Echo planar imaging (EPI) is widely used
clinically for its speed, but is known to be sensitive to non-idealities like
B0 field inhomogeneity, eddy currents, and gradient nonlinearity. Such
non-idealities are not typically managed during image reconstruction, resulting
in geometrically distorted images. Post-processing corrections (e.g., image-based
interpolation) usually tend to degrade resolution. In this work, a
comprehensive model-based reconstruction framework that prospectively and
simultaneously accounts for non-idealities in accelerated single-shot EPI
acquisitions is proposed. Sparsity regularization is also incorporated to
mitigate noise amplification. The proposed algorithm is demonstrated on
brain MRI data acquired on a compact 3T MRI system.
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