title: Undersampled linogram trajectory for fast imaging (ULTI): experiments at 3 T and 7 T.
abstract: In this study, the performance of linogram acquisition was investigated for the reconstruction of images from undersampled data using parallel imaging methods. The point spread function (PSF) of linogram sampling was analyzed for image sharpness and artifacts. Generalized auto-calibrating partially parallel acquisition was implemented for this new sampling scheme, and images were reconstructed with high acceleration rates. The results were compared with conventional radial sampling methods using simulations and phantom experiments at 3 T. Additionally, a human volunteer was scanned at 7 T. The results demonstrated that the PSF was sharper and the mean artifact power was lower for linogram sampling compared with radial sampling. Results of simulations and phantom experiments were in accord with the findings of the PSF analysis. In simulations, errors in the reconstructed images were lower for linogram sampling. In phantom experiments, fine details and sharp edges were preserved for linogram sampling, while details were blurred for radial sampling. The in vivo human study demonstrated that linogram sampling could provide high quality images of anatomy, even at high acceleration rates. Linogram sampling not only possesses the advantages of radial sampling, such as reduced sensitivity to motion and higher acceleration rates, but it also provides sharper images with fewer artifacts. Moreover, it is less prone to off-resonance artifacts compared with radial sampling. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA.
authors.forename: Ali
authors.initials: A
authors.lastname: Ersoz
authors.affiliation: Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA.|Center for Imaging Research, Medical College of Wisconsin, Milwaukee, WI, USA.
authors.forename: L
authors.initials: L
authors.lastname: Tugan Muftuler
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D059629:Signal-To-Noise Ratio
keywords: linogram; non-Cartesian; parallel imaging; radial imaging