Deep-learning-based image reconstruction in dynamic contrast-enhanced abdominal CT: image quality and lesion detection among reconstruction strength levels.

Journal: Clinical radiology
PMID: 33879322

Abstract

AIM: To evaluate the use of deep-learning-based image reconstruction (DLIR) algorithms in dynamic contrast-enhanced computed tomography (CT) of the abdomen, and to compare the image quality and lesion conspicuity among the reconstruction strength levels.

Authors

  • T Kaga
    Department of Radiology, Gifu University, 1-1 Yanagido, Gifu 501-1194, Japan.
  • Y Noda
    Department of Radiology, Gifu University, 1-1 Yanagido, Gifu 501-1194, Japan. Electronic address: noda1031@gifu-u.ac.jp.
  • K Fujimoto
    Department of Radiology, Gifu University, 1-1 Yanagido, Gifu 501-1194, Japan.
  • T Suto
    Department of Radiology, Gifu Municipal Hospital, Gifu, Japan.
  • N Kawai
    Department of Radiology, Gifu University, 1-1 Yanagido, Gifu 501-1194, Japan.
  • T Miyoshi
    Department of Radiology Services, Gifu University Hospital, Gifu, Japan.
  • F Hyodo
    Department of Radiology, Frontier Science for Imaging, Gifu University, Gifu, Japan.
  • M Matsuo
    Department of Radiology, Gifu University, 1-1 Yanagido, Gifu 501-1194, Japan.

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