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Parallel imaging with linear predictability takes advantage of informationpresent in multiple receive coils to accurately reconstruct the image withfewer samples. Commonly used algorithms based on linear predictability includeGRAPPA and SPIRiT. We present a sufficient condition for reconstruction basedon the direction of undersampling and the arrangement of the sensing coils.This condition is justified theoretically and examples are shown using realdata. We also propose a metric based on the fully-sampled auto-calibrationregion which can show which direction(s) of undersampling will allow for a goodquality image reconstruction.

The Dependence of Parallel Imaging with Linear Predictability on the Undersampling Direction