I am a post-doctoral research associate in the Centre for Medical Image Computing (CMIC) and the Dementia Research Centre (DRC) at University College London. I work with Professor Sebastien Ourselin and Professor Nick Fox. My current research follows two strands: Firstly, the investigation of methodologies for analysing diffusion magnetic resonance images, with the aim of developing sensitive and reliable biomarkers of neurodenegerative disease. My other work focuses on the development of generative Bayesian models for image registration that allow the quantification of registration uncertainty and facilitate model selection, with application to describing group differences or longitudinal changes in brain morphology.

General research interests include: Medical Image Analysis, Generative Models, Bayesian Analysis, Pattern Recognition and Statistical Learning.

I received my DPhil (PhD) from the University of Oxford in 2013, jointly supervised by Dr Julia Schnabel and Dr Mark Woolrich, within the Institute of Biomedical Engineering and the Oxford Centre for Functional MRI of the Brain. The focus of my DPhil was in the development of non-rigid registration methodology with application to the detection of Alzheimer's Disease through the use of biomarkers derived from structural MR images of the brain. Specifcally, my thesis explores the use of Bayesian statistical methods in facilitating adaptive regularisation and providing estimates of registration uncertainty. I subsequently describe approaches for incorporating registration uncertainty into statistical analysis for the detection of Alzheimer's Disease

I studied Computer Science with Image and Multimedia at the University of Southampton, graduating with MEng 1st class in 2008 with the Quantum Research Group award for academic achieviement. I also recieved the MISYS scholarship for academic achievement for 3 years during my undergraduate studies.

My CV is available here.


I formely designed and ran a week long course on Engineering for gifted AS/A2 students at the Villiers Park Educational Trust with Rob Spanton between 2009-2012.

I was involved in teaching on the Centre for Doctoral Training in Healthcare Innovation DPhil program. Specifically doing lab demonstration on Biological Signal Processing and demonstrating and lecturing on Information Driven Healthcare.

DPhil Thesis

Simpson, I.J.A., A Probabilistic Approach To Non-Rigid Medical Image Registration, DPhil Thesis, University of Oxford. Link.

Peer Reviewed Publications


Simpson, I.J.A., Woolrich, M.W, Cardoso, M.J., Cash, D.M., Modat, M., Schanbel, J.A., Ourselin, S.
A Bayesian Approach for Spatially Adaptive Regularisation in Non-Rigid Registration
To Appear at MICCAI 2013, contact me for a pre-print.

Simpson, I.J.A., Woolrich, M.W., Andersson, J.L.R., Groves, A.R.,Schnabel, J.A.
Ensemble Learning Incorporating Uncertain Registration
IEEE Transactions on Medical Imaging 32(4), pp. 748-756, 2013


Simpson, I.J.A., Schnabel, J.A., Groves, A.R., Andersson, J.L.R., Woolrich, M.W.
Probabilistic inference of regularisation in non-rigid registration
Neuroimage 59(3), pp. 2438-51, 2012

Simpson, I.J.A., Schnabel, J.A., Andersson, J.L.R., Groves, A.R., Woolrich, M.W.
A Probabilistic Non-Rigid Registration Framework Using Local Noise Estimates
Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI) 2012.

Simpson, I.J.A., Schnabel, J.A., Andersson, J.L.R., Groves, A.R., Woolrich, M.W.
Ensemble Learning Incorporating Uncertain Registration
Proceedings of Medical Image Understanding and Analysis (MIUA) 2012.


Simpson, I.J.A, Woolrich, M.W., Groves, A.R., Schnabel, J.A.
Longitudinal Brain MRI Analysis with Uncertain Registration
In: Fichtinger, G., Martel, A. and Peters, T., MICCAI 2011, LNCS, vol. 6892, pp. 647-654, 2011
Poster, Slides from talk and Paper

Simpson, I.J.A., Woolrich, M.W., Schnabel, J.A.
Probabilistic segmentation propagation from uncertainty in registration
Proceedings of Medical Image Understanding and Analysis (MIUA) 2011.
Poster and Paper


Email: ivor.simpson at ucl.ac.uk