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EE讲堂

学术报告:New Opportunities in Medical Image Analysis

报告时间:星期四(2016.7.21)10:00am
报告地点:电子信息楼306
报告人:Shuo Li Associate professor University of Western Ontario
邀请人: 陈新建特聘教授
报告摘要:
Medical image analysis is going through great changes with tremendous new opportunities showing up. The rise of machine learning, the rise of big data analytics and the rise of cloud computing, have brought wonderful opportunities to invent new generation of medical image analysis, not only to solve new problems appearing, but also to solve many years challenges in conventional medical image analysis with much more satisfactory real time solutions. This talk will share our experience on developing state-of-art new generation of image analytics tools to help physicians, hospital administrative to analyze the huge growing medical data and help them to make the right decision and early decision. 
报告人简介:
Dr. Shuo Li is an associate professor in department of medical imaging and medical biophysics in the University of Western Ontario and scientist in Lawson Health Research Institute. Before this position he was research scientist and project manager in general electric (GE) healthcare, Canada for 9 years. He fund and direct the Digital Imaging Group of London (http://digitalimaginggroup.ca/) since 2006, which is a very dynamic and highly multiple disciplinary collaboration group. He received his Ph.D. degree in computer science from Concordia University 2006, where his PhD thesis won the doctoral prize giving to the most deserving graduating student in the faculty of engineering and computer science. He has published over 100 publications; He is the recipient of several GE internal awards; He serves as guest editors and associate editor in several prestigious journals in the field; He servers as program committee members in highly influential conferences; He is the editors of five springer books. His  current interest is development intelligent analytic tools to help physicians and hospital administrative to handle the big medical data, centered with medical images
 

 

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