【海韵讲座】2019年第68期-Towards Intelligent Surgery: Dynamic Surgical Visual Perception with Deep Learning
发布时间:2019-11-19 点击:

海韵讲座第68

报告题目Towards Intelligent Surgery: Dynamic Surgical Visual Perception with Deep Learning

主讲人:Yueming JIN, The Chinese University of Hong Kong

时间:20191122 1530-16:30

地点:海韵园行政楼C505

报告简介

In modern healthcare, the operating room has undergone tremendous transformations evolving into a highly complicated and technologically rich environment. Such transformations innovate the surgery procedure and greatly enhance the patient safety. To better tackle this new scenario, the computer-assisted and robotic-assisted systems have been gradually developed to provide surgeons with the detailed contextual support.

Automatic surgical visual perception has become a crucial component when developing these systems. The exploding amount of surgical videos collected in nowadays clinical centers offer enormous opportunities, by developing a new-generation of data analytics techniques for improving these assisted systems and even revolutionizing healthcare industry. In the meanwhile,

the momentum in cutting-edge AI systems is towards representation learning and pattern recognition via data-driven approaches.

报告人简介

Dr. Yueming JIN has received her Ph.D. degree in Computer Science and Engineering from The Chinese University of Hong Kong in July 2019, supervised by Prof. Pheng-Ann Heng and Prof. Chi-Wing Fu. Before that, she got her Bachelor's degree in Biomedical Engineering at Northeastern University in China with honor in 2015. Her research interests are in the development of advanced machine learning methods for medical image analysis and surgical robotic perception, with expertise in deep learning. She received Hong Kong Postgraduate Fellowship (HKPFS) from 2015-2019. She has won the Best Paper Award of Medical Image Analysis-MICCAI in 2017. She has published over 10 papers in top-tier journals and conferences, including IEEE-TMI, Medical Image Analysis, Radiology, MICCAI, SIGGRAPH Asia, etc. Her current Google Scholar citation is 350+ with h-index 6.


邀请人:王连生 计算机科学系