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Abstract #3484

Model-based PSF-encoded multi-shot EPI reconstruction with low-rank constraints

Nolan K Meyer1,2, Myung-Ho In2, Daehun Kang2, Yunhong Shu2, John Huston III2, Matt A Bernstein2, and Joshua D Trzasko2
1Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, United States, 2Department of Radiology, Mayo Clinic, Rochester, MN, United States


Echo planar imaging (EPI) is commonly used clinically for its speed, but is sensitive to non-idealities including system field inhomogeneity and subject-specific susceptibility effects. Multi-shot techniques encoding an auxiliary point-spread-function (PSF)-encoding dimension provide robustness to off-resonance effects, with demonstrated potential for diffusion and anatomic applications, but incur scan time penalties motivating acquisition and reconstruction strategies to increase acceleration. This work proposes a comprehensive model-based iterative reconstruction framework for anatomic PSF-encoded EPI scans incorporating low-rank constraints, directly reconstructing undistorted images from undersampled data. Advantages are demonstrated using brain MRI data acquired on a compact 3T MRI system.

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