Deep learning image reconstruction algorithm for abdominal multidetector CT at different tube voltages: assessment of image quality and radiation dose in a phantom study.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To compare the image quality and radiation dose of a deep learning image reconstruction (DLIR) algorithm compared with iterative reconstruction (IR) and filtered back projection (FBP) at different tube voltages and tube currents.

Authors

  • Hye Joo Park
    Department of Radiology, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, 170 Jomaru-ro, Bucheon, 14584, Republic of Korea.
  • Seo-Youn Choi
    Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon.
  • Ji Eun Lee
    Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon.
  • Sanghyeok Lim
    Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon.
  • Min Hee Lee
    Division of Environmental Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongsangbuk-do, 37673, Republic of Korea.
  • Boem Ha Yi
    Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon.
  • Jang Gyu Cha
    Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon.
  • Ji Hye Min
    Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul,, 06351, Republic of Korea.
  • Bora Lee
    Department of Biochemistry, Chonnam National University Medical School, Hwasun, Republic of Korea.
  • Yunsub Jung
    CT Research Team, GE Healthcare Korea, Seoul, Korea.