Machine Learning in Health Care
Analysis of medical images is essential in modern medicine. With the ever-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 scans. 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.
Antonio Criminisi joined Microsoft Research Cambridge as a Visiting Researcher in 2000. In 2001 he moved to the Interactive Visual Media Group in Redmond (WA, USA) as a Post-Doctoral Researcher. In 2002 he moved back to Cambridge UK to join the Vision Group as a Researcher. In 2013 he became Principal Researcher and now leads the medical image analysis team. Antonio’s research interests include medical image analysis, object recognition, image and video analysis and editing, teleconferencing, 3D reconstruction with application to virtual reality, forensic science, and history of art. Prior to Microsoft, he received a degree in Electronics Engineering from the University of Palermo, and in December 1999, he obtained the Doctor of Philosophy 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 2000. He has won a number of best paper prizes in top computer vision conferences.
- Antonio Criminisi
- Microsoft Research
Partner Research Lead Mesh Labs (Mixed Reality & AI) Microsoft Cambridge