Accelerated cardiac cine with spatio-coil regularized deep learning reconstruction.

Journal: Magnetic resonance in medicine
PMID:

Abstract

PURPOSE: To develop an iterative deep learning (DL) reconstruction with spatio-coil regularization and multichannel k-space data consistency for accelerated cine imaging.

Authors

  • Omer Burak Demirel
  • Fahime Ghanbari
    From the Cardiovascular Medicine Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (M.A.M., F.G., S.N., S.A., A.A., S.Y., J.R., R.N.); Division of Cardiology, Department of Medicine, Tufts Medical Center, Boston, Mass (M.S.M., E.J.R.); Division of Cardiology, Weill Cornell Medicine, New York, NY (J.K., J.W.W.); and Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC (R.M.J.).
  • Manuel Antonio Morales
    Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Patrick Pierce
    Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Scott Johnson
    Medical College of Wisconsin, Milwaukee, WI, USA.
  • Jennifer Rodriguez
    Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts.
  • Jordan Amy Street
    Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Reza Nezafat