Events Calendar

PhD Defense

Talk Title: Efficient and Accurate 3D FISP=MRF at 0.55 T

Abstract: Magnetic Resonance Fingerprinting (MRF) are a set of popular multiparametric quantitative MRI techniques. With the resurgence of interest in mid- and low-field MRI, such as the 0.55 T MR system in Dynamic Imaging Science Center in USC, these techniques have gained growing research and clinical tractions. At 0.55 T, a basic fast imaging with steady-state free precession (FISP)-MRF approach has been shown feasible with promising but unexplored improvements, however, also with substantial quantification biases from reference measurements and literature values. Therefore, how to perform this approach in a more Signal-to-Noise Ratio(SNR) efficiency optimized way and how to improve its quantification accuracy have become interesting research problems.
In this dissertation, I propose a more efficient and accuracy FISP-MRF approach at 0.55 T. I start with improving 0.55 T FISP-MRF SNR efficiency and the approach produces more precise results (up to 50% smaller standard deviation values) but temporarily with unaddressed biases. It includes higher readout duty cycle, constrained reconstruction and artifacts mitigation algorithms. Then, I focus on refining RF excitation designs, which helps to partially suppress the sources of bias, resulting in more accurate quantification (~75% less bias).

Biography: Zhibo Zhu is a PhD candidate in Electrical and Computer Engineering in University of Southern California, advised by Prof. Krishna S. Nayak. He received Bachelor of Science degree in Nanjing University of Post and Telecommunication in 2015 and Master of Science degree in University of Southern California in 2017. His current research interest is improved FISP-MRF at 0.55 T MRI.
 

Host: Krishna Nayak

Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

Audiences: Everyone Is Invited

Contact: Bella Schilter