As an advanced medical imaging technology, magnetic resonance imaging (MRI) has great advantages and application potentials in medical clinical diagnosis. However, since the long scanning time and the artifacts caused by patient movements, the imaging results are always not satisfactory. Therefore, accelerating MRI and improving the imaging quality are the key problems. In this work, we propose a novel deep network that combines the U-net architecture with non-local attention blocks for MRI reconstruction. We employ the U-net to construct the basic network. The non-local attention is exploited...
