Fakultätskolloquium M&I - Biomedical Imaging: Driving force for life sciences

Imaging has become an indispensable tool in biology and medicine for both basic research and clinical practice. The specific image characteristics and problems in these areas have motivated researchers to develop novel concepts and algorithms. This talk highlights the fundamental research view of biomedical imaging and discusses a number of related challenges, concepts, and algorithms. In addition to the traditional computer vision approaches, another focus will be given to machine learning / deep learning based approaches. Besides the information processing view the imposing development in biomedical imaging also provides a driving force for advances in life sciences.

Xiaoyi Jiang studied Computer Science at Peking University, China, and received his PhD and Venia Docendi (Habilitation) degree in Computer Science from University of Bern, Switzerland. He was an associate professor at Technical University of Berlin, Germany. Since 2002 he is a full professor at University of Münster, Germany, and currently the Dean of the Faculty of Mathematics and Computer Science. He is Editor-in-Chief of International Journal of Pattern Recognition and Artificial Intelligence. In addition, he also serves on the advisory board and editorial board of several other journals including IEEE Transactions on Medical Imaging and International Journal of Neural Systems. His research interests include image analysis, pattern recognition, and machine learning. Prof. Jiang is a Fellow of IAPR (International Association for Pattern Recognition) and senior member of IEEE.