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Coil‐to‐coil physiological noise correlations and their impact on functional MRI time‐series signal‐to‐noise ratio
Author(s) -
Triantafyllou Christina,
Polimeni Jonathan R.,
Keil Boris,
Wald Lawrence L.
Publication year - 2016
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26041
Subject(s) - noise (video) , signal (programming language) , series (stratigraphy) , signal to noise ratio (imaging) , covariance , covariance matrix , nuclear magnetic resonance , physics , computer science , biological system , algorithm , mathematics , statistics , artificial intelligence , optics , paleontology , image (mathematics) , biology , programming language
Purpose Physiological nuisance fluctuations (“physiological noise”) are a major contribution to the time‐series signal‐to‐noise ratio (tSNR) of functional imaging. While thermal noise correlations between array coil elements have a well‐characterized effect on the image Signal to Noise Ratio (SNR 0 ), the element‐to‐element covariance matrix of the time‐series fluctuations has not yet been analyzed. We examine this effect with a goal of ultimately improving the combination of multichannel array data. Theory and Methods We extend the theoretical relationship between tSNR and SNR 0 to include a time‐series noise covariance matrix Ψ t , distinct from the thermal noise covariance matrix Ψ 0 , and compare its structure to Ψ 0 and the signal coupling matrix SS H formed from the signal intensity vectors S . Results Inclusion of the measured time‐series noise covariance matrix into the model relating tSNR and SNR 0 improves the fit of experimental multichannel data and is shown to be distinct from Ψ 0 or SS H . Conclusion Time‐series noise covariances in array coils are found to differ from Ψ 0 and more surprisingly, from the signal coupling matrix SS H . Correct characterization of the time‐series noise has implications for the analysis of time‐series data and for improving the coil element combination process. Magn Reson Med 76:1708–1719, 2016. © 2016 International Society for Magnetic Resonance in Medicine