The large amount of imaging data that is acquired everyday in clinical routine raises immense computational challenges. The data often needs to be processed and transformed into clinically useful information very quickly in order to incorporate this information into tasks such as computer aided diagnosis and intervention. Such time-critical applications demand efficient algorithms and high-performance computing infrastructures. Besides time efficiency, an important aspect is the ability to process large databases containing thousands of datasets from groups of patients or even populations. Such big data can help us to better understand pathologies and we can learn to build computational models and tools for improved diagnosis and therapy.

The mission of the Biomedical Image Analysis Group is to develop novel, computational techniques for the analysis of biomedical images, in particular in the context of big data. The group has strong expertise in applying machine learning algorithms to tackle the current and future problems in healthcare. We have extensive, close collaborations with numerous clinical institutions and hospitals in the UK and around the world. For more details about our research, visit: http://biomedic.doc.ic.ac.uk/


Prof. Daniel Rueckert

Dr. Ben Glocker

Dr. Bernhard Kainz