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Abstract #2703

Locally low-rank denoising preserves statistical confidence in task-based functional activation under scan duration reduction

Nolan Meyer1, Norbert G Campeau2, David F Black2, Kirk M Welker2, Erin Gray2, 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

Functional MRI activation maps derived from locally low-rank (LLR) denoising of complex-valued time series echo planar imaging (EPI) data were compared to those obtained from conventional non-denoised data for a six-block verbal task-based fMRI exam obtained in five healthy subjects, as data were retrospectively truncated block-by-block. The LLR-denoised fMRI activation maps exhibited superior performance as timeframes were removed in sets of blocks, with acceptable statistical confidence overall in localizing verbal activation following retrospective truncation of scan data. LLR denoising significantly increases temporal signal to noise ratio of timecourse data, a performance advantage which remains stable as timeframes are removed.

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