Most Cited Paper in MRM (2019)
Our paper "Scan-specific robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction: Database-free deep learning for fast imaging" was the most cited paper from 2019 in Magnetic Resonance in Medicine, a flagship journal for MRI research.