Iterative reconstruction deep learning image reconstruction: comparison of image quality and diagnostic accuracy of arterial stenosis in low-dose lower extremity CT angiography.

Journal: The British journal of radiology
PMID:

Abstract

OBJECTIVE: To compare image quality and diagnostic accuracy of arterial stenosis in low-dose lower-extremity CT angiography (CTA) between adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction (DLIR) algorithms.

Authors

  • Tingting Qu
    Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi province, PR China.
  • Yinxia Guo
    Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P.R. China.
  • Jianying Li
    CT Research Center, GE Healthcare China, Beijing 100176, China.
  • Le Cao
    Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi province, PR China.
  • Yanan Li
    Beijing Key Laboratory of Flavor Chemistry, Beijing Technology and Business University Beijing 100048 China chenht@th.btbu.edu.cn yangshaoxiang@th.btbu.edu.cn.
  • Lihong Chen
    NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100176, China.
  • Jingtao Sun
    Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China.
  • Xueni Lu
    Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P.R. China.
  • Jianxin Guo
    Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi province, PR China.