In the presented work, a compressed sensing approach is introduced to calibrate k-t space parallel imaging reconstruction. This approach removes the need for calibration data and improves image reconstruction using data sparsity associated with narrow bandwidth of physiological motion signals. The new approach is used to enable real-time neonatal chest MRI. It is experimentally demonstrated that real-time imaging can provide high-quality cardiac and pulmonary images for improved clinical diagnosis in premature babies.
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