CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spatio-temporal convolutions.Cardiac CINE magnetic resonance imaging is the gold-standard for the assessment of cardiac function.  In this work, we propose a novel 4D (3D + time) deep learning-based reconstruction network, termed 4D CINENet, for prospectively undersampled 3D Cartesian CINE imaging.  CINENet is based on (3 + 1)D complex-valued spatio-temporal convolutions and multi-coil data processing.  We trained and evaluated the proposed CINENet on in-house acquired 3D CINE data of 20 healthy subjects and 15 patients with suspected cardiovascular disease.  The proposed CINENet network outperforms iterative reconstructions in visual image quality and contrast (+ 67% improvement). 
CINENet
CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spatio-temporal convolutions.Cardiac CINE magnetic resonance imaging is the gold-standard for the assessment of cardiac function. 
deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spatio-temporal convolutions