PhD Students

Contact

8th Floor
Malet Place Engineering Building
University College London
London
"This email address is being protected from spambots. You need JavaScript enabled to view it.
Download information as: vCard

Miscellaneous Information

Research:

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.

Publications:

2017

  • Owen, D.; Melbourne, A.; Eaton-Rosen, Z.; Thomas, D. L.; Marlow, N.; Rohrer, J.; Ourselin, S. Anatomy-driven modelling of spatial correlation for regularisation of arterial spin labelling images. MICCAI 2017.
  • Melbourne, A.; Pratt, R.; Sokolska, M.; Owen, D.; Bainbridge, A.; Atkinson, D.; Kendall, G.; Deprest, J.; Vercauteren, T.; David, A.; Ourselin, S. Separation of fetal and maternal circulations using multi-modal MRI. Placenta, 2017.
  • 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.

 

2016

 

2015

 

Theses

  • 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.

 

Selected Results:

Example improvements in cerebral blood flow and arterial transit time estimation using an optimised acquisition.

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.

 

About:

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!