04/13/2022
By Ian Chen
Location: Via Zoom (Passcode: cstalks)
Time: 3:30 – 4:30 p.m., Friday, April 15
Abstract: Cardiac Magnetic Resonance Fingerprinting (MRF) is a novel framework for obtaining quantitative maps of multiple tissue properties (such as the MRI relaxation times T1 and T2) from one rapid acquisition. The purpose of this talk is to introduce the basics of the cardiac MRF technique and provide an overview of recent advances in cardiac MRF, including the use of physics-based deep learning to shorten scan times and improve image quality. During the first half of the presentation, the basic steps in acquiring and reconstructing cardiac MRF data will be described, including pulse sequence design, k-space sampling methods, dictionary generation, and pattern matching. Next, recent advances in cardiac MRF will be discussed, including 1) 3D free-breathing MRF; 2) cine MRF for simultaneous functional imaging and tissue characterization, and 3) applications of deep learning for MRF dictionary generation and parameter map reconstruction.
Bio: Jesse Hamilton received his B.S. degree in Biomedical Engineering from Johns Hopkins University, Baltimore, MD, USA in 2012, and his Ph.D. degree from Case Western Reserve University in 2018 with a focus on rapid quantitative magnetic resonance imaging techniques. After completing postdoctoral research at Case Western Reserve University and the University of Michigan, he joined the Department of Radiology at the University of Michigan as an Assistant Professor in 2020 with a secondary appointment in Biomedical Engineering. Currently, his work focuses on the development of rapid quantitative cardiac MRI methods for imaging the heart, including Magnetic Resonance Fingerprinting, as well as physics-based deep learning algorithms for reconstructing MRI data. He is active in multiple societies, including the International Society for Magnetic Resonance in Medicine and the Society for Cardiovascular Magnetic Resonance, and has authored or co-authored over 20 peer-reviewed articles in the field of rapid imaging and quantitative MRI.
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