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Abstract #2868

Improved signal integrity in multi-echo fMRI through locally low-rank tensor regularization

Nolan K Meyer1, Daehun Kang2, MyungHo In2, John Huston2, Yunhong Shu2, Matt A Bernstein2, and Joshua D Trzasko2
1Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, United States, 2Radiology, Mayo Clinic, Rochester, MN, United States

Locally low-rank (LLR) regularization is extended to a multi-echo tensor framework for resting-state fMRI, building on previous generalizations of LLR frameworks. We demonstrate substantial increases in temporal SNR with improved robustness in mapping default mode, auditory, and sensorimotor resting-state connectivity networks in a preliminary seed-based analysis.

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