Impact of deep learning-based image reconstruction on image quality compared with adaptive statistical iterative reconstruction-Veo in renal and adrenal computed tomography.

Journal: Journal of X-ray science and technology
Published Date:

Abstract

OBJECTIVE: To evaluate image quality of deep learning-based image reconstruction (DLIR) in contrast-enhanced renal and adrenal computed tomography (CT) compared with adaptive statistical iterative reconstruction-Veo (ASiR-V).

Authors

  • Yifan Bie
    Department of Radiology, the Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China.
  • Shuo Yang
    Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China.
  • Xingchao Li
    Department of Radiology, the Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China.
  • Kun Zhao
    Frontier Science Center for Synthetic Biology, Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University Tianjin 300072 P. R. China kunzhao@tju.edu.cn.
  • Changlei Zhang
    Department of Radiology, the Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China.
  • Hai Zhong
    The Second Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan 250000, China. Electronic address: 18753107255@163.com.