PRIMORIS      Contacts      FAQs      INSTICC Portal
 

Keynote Lectures

To be announced soon.
Rita Cucchiara, University of Modena and Reggio Emilia, Italy

To be announced soon.
Edwin Hancock, York University, United Kingdom

Biomedical Imaging - Challenges and Potentials
Xiaoyi Jiang, University of Münster, Germany

To be announced soon.
Alfred Bruckstein, Technion, Israel

 

To be announced soon.

Rita Cucchiara
University of Modena and Reggio Emilia
Italy
 

Brief Bio
Available soon.


Abstract
Available soon.



 

 

To be announced soon.

Edwin Hancock
York University
United Kingdom
 

Brief Bio
Available soon.


Abstract
Available soon.



 

 

Biomedical Imaging - Challenges and Potentials

Xiaoyi Jiang
University of Münster
Germany
 

Brief Bio
Xiaoyi Jiang studied Computer Science at Peking University, China, and received his PhD and Venia Docendi (Habilitation) degree from University of Bern, Switzerland. He was associate professor at Technical University of Berlin and since 2002 full Professor at University of Münster, Germany. Currently, he is the dean of Faculty of Mathematics and Computer Science at University of Münster. He is a PI and research area leader of the Cluster of Excellence “Cells in Motion – Imaging to understand cellular behaviour in organisms” established by the German Research Foundation DFG in 2013. 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 journals, including IEEE Transactions on Medical Imaging, International Journal of Neural Systems, Pattern Analysis and Applications, and Pattern Recognition. His research interests include biomedical imaging, 3D image analysis, and structural pattern recognition. He is a Senior Member of IEEE and Fellow of IAPR.


Abstract
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 fields have motivated researchers to develop novel concepts and algorithms. This talk emphasizes 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 based approaches. In particular, Barista (an open-source graphical high-level interface for the Caffe deep learning framework) and its application to biomedical imaging will be presented.
Besides the information processing view the imposing development in biomedical imaging also provides a driving force for life sciences from a Galisonian perspective.



 

 

To be announced soon.

Alfred Bruckstein
Technion
Israel
 

Brief Bio
Available soon.


Abstract
Available soon.



footer