Enhancing the X-Ray Differential Phase Contrast Image Quality With Deep Learning Technique.

Journal: IEEE transactions on bio-medical engineering
Published Date: May 21, 2021

Abstract

OBJECTIVE: The purpose of this work is to investigate the feasibility of using deep convolutional neural network (CNN) to improve the image quality of a grating-based X-ray differential phase contrast imaging (XPCI) system.

Authors

  • Yongshuai Ge
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
  • Peizhen Liu
  • Yifan Ni
  • Jianwei Chen
    College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China.
  • Jiecheng Yang
  • Ting Su
    Changsha Jingyi Pharmaceutical Technology Co., Ltd, Changsha, Hunan Province, China.
  • Huitao Zhang
  • Jinchuan Guo
  • Hairong Zheng
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.
  • Zhicheng Li
    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
  • Dong Liang
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.

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