Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study.

Abstract

Authors

• Akiyo Fukutomi
  Center for Radiology and Radiation Oncology, Kobe University Hospital, Kobe, Japan.
• Keitaro Sofue
  Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe City, Hyogo 650-0017, Japan.
• Eisuke Ueshima
  Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
• Noriyuki Negi
  Center for Radiology and Radiation Oncology, Kobe University Hospital, Kobe, Japan.
• Yoshiko Ueno
  Department of Radiology, Royal Victoria Hospital, McGill University Health Centre, 1001 Decarie Blvd, Montreal, QC, H4A 3J1, Canada.
• Yushi Tsujita
  Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
• Shinji Yabe
  Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
• Takeru Yamaguchi
  Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
• Ryuji Shimada
  Center for Radiology and Radiation Oncology, Kobe University Hospital, Kobe, Japan.
• Akiko Kusaka
  Center for Radiology and Radiation Oncology, Kobe University Hospital, Kobe, Japan.
• Masatoshi Hori
  Department of Radiology, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan.
• Takamichi Murakami
  Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe City, Hyogo 650-0017, Japan.

Keywords

External Resources