engineering (1st class MEng, University of Oxford, 2010-2014), specialising in mathematical modelling and software for biomedical applications. The bulk of my professional experience has been in software, although in 2013 I was fortunate enough to receive funding for a three-month experimental research project examining motor degradation. In my masters year, I went on to research speed and accuracy improvements for variational Bayesian parameter estimation and model fitting. I'm excited to be part of TIG, using theory and software to directly improve patient outcomes.
Hobbies include reading, tennis and electronics. Grab me if you want to talk books, play tennis or build some breadboards!