学术报告
Neural Medical Image Recovery——Professor S. Kevin Zhou Medical Imaging（Chinese Academy of Sciences）
题目：Neural Medical Image Recovery
报告人：Professor S. Kevin Zhou Medical Imaging, Robotics, Analytical Computing Laboratory & Engineering (MIRACLE) Institute of Computing Technology, Chinese Academy of Sciences
Abstract :
Medical imaging is widely used in clinical decision making. However, medical image acquisition or its acquired image still suffers from an array of challenges such as metal artifacts, slow acquisition time, anisotropic resolution, strong noise, etc. In this talk, we present several learning approaches that attempt to recover the original images under these adverse conditions:
a dual domain network (DuDoNet) for reducing metal artifacts in CT via joint learning in both sinogram and image domains;
a dual domain recurrent network (DuDoRNet) for MRI image reconstruction from undersampled k-space data via joint and recurrent learning in both frequency and image domains;
a spatially adaptive interpolation network (SAINT) for synthesizing slices to mitigate the anisotropic resolution issue; and
an artifact disentanglement network (ADN) for removing artifacts or noises without paired data while preserving anatomical structures.
Our supervised and unsupervised approaches leverage deep neural networks as cores, integrate specific domain knowledge, and yield high quality recovery for both simulated data and clinical images.
Prof. S. Kevin Zhou obtained his PhD degree from University of Maryland, College Park. He is a Professor at Institute of Computing Technology, Chinese Academy of Sciences. Prior to this, he was a Principal Expert and a Senior R&D director at Siemens Healthcare. Dr. Zhou has published 200+ book chapters and peer-reviewed journal and conference papers, registered 140+ granted patents, written two research monographs, and edited three books. His three most recent books are entitled "Medical Image Recognition, Segmentation and Parsing: Machine Learning and Multiple Object Approaches, SK Zhou (Ed.)", "Deep Learning for Medical Image Analysis, SK Zhou, H Greenspan, DG Shen (Eds.)" and "Handbook of Medical Image Computing and Computer Assisted Intervention, SK Zhou, D Rueckert, G Fichtinger (Eds.)". He has won multiple awards including R&D 100 Award (Oscar of Invention), Siemens Inventor of the Year, and UMD ECE Distinguished Alumni Award. He has been an associate editor for IEEE Trans. Medical Imaging and Medical Image Analysis, an area chair for CVPR and MICCAI. He has elected as a board member of the MICCAI society and a fellow of IEEE and AIMBE. He served as a program co-chair for MICCAI2020, Lima, Peru.
时间：2020年11月16日（周一） 13:30-15:30
地点：线上腾讯会议（会议号：737 358 155）
联系人：赵云松
主办单位：首都师范大学77779193永利官网
检测成像北京市高校工程研究中心
欢迎全体师生积极参加！
