Accelerating T mapping of the brain by integrating deep learning priors with low-rank and sparse modeling.

Journal: Magnetic resonance in medicine
Published Date:

Abstract

PURPOSE: To accelerate T mapping with highly sparse sampling by integrating deep learning image priors with low-rank and sparse modeling.

Authors

  • Ziyu Meng
    Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
  • Rong Guo
    Department of Biochemistry and Molecular Biology, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, 610041, China. Electronic address: rongguo@scu.edu.cn.
  • Yudu Li
    Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
  • Yue Guan
    Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Tianyao Wang
    Department of Radiology, the Fifth People's Hospital of Shanghai, Fudan University, Shanghai, China.
  • Yibo Zhao
    Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
  • Brad Sutton
    Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
  • Yao Li
    Center of Robotics and Intelligent Machine, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Science, No. 266 Fangzhen Road, Beibei District, Chongqing, 400714, China.
  • Zhi-Pei Liang
    Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.