Deep Learning-Based Fully Automated Aortic Valve Leaflets and Root Measurement From Computed Tomography Images　- A Feasibility Study.

Journal: Circulation journal : official journal of the Japanese Circulation Society
Published Date: May 28, 2025

Abstract

BACKGROUND: The aim of this study was to retrain our existing deep learning-based fully automated aortic valve leaflets/root measurement algorithm, using computed tomography (CT) data for root dilatation (RD), and assess its clinical feasibility.

Authors

  • Haruo Yamauchi
    Department of Cardiovascular Surgery, Graduate School of Medicine, The University of Tokyo.
  • Gakuto Aoyama
    Research and Development Center, Canon Medical Systems Corporation.
  • Hiroyuki Tsukihara
    The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, Japan.
  • Kenji Ino
    Radiology Center, The University of Tokyo Hospital.
  • Naoki Tomii
    Faculty of Engineering, The University of Tokyo, 7-3-1, Bunkyo-ku, 113-8656, Tokyo, Japan. Electronic address: naoki_tomii@bmpe.t.u-tokyo.ac.jp.
  • Shu Takagi
    Faculty of Engineering, The University of Tokyo, 7-3-1, Bunkyo-ku, 113-8656, Tokyo, Japan.
  • Katsuhiko Fujimoto
    Research and Development Center, Canon Medical Systems Corporation.
  • Takuya Sakaguchi
    Research and Development Center, Canon Medical Systems Corporation.
  • Ichiro Sakuma
    Department of Precision Engineering, The University of Tokyo, Tokyo, Japan.
  • Minoru Ono
    Department of Cardiovascular Surgery, Graduate School of Medicine, The University of Tokyo.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals