Fri, Dec 10, 2021 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Talk Title: Improved Regularized Simultaneous Multi-slice (SMS) Imaging Reconstruction
Series: Medical Imaging Seminar Series
Abstract: MRI acquisitions are inherently slow, necessitating the use of accelerated imaging. Simultaneous multi- slice (SMS) imaging has gained substantial interest by providing improved coverage with minimum signal- to-noise ratio (SNR) loss in accelerated MRI and has been widely integrated into large-scale projects such as Human Connectome Project. However, ultra-high accelerations are prone to noise amplification and residual aliasing artifacts, necessitating new reconstruction techniques that can successfully suppress both. In this talk, we will present recently developed techniques for regularized SMS reconstruction. We will first introduce two model-based algorithms that simultaneously reduce noise amplification and inter-leakage artifacts. Subsequently, we will concentrate on physics-guided deep learning reconstruction for SMS MRI with applications in fMRI. Finally, we will discuss an alternative way to view the multi-coil encoding operator in physics-guided DL reconstruction for improved generalizability in dynamic contrast-enhanced MRI.
Biography: Omer Burak Demirel is a PhD candidate at the University of Minnesota working with Prof. Mehmet Akçakaya. Prior to the University of Minnesota, he received the B.S. and M.S. degrees from Bilkent University, Ankara, Turkey in January 2015 and June 2017, respectively. His research interests include image processing, MRI acquisition methods, image reconstruction techniques and accelerated MRI. He is a recipient of an AHA predoctoral fellowship focusing on improved image reconstruction techniques for cardiac MRI.
Host: Krishna Nayak, email@example.com
Audiences: Everyone Is Invited
Contact: Talyia White