C. Baumgartner: Machine learning for medical image analysis and why clinicians are not using it

Christian Baumgartner is head of the Independent Research Group “Machine Learning in Medical Image Analysis“ at the University of Tübingen. His group has been established by the Cluster of Excellence “Machine Learning: New Perspectives for Science“. It focuses on developing technologies rooted in machine learning and computer vision with the aim to accurately and efficiently analyse medical imaging data. The group pursues topics that will help to bridge the gap between clinical applications and machine learning theory. Topics of particular interest include uncertainty estimation, robustness of predictions, working with scarce labels, and using generative modelling to extract knowledge from large medical data collections: Before joining the University of Tübingen, Christian Baugartner worked in a senior research engineering role at PTC Vuforia, where he worked on research and development of machine learning technology for augmented reality applications. Prior to this, he was