Deep residual network for off-resonance artifact correction with application to pediatric body MRA with 3D cones.

Journal: Magnetic resonance in medicine
Published Date:

Abstract

PURPOSE: To enable rapid imaging with a scan time-efficient 3D cones trajectory with a deep-learning off-resonance artifact correction technique.

Authors

  • David Y Zeng
    Department of Electrical Engineering, Stanford University, Stanford, California.
  • Jamil Shaikh
    Department of Radiology, Stanford University, Stanford, California.
  • Signy Holmes
    Department of Radiology, Stanford University, Stanford, California.
  • Ryan L Brunsing
    Department of Radiology, Stanford University, Stanford, California.
  • John M Pauly
    Department of Electrical Engineering, Stanford University, Stanford, California, USA.
  • Dwight G Nishimura
    Department of Electrical Engineering, Stanford University, Stanford, California.
  • Shreyas S Vasanawala
  • Joseph Y Cheng