This abstract presents a new approach to compressed sensing cardiac MRI, which enables free-breathing whole heart coverage cine imaging within 30 seconds. Using a phased array coil, data was acquired continuously along Cartesian sampling trajectories using a lookup table without ECG gating. Each slice was continuously sampled for a fixed period of time, before the slice-selective RF excitation pulse switch to the next slice. In reconstruction, the approach jointly updates coil sensitivity maps and images, integrated with compressed sensing. In post-processing, virtual ECG is calculated based on unsupervised machine learning.
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