Does the deep learning-based iterative reconstruction affect the measuring accuracy of bone mineral density in low-dose chest CT?

Journal: The British journal of radiology
Published Date:

Abstract

OBJECTIVES: To investigate the impacts of a deep learning-based iterative reconstruction algorithm on image quality and measuring accuracy of bone mineral density (BMD) in low-dose chest CT.

Authors

  • Hui Hao
    Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, P.R. China.
  • Jiayin Tong
    Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, P.R. China.
  • Shijie Xu
    Shanghai United Imaging Healthcare, Shanghai, China.
  • Jingyi Wang
  • Ningning Ding
    Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, P.R. China.
  • Zhe Liu
    Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
  • Wenzhe Zhao
    Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Shaanxi province, China.
  • Xin Huang
    Department of ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
  • Yanshou Li
    Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Shaanxi province, China.
  • Chao Jin
    Department of General Surgery, Tangdu Hospital, The Fourth Military Medical University, Xi'an, China.
  • Jian Yang
    Drug Discovery and Development Research Group, College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada.