This paper proposes an accelerated MR reconstruction method for parallel imaging from uniformly undersampled k-space data by learning scan-specific GRAPPA kernel using the long short-term memory network (LSTM). In particular, the meta-leaner LSTM is redesigned to quickly estimate the GRAPPA kernel for each k-space from its auto-calibration signals (ACS). The proposed method shows improved reconstruction performance with minimum error.
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