Xi Peng of University of Iowa

Abstract

Multi-modal MRIs offer the opportunity to comprehend the intricate functional, metabolic, and physiological states of the brain. However, the practical utilization of these techniques is impeded mainly by four types of longstanding obstacles, including the curse of dimensionality, the demand for high resolution, low SNR or signal sensitivity, and the inevitable presence of physiological noise or nuisance signals. To address these problems, many efforts have been directed towards the development of fast scanning sequences, advancement of hardware, and evolution of signal processing approaches such as parallel imaging, sparse/low-rank models, and machine learning. In this talk, I will briefly introduce our work in this regime, focusing on the development of advanced imaging data acquisition and processing tools for MR Spectroscopic imaging, MR Elastography, quantitative susceptibility mapping, etc.

Biography:

Short-Bio: Xi Peng received his Ph.D. degree in electrical engineering in 2012 from Wuhan University, Hubei, China. He was an associate professor at Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, and the PI on several key grants. He is currently an assistant professor and Director of Pediatric MR Research in the Department of Radiology at the University of Iowa. He received the Summa Cum Laude, Magna Cum Laude Merit Awards from ISMRM, Best Paper Award from the MR Elastography study group and Outstanding Research Award from OCSMRM. His research focuses on the development of innovative MRI data acquisition and computational tools for high-dimensional brain imaging, such as MR Spectroscopic imaging, MR Elastography, and quantitative mapping.

Email:

Address:Iowa City, Iowa, United States, 52242