Cardiac magnetic resonance (CMR) real-time cine, which does not require breath-holding or ECG gating, is clinically useful particularly for patients with impaired breath-hold capacity and/or arrhythmias. Spiral acquisitions, which provide high acquisition efficiency and insensitivity to motion artifacts, can require a long reconstruction time particularly for compressed-sensing or other iterative reconstruction techniques. As such they cannot provide immediate feedback to the imager. Here, we sought to develop high-resolution real-time cine imaging at 1.5 T using fast spiral acquisitions and deep learning-based rapid imaging reconstruction for both bSSFP and GRE imaging, to make high-quality and online reconstruction for cine imaging feasible.
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