Parallel imaging and convolutional neural network combined fast MR image reconstruction: Applications in low-latency accelerated real-time imaging.

Journal: Medical physics
Published Date: Jun 17, 2019

Abstract

PURPOSE: To develop and evaluate a parallel imaging and convolutional neural network combined image reconstruction framework for low-latency and high-quality accelerated real-time MR imaging.

Authors

  • Ziwu Zhou
    Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
  • Fei Han
    Organ Transplantation Research Institution, Division of Kidney Transplantation, Department of Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Vahid Ghodrati
    Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
  • Yu Gao
    Department of Radiology Center, The First Affiliated Hospital of Xinxiang Medical University, Xin Xiang, China.
  • Wotao Yin
    Department of Mathematics, University of California, Los Angeles, CA, USA.
  • Yingli Yang
    Biomedical Physics Inter-Departmental Graduate Program, University of California, Los Angeles, CA, USA.
  • Peng Hu
    The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Keywords

External Resources

Popular Topics
Recent Journals