
PurposeTo develop a reconstruction pipeline that intrinsically accounts for both simultaneous multislice echo planar imaging (SMS‐EPI) reconstruction and dynamic slice‐specific Nyquist ghosting correction in time‐series data.MethodsAfter 1D slice‐group average phase correction, the separate polarity (i.e., even and odd echoes) SMS‐EPI data were unaliased by slice GeneRalized Autocalibrating Partial Parallel Acquisition. Both the slice‐unaliased even and odd echoes were jointly reconstructed using a model‐based framework, extended for SMS‐EPI reconstruction that estimates a 2D self‐phase map, corrects dynamic slice‐specific phase errors, and combines data from all coils and echoes to obtain the final images.ResultsThe percentage ghost‐to‐signal ratios (%GSRs) and its temporal variations for MB3Ry2 with a field of view/4 shift in a human brain obtained by the proposed dynamic 2D and standard 1D phase corrections were 1.37 ± 0.11 and 2.66 ± 0.16, respectively. Even with a large regularization parameter λ applied in the proposed reconstruction, the smoothing effect in fMRI activation maps was comparable to a very small Gaussian kernel size 1 × 1 × 1 mm3.ConclusionThe proposed reconstruction pipeline reduced slice‐specific phase errors in SMS‐EPI, resulting in reduction of GSR. It is applicable for functional MRI studies because the smoothing effect caused by the regularization parameter selection can be minimal in a blood‐oxygen‐level–dependent activation map.
Echo-Planar Imaging, Phantoms, Imaging, Brain, Signal Processing, Computer-Assisted, Signal-To-Noise Ratio, methods [Echo-Planar Imaging], methods [Image Processing, Computer-Assisted], Image Processing, Computer-Assisted, Humans, Artifacts, diagnostic imaging [Brain], Algorithms, ddc: ddc:610
Echo-Planar Imaging, Phantoms, Imaging, Brain, Signal Processing, Computer-Assisted, Signal-To-Noise Ratio, methods [Echo-Planar Imaging], methods [Image Processing, Computer-Assisted], Image Processing, Computer-Assisted, Humans, Artifacts, diagnostic imaging [Brain], Algorithms, ddc: ddc:610
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