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Abstract #1346

Improved multi-shot EPI ghost correction for high gradient strength diffusion MRI using Structured Low-Rank Modeling k-space reconstruction

Gabriel Ramos-Llordén1, Rodrigo A. Lobos2, Tae Hyung Kim1, Qiyuan Tian1, Slimane Tounetki1, Thomas Witzel3, Boris Keil4, Anatasia Yendiki1, Berkin Bilgic1,5, Justin P. Haldar2, and Susie Huang1,5
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Masachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, 2Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, 3Q Bio Inc, San Carlos, CA, United States, 4Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Sciences, Giessen, Germany, 5Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States

Multi-shot EPI diffusion MRI acquired using high diffusion-encoding gradient strengths suffers from severe ghosting artifacts, which can bias and confound the estimation of diffusion microstructural MRI measures at high b-values. In this work, we show that conventional EPI ghost correction techniques fall short in ghosting reduction when high diffusion-encoding gradient strengths ~250mT/m are used, and that advanced reconstruction algorithms based on structured low-rank matrix modeling can substantially reduce ghosting without introducing additional artifacts.

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