Abstract #1097

SpinalCompCor: PCA-based denoising for spinal cord fMRI

Kimberly J. Hemmerling^1,2, Mark A. Hoggarth², Todd Parrish³, Robert L. Barry^4,5,6, and Molly G. Bright^1,2

¹Biomedical Engineering, Northwestern University, Evanston, IL, United States, ²Physical Therapy & Human Movement Sciences, Northwestern University, Chicago, IL, United States, ³Department of Radiology, Northwestern University, Chicago, IL, United States, ⁴Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States, ⁵Department of Radiology, Harvard Medical School, Boston, MA, United States, ⁶Harvard–Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, United States

Synopsis

SpinalCompCor is a denoising technique in which principal component (PC) analysis is performed in a region outside of the spinal cord to define nuisance regressors. Temporal SNR was greater when PC regressors were included in the general linear model, compared to when they were regressed out of the data prior to motion correction. In comparing models that vary the number of PC regressors, models with multiple PCs generally performed better than those with single PCs. SpinalCompCor is a promising technique for spinal cord fMRI denoising.

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