题目:Computational Diffusion MRI Analysis Using Deep Learning

报告人：张帆

邀请人：何宏建

时间：2023年6月28日（周三），下午15：00

地点：玉泉校区教十二203会议室 

摘要:Diffusion MRI is an advanced imaging technique that measures the random molecular motion or diffusion of water molecules. It enables estimation of the underlying tissue microstructure and allows in vivo mapping of the brain’s white matter connections. Recent advances in deep learning have witnessed great success in computational diffusion MRI, which has shown great potential in clinical and research applications, e.g., study of the brains in health and disease and neurosurgical planning research. In this talk, Dr. Zhang will introduce several machine/deep learning techniques that he and his colleagues developed for computational diffusion MRI tasks as well as applications of his methods in clinically relevant tasks.

个人简介:

Fan Zhang is a national young talent, a Professor at the University of Electronic Science and Technology of China (UESTC), and an adjunct researcher at Harvard Medical School (HMS). From 2015 to 2023, he was a visiting scholar, a postdoctoral researcher, and then a faculty member at HMS in the USA. In 2016, he received my PhD degree in Computer Science from The University of Sydney (USYD) in Australia. Fan Zhang’s research focuses on developing advanced AI-based technologies for medical image analysis and neuroimage computing, with the goal of providing clinicians with the tools and information needed to make accurate diagnoses and to guide effective treatments, ultimately improving patient outcomes and quality of life. Fan Zhang has published over 120 peer-reviewed papers in leading international journals and proceedings at top international conferences such as MedIA, IEEE TMI, MICCAI, CVPR. Fan is an Associate Editor for Frontiers in Radiology, Editorial Board Member for Meta-Radiology and Brain-X, and an Area Chair for MICCAI 2023. Fan was an organizer of the CDMRI Workshops (2019, 2020) and the MUDI and Super-MUDI Challenges. Fan also serves as a regular reviewer for over 40 journals and conferences.

欢迎老师和同学参加！