GRASP is a valuable tool to perform free-breathing dynamic contrast-enhanced (DCE) MRI with high spatial and temporal resolution. However, the 4D reconstruction algorithm is iterative and relatively long for clinical studies. In this work, we present a spatiotemporal deep learning approach to significantly reduce the reconstruction time without affecting image quality.
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