Quantitative and qualitative assessment of ultra-low-dose paranasal sinus CT using deep learning image reconstruction: a comparison with hybrid iterative reconstruction.

Journal: European radiology
Published Date: Jun 13, 2025

Abstract

OBJECTIVES: This study aimed to evaluate the quantitative and qualitative performances of ultra-low-dose computed tomography (CT) with deep learning image reconstruction (DLR) compared with those of hybrid iterative reconstruction (IR) for preoperative paranasal sinus (PNS) imaging.

Authors

  • Chuluunbaatar Otgonbaatar
    Department of Radiology, College of Medicine, Seoul National University, 03080 Seoul, Republic of Korea.
  • Dakyong Lee
    Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
  • Juneho Choi
    Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
  • Heijung Jang
    Medical Imaging AI Research Center, Canon Medical Systems Korea, Seoul, Republic of Korea.
  • Hackjoon Shim
    Connect AI Research Center, Yonsei University College of Medicine, 03772 Seoul, Republic of Korea.
  • Inseon Ryoo
    Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea. isryoo@gmail.com.
  • Hye Na Jung
    Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
  • Sangil Suh
    Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea. sangil.suh@gmail.com.

Keywords

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