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“Can we train a machine to help us read medical images, and detect patterns of disease that humans find difficult to see?”

L 2038I am Lecturer in Medical Image Computing at Imperial College London and a member of the Biomedical Image Analysis Group in the section of Visual Information Processing at the Department of Computing.

My research is in the area of biomedical image computing and medical computer vision with a focus on semantic understanding of images using machine learning and artificial intelligence.

I am teaching Algorithms and Medical Image Computing, coordinate the HiPEDS Group Projects, and lead the stream 3 of the Medical Imaging CDT.


DeepMedicArchitectureDeepMedic Source Code Released

Just released our DeepMedic software on Github. That’s deep, fully 3D convolutional neural networks for medical image segmentation! The code has been used in our winning entry for the ISLES 2015 stroke lesion segmentation challenge, and for brain tumour segmentation and traumatic brain injuries.


NVIDIA Global Impact Award Finalists

We are very excited to be placed among five finalists for the 2016 NVIDIA Global Impact Award with our work on Deep Learning for Brain Lesion Segmentation. The credit goes to PhD student Konstantinos Kamnitsas. More details about the work can be found here.


logo33Call for Participation: mTOP Challenge

We are co-organising the mTOP challenge hosted at MICCAI’16. The task is to use unsupervised learning on brain MRI for grouping patients with traumatic brain injury. More details can be found on the mTOP website.


2015 Imperial Festival Demo

ElasticFusion presented at RSS 2015


my-logoEPSRC-NIHR Medical Image Analysis Network

The BioMedIA group is a member of the EPSRC-NIHR Healthcare Technology Co-operatives Partnership Medical Image Analysis Network (MedIAN) which seeks to bring together leading UK researchers in medical image analysis with relevant stakeholders to identify new opportunities for medical image analysis methodology research and early clinical translation. More information can be found on the MedIAN website.


SpineWeb Onlinespineweb

As a founding member of an international research initiative on spine imaging, we are proud to announce the official opening of the SpineWeb – A Collaborative Platform for Research on Spine Imaging and Image Analysis. Researchers are invited to actively participate in this initiative and contribute to the SpineWeb platform.

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