Here we use an extended model describing the impact of smoothing on tSNR to characterize 2D-Multiband-EPI and 3D-EPI time-series, in vivo, in terms of their SNR, tSNR, intrinsic smoothness, as well as the level of physiological noise (λ) and its degree of spatial correlation. The model fitting suggested that higher intrinsic smoothness and physiological noise levels in 3D-EPI can explain why spatial smoothing is less beneficial than for 2D-MB-EPI, as previously observed. Furthermore, the model captured the facts that the level of physiological noise is higher for 3D-EPI than 2D-MB-EPI and that λ increases with the number of acquired segments.
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