HMS-CardiacMR/DRAPR

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DRAPR: Deep-Learning Radial Acceleration with Parallel Reconstruction We implemented a 3D (2D+time) convolutional neural network to suppress streaking artifacts from undersampled radial cine images. We trained the network using synthetic real-time radial cine images simulated using ECG-gated segmented Cartesian k-space data, which was acquired from 503 patients during breath-hold and at rest. Further, we implemented a prototype real-time radial sequence with acceleration rate = 12 on a 3T scanner,...