Rapid 3D breath-hold MR cholangiopancreatography using deep learning-constrained compressed sensing reconstruction.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To compare the image quality of three-dimensional breath-hold magnetic resonance cholangiopancreatography with deep learning-based compressed sensing reconstruction (3D DL-CS-MRCP) to those of 3D breath-hold MRCP with compressed sensing (3D CS-MRCP), 3D breath-hold MRCP with gradient and spin-echo (3D GRASE-MRCP) and conventional 2D single-shot breath-hold MRCP (2D MRCP).

Authors

  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Wanlin Peng
    Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
  • Yi Xiao
    Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China.
  • Yue Ming
    Beijing Key Laboratory of Work Safety and Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China.
  • Kehang Ma
    Department of Radiology, West China Hospital of Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
  • Sixian Hu
    Department of Radiology, West China Hospital of Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
  • Wen Zeng
    Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
  • Lingming Zeng
    Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
  • Zejun Liang
    Department of Radiology, West China Hospital of Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
  • Xiaoyong Zhang
    Clinical Science, Philips Healthcare, Chengdu, China.
  • Chunchao Xia
    Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
  • Zhenlin Li
    Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, P.R.China.