Usefulness of compressed sensing coronary magnetic resonance angiography with deep learning reconstruction.

Journal: Japanese journal of radiology
Published Date: Jul 7, 2025

Abstract

PURPOSE: Coronary magnetic resonance angiography (CMRA) scans are generally time-consuming. CMRA with compressed sensing (CS) and artificial intelligence (AI) (CSAI CMRA) is expected to shorten the imaging time while maintaining image quality. This study aimed to evaluate the usefulness of CS and AI for non-contrast CMRA.

Authors

  • Kohei Tabo
    Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, Japan. zinpan1219@gmail.com.
  • Tomoyuki Kido
    Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan.
  • Megumi Matsuda
    Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, Japan.
  • Shota Tokui
    Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, Japan.
  • Genki Mizogami
    Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, Japan.
  • Yoshihiro Takimoto
    Ehime University Hospital, Shitsukawa, Toon, Ehime, Japan.
  • Masaki Matsumoto
    Ehime University Hospital, Shitsukawa, Toon, Ehime, Japan.
  • Mitsuharu Miyoshi
    GE HealthCare, Hino, Tokyo, Japan.
  • Teruhito Kido
    Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan.

Keywords

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