In this study, a spatio-temporal U-Net was developed for efficient and accurate T1 and T2 quantifications from multislice MR Fingerprinting acquisitions. Our preliminary results demonstrate that the proposed method outperforms the standard template matching method and deep learning methods in the literature, enabling higher multislice factors for MR Fingerprinting.
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