Abolfazl Mehranian1, Hamidreza Saligheh Rad1, 2, Mohammadreza Ay1, 2, Arman Rahmim3
1Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences of Medical Sciences, Tehran,Iran, Tehran, Iran; 2Research Center for Science and Technology in Medcine, Imam Hospital, Tehran, Iran; 3Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
The compressive sensing (CS) of spirally encoded MR acquisitions makes it possible to significantly reduce the scanning time in 3D MR imaging techniques. In this work, we studied an efficient primal-dual algorithm for 3D total variation (TV) and Huber-based compressed MR image reconstruction. We tailored this algorithm for TV and Huber regularizations in 3D and made use of a stack of variable-density spiral trajectories for 80% k-space undersampling. In a volumetric cardiac dataset, it was demonstrated that the derived algorithm objectively outperforms several state-of-the-art algorithms and thus can have promising clinical implications in fast MR imaging.