PhD: Machine Learning for medical Image Analysis


July 3, 2012


Antonio Criminisi




Analysis of medical images is essential in modern medicine. With the increasing amount of patient data, new challenges and opportunities arise for different phases of the clinical routine, such as diagnosis, treatment and monitoring. The InnerEye research project focuses on the automatic analysis of patients’ medical images. It uses state of the art machine learning techniques for the:

  • Automatic delineation and measurement of healthy anatomy and anomalies;
  • Robust registration for monitoring disease progression;
  • Semantic navigation and visualization for improved clinical workflow;
  • Development of natural user interfaces for medical practitioners.

Our mission is to advance the state of the art in machine learning and marry it with medical expertise, with application in computer-aided diagnosis, personalized medicine and efficient data management. Some of this technology is now incorporated within the Microsoft Amalga Unified Intelligence System.


Antonio Criminisi

Antonio Criminisi joined the Machine Learning and Perception group at Microsoft Research Cambridge in June 2000 as Visiting Researcher. In February 2001, he moved to the Interactive Visual Media Group in Redmond (WA, USA) as a Post-Doctorate Researcher. In October 2002, he moved back to the Machine Learning and Perception Group in Cambridge as Researcher. Antonio’s current research interests are in the area of medical image analysis, object category recognition, image and video analysis and editing, one-to-one teleconferencing, 3D reconstruction from single and multiple images with application to virtual reality, forensic science and history of art.

Antonio Criminisi was born in 1972 in Italy. In October 1990 he was appointed “Alfiere del Lavoro” by the Italian President F. Cossiga for his successful studies. In July 1996 he received a Degree in Electronics Engineering at the University of Palermo and in December 1999, he obtained a “Doctor of Philosophy” (PhD) Degree in Computer Vision at the University of Oxford. His thesis “Accurate Visual Metrology from Single and Multiple Uncalibrated Images” won the British Computer Society Distinguished Dissertation Award for the year 2000 and was published by Springer-Verlag London Ltd. in August 2001. Antonio was a Research Fellow at Clare Hall College, Cambridge from 2002 to 2005. Antonio has won a number of best paper prizes in top computer vision conferences.