A novel fast kilovoltage switching dual-energy CT with deep learning: Accuracy of CT number on virtual monochromatic imaging and iodine quantification.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PMID: 33508738

Abstract

PURPOSE: A novel fast kilovoltage switching dual-energy CT with deep learning [Deep learning based-spectral CT (DL-Spectral CT)], which generates a complete sinogram for each kilovolt using deep learning views that complement the measured views at each energy, was commercialized in 2020. The purpose of this study was to evaluate the accuracy of CT numbers in virtual monochromatic images (VMIs) and iodine quantifications at various radiation doses using DL-Spectral CT.

Authors

  • 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.
  • Takashi Shirasaka
    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.
  • Toyoyuki Kato
    Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Akihiro Nishie
    Department of Radiology, Graduate School of Medical Science, University of the Ryukyus, 1076 Kiyuna, Ginowan-shi, Okinawa, 901-2720, Japan.
  • Kousei Ishigami
    Departments of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
  • Hidetake Yabuuchi
    Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, Fukuoka, Japan.

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