Superior objective and subjective image quality of deep learning reconstruction for low-dose abdominal CT imaging in comparison with model-based iterative reconstruction and filtered back projection.

Journal: The British journal of radiology
Published Date: Jul 1, 2021

Abstract

OBJECTIVE: This study aimed to conduct objective and subjective comparisons of image quality among abdominal computed tomography (CT) reconstructions with deep learning reconstruction (DLR) algorithms, model-based iterative reconstruction (MBIR), and filtered back projection (FBP).

Authors

  • Akio Tamura
    Department of Radiology, Iwate Medical University School of Medicine, 19-1 Uchimaru, Morioka 020-8505, Japan. Electronic address: a.akahane@gmail.com.
  • Eisuke Mukaida
    Department of Radiology, Iwate Medical University School of Medicine, Iwate, Japan.
  • Yoshitaka Ota
    Division of Central Radiology, Iwate Medical University Hospital, Iwate, Japan.
  • Masayoshi Kamata
    Iwate Medical University Hospital, 19-1 Uchimaru, Morioka 020-8505, Japan. Electronic address: kamataaoi@yahoo.co.jp.
  • Shun Abe
    Division of Central Radiology, Iwate Medical University Hospital, Iwate, Japan.
  • Kunihiro Yoshioka
    Department of Radiology, Iwate Medical University School of Medicine, Iwate, Japan.

Keywords

External Resources

Popular Topics
Recent Journals