InnerEye – Assistive AI for Cancer Treatment

InnerEye – Assistive AI for Cancer Treatment

Established: October 7, 2008

InnerEye is a research project that uses state of the art artificial intelligence to build innovative image analysis tools to help doctors treat diseases such as cancer in a more targeted and effective way.

“…We are pursuing AI so that we can empower every person and every institution that people build with tools of AI so that they can go on to solve the most pressing problems of our society and our economy. That’s the pursuit.”.

Satya Nadella, keynote at Microsoft IGNITE 2016.

Plenary InnerEye session @ RSNA 2017

I am incredibly honoured to have been selected as a plenary speaker at RSNA 2017  (Nov 28th 2017). Please come and see what we are up to in Assistive AI for Cancer Treatment. Antonio.

Project description

The project’s main focus is in the treatment of tumors and monitoring the progression of cancer in temporal studies.

InnerEye builds upon many years of research in computer vision and machine learning. It employs decision forests (as used already in Kinect and Hololens) to help radiation oncologists and radiologists deliver better care, more efficiently and consistently to their cancer patients.

Demo videos



In Aug 2012 our algorithm for the automatic detection and localization of anatomy within Computed Tomography scans has obtained FDA 510(k) clearance.


Please send an email to if you wish to collaborate with us or would like further information on this project.







Infrared depth sensor based automated classification of motor dysfunction in multiple sclerosis – a proof-of-concept study
Marcus DSouza, J. Burggraaf, Christian P. Kamm, Prejass Tewarie, Peter Kontschieder, Jonas F. Dorn, Cecily Morrison, Thomas Vogel, Abigail Sellen, Matthias Machacek, Peter Chin, Antonio Criminisi, Frank Dahlke, Bernard Uitdehaag, Ludwig Kappos, in European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), September 1, 2014, View abstract, View external link
Quantifying Progression of Multiple Sclerosis via Classification of Depth Videos
Peter Kontschieder, Jonas F. Dorn, Cecily Morrison, Bob Corish, Darko Zikic, Abigail Sellen, Marcus DSouza, Christian P. Kamm, Jessica Burggraaff, Prejaas Tewarie, Thomas Vogel, Michael Azzarito, Ben Glocker, Peter Chin, Frank Dahlke, Chris Polman, Ludwig Kappos, Bernard Uitdehaag, Antonio Criminisi, in MICCAI 2014 - Intl Conf. on Medical Image Computing and Computer Assisted Intervention, Springer, September 1, 2014, View abstract, Download PDF