报 告 人：Shuo Li， University of Western Ontario
报告题目：New Opportunities in Medical Image Analysis
报告时间：2015.12.28， 10：00- 11：30
报告地点：教三326
报告内容及报告人简介：
New Opportunities in Medical Image Analysis
Dr. Shuo Li
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.
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.
