Image Quality and Lesion Detectability of Pancreatic Phase Thin-Slice Computed Tomography Images With a Deep Learning-Based Reconstruction Algorithm.

Journal: Journal of computer assisted tomography
Published Date: Jul 22, 2023

Abstract

OBJECTIVE: To evaluate the image quality and lesion detectability of pancreatic phase thin-slice computed tomography (CT) images reconstructed with a deep learning-based reconstruction (DLR) algorithm compared with filtered-back projection (FBP) and hybrid iterative reconstruction (IR) algorithms.

Authors

  • Atsushi Nakamoto
    From the Department of Radiology, Osaka University Graduate School of Medicine.
  • Hiromitsu Onishi
    From the Department of Radiology, Osaka University Graduate School of Medicine.
  • Takahiro Tsuboyama
    From the Department of Radiology, Osaka University Graduate School of Medicine.
  • Hideyuki Fukui
    Department of Radiology, Osaka University Graduate School of Medicine.
  • Takashi Ota
    Department of Radiology, Osaka University Graduate School of Medicine.
  • Kazuya Ogawa
  • Keigo Yano
    Department of Radiology, Osaka University Graduate School of Medicine.
  • Kengo Kiso
    Department of Radiology, Osaka University Graduate School of Medicine.
  • Toru Honda
    Department of Radiology, Osaka University Graduate School of Medicine.
  • Mitsuaki Tatsumi
    Department of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Noriyuki Tomiyama
    Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.

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