Super-resolution deep learning reconstruction for improved quality of myocardial CT late enhancement.

Journal: Japanese journal of radiology
Published Date: Mar 12, 2025

Abstract

PURPOSE: Myocardial computed tomography (CT) late enhancement (LE) allows assessment of myocardial scarring. Super-resolution deep learning image reconstruction (SR-DLR) trained on data acquired from ultra-high-resolution CT may improve image quality for CT-LE. Therefore, this study investigated image noise and image quality with SR-DLR compared with conventional DLR (C-DLR) and hybrid iterative reconstruction (hybrid IR).

Authors

  • Masafumi Takafuji
    Department of Radiology, Mie University School of Medicine, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.
  • Kakuya Kitagawa
    Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.
  • Sachio Mizutani
    Department of Radiology, Matsusaka Municipal Hospital, Matsusaka, Japan.
  • Akane Hamaguchi
    Department of Radiology, Matsusaka Municipal Hospital, Matsusaka, Japan.
  • Ryosuke Kisou
    Department of Radiology, Matsusaka Municipal Hospital, Matsusaka, Japan.
  • Kenji Sasaki
    Department of Radiology, Matsusaka Municipal Hospital, Matsusaka, Japan.
  • Yuto Funaki
    Department of Radiology, Matsusaka Municipal Hospital, Matsusaka, Japan.
  • Kotaro Iio
    Department of Cardiology, Matsusaka Municipal Hospital, Matsusaka, Japan.
  • Kazuhide Ichikawa
    Department of Cardiology, Matsusaka Municipal Hospital, Matsusaka, Japan.
  • Daisuke Izumi
    Department of Cardiology, Matsusaka Municipal Hospital, Matsusaka, Japan.
  • Shiko Okabe
    Department of Radiology, Mie University Graduate School of Medicine, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.
  • Motonori Nagata
    Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.
  • Hajime Sakuma
    Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.

Keywords

External Resources

Popular Topics
Recent Journals