BME Seminar: Duohua Sun
Monday, October 24, 2022 - 12:00 p.m.
Duohua Sun
Ph.D. Candidate
The Department of Biomedical Engineering
The University of Arizona
"Improving Spatial-temporal-resolution and Signal-to-noise Ratio for Dynamic MRI"
Keating 103 | Live Zoom link, passcode: BearDown
(Instructor permission required for enrolled students to attend via Zoom)
Hosts: Dr. Beth Hutchinson and Dr. Shang Song
Persons with a disability may request a reasonable accommodation by contacting the Disability Resource Center at 621-3268 (V/TTY).
ABSTRACT: Improvement in spatial and temporal resolution directly benefits the sensitivity and specificity of T2*-weighted dynamic MRI, for various applications ranging from dynamic susceptibility contrast to functional MRI. However, it is challenging to simultaneously achieve high signal quality and high spatial-temporal- resolution due to trade-offs that exist among resolution, acquisition time and signal-to-noise ratio. One example is that reducing MRI voxels size improves spatial resolution, but results in the increase of data acquisition time and the reduction of signalto-noise ratio. One approach to resolve this challenge is to use super-resolution to reconstruct high resolution images using spatially-sub-voxel-shifted (along the slice-selection direction) low resolution images. As shown in previous studies, high spatial-temporal-resolution functional MRI could be achieved when combining super-resolution and multi-band MRI (e.g., SLIDER-SMS). However, susceptibility signal loss in T2*-weighted dynamic MRI data obtained with thick slices has not been well addressed with existing magnitude-only super-resolution reconstruction scheme. In this project, Sun will present an approach for improving spatial and temporal resolution of complex-valued T2*-weighted dynamic MRI. Compared with the conventional magnitude-valued super-resolution approaches, our technique utilizes phase information to better recover signal loss caused by susceptibility gradients and generate finer representations of temporal dynamic signal variation. Results from numerical and hybrid simulation show that promising improvements in image resolution, susceptibility artifact reduction and temporal signal variation representation can be achieved using Sun's complex-valued super-resolution MRI scheme when compared to magnitude-valued super-resolution.