Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.

Journal: Journal of applied clinical medical physics
Published Date: Jun 23, 2021

Abstract

PURPOSE: In an ultrahigh-resolution CT (U-HRCT), deep learning-based reconstruction (DLR) is expected to drastically reduce image noise without degrading spatial resolution. We assessed a new algorithm's effect on image quality at different radiation doses assuming an abdominal CT protocol.

Authors

  • Takashi Shirasaka
    Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Tsukasa Kojima
    Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan; Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan. Electronic address: tukasa@med.kyushu-u.ac.jp.
  • Yoshinori Funama
    Department of Medical Physics, Faculty of Life Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto 860-8556, Japan (Y.F.).
  • Yuki Sakai
    Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Masatoshi Kondo
    Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Ryoji Mikayama
    Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Hiroshi Hamasaki
    Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Toyoyuki Kato
    Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Yasuhiro Ushijima
    Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
  • Yoshiki Asayama
    Department of Advanced Imaging and Interventional Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
  • Akihiro Nishie
    Department of Radiology, Graduate School of Medical Science, University of the Ryukyus, 1076 Kiyuna, Ginowan-shi, Okinawa, 901-2720, Japan.

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