Centre for Medical Image Computing (CMIC)


Centre for Medical Image Computing (CMIC)



Our aim is to make impact on key medical challenges facing 21st century society and to perform world leading research on medical imaging, image-analysis problems and applications.



A  group of academic staff, research staff and research students with close links with clinical Partners.



CMIC is located in the Engineering Front Building (EFB). The entrance to the building is in Malet Place, a small road off Torrington Place opposite Waterstone's bookshop.


CMIC success at MICCAI 2017

CMIC had several significant successes at MICCAI 2017.

Ryutaro Tanno received a Young Scientist Award for his presentation and poster - the closest MICCAI has to a best-paper award, so a great achievement!

Patrick Brandao won 3 awards at the EndoVis challenge on polyp detection and overall was placed 2nd.  Great stuff Patrick!

Guotai Wang was ranked 2nd at the BraTS challenge.  A long-standing and very competitive challenge, so very well done!

Nature Reviews Neurology Research Highlights feature MIG work (Grussu F et al, ACTN 2017)

The Research Highlights section of the prestigious journal Nature Reviews Neurology features MIG research. The highlight, which is authored by Dr Mitesh Patel and which will appear in the October 2017 issue, summarises recent results published by a joint UCL-University of Oxford venture in the Annals of Clinical and Translational Neurology (available online since august 2017).

The team, led by Professors Claudia Gandini-Wheeler Kingshott (UCL), Gabriele C. DeLuca (Oxford) and Daniel Alexander (UCL), investigates neurite orientation dispersion, namely the variability of axon and dendrite orientations, in the multiple sclerosis spinal cord. Findings demonstrate that neurite dispersion carries the signature of multiple sclerosis pathology and could therefore be a new useful biomarker. Also, the metric could be clinically relevant, since the team shows that a clinically viable MRI technique known as NODDI provides histological meaningful indices of neurite dispersion. NODDI can be already set up in clinical systems, and future work will assess whether NODDI-derived dispersion can improve the accuracy of current prognosis and be useful for treatment monitoring in multiple sclerosis.

The Research Highlight is available here: http://www.nature.com/nrneurol/journal/vaop/ncurrent/full/nrneurol.2017.127.html

The original article of Grussu F et al in ACTN is available here: http://onlinelibrary.wiley.com/doi/10.1002/acn3.445/full

Dr Gary Zhang article in "The I" newspaper

Gary has recently spent a month working at a newspaper called the I.  He wrote an article that appeared in the paper on a family that has made a massive difference to Alzheimer's research.  The article can be seen at


TIG academic wins Best Poster Award at IPMI 2017

We are pleased to congratulate Juan Eugenio Iglesias for winning the Best Poster Award at the Information Processing in Medical Imaging (IPMI) conference 2017 for is work on "Globally Optimal Coupled Surfaces for Semi-Automatic Segmentation of Medical Images". This award was shared with Adrian Dalca et al's poster on "Population Based Image Imputation".  Read the full story.

CMIC successes at IPMI 2017

Well done to Eugenio Iglesias for his joint best-poster prize and to Razvan Marinescu for his honourable mention as one of two runners-up for the Erbsmann prize.