Application of deep learning techniques for breath-hold, high-precision T2-weighted magnetic resonance imaging of the abdomen.

Journal: Abdominal radiology (New York)
Published Date: Nov 13, 2024

Abstract

PURPOSE: To evaluate the feasibility of a high-precision single-shot fast spin-echo (SS-FSE) sequence using the deep learning-based Precise IQ Engine (PIQE) algorithm in comparison with standard SS-FSE for T2-weighted MR imaging of the abdomen, and to compare the image quality with a multi-shot (MS)-FSE sequence using the PIQE algorithm.

Authors

  • Masahiro Tanabe
    Department of Radiology, Yamaguchi University Graduate School of Medicine, Japan. Electronic address: m-tanabe@yamaguchi-u.ac.jp.
  • Yosuke Kawano
    Department of Radiology, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-Kogushi, Ube, Yamaguchi 755-8505, Japan.
  • Kenichiro Ihara
    Department of Radiology, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-Kogushi, Ube, Yamaguchi 755-8505, Japan.
  • Keisuke Miyoshi
    Department of Radiology, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-Kogushi, Ube, Yamaguchi 755-8505, Japan.
  • Jo Ishii
    Department of Radiology, Yamaguchi University Graduate School of Medicine, Ube, Yamaguchi, Japan.
  • Kanako Nomura
    Department of Radiology, Yamaguchi University Graduate School of Medicine, Ube, Yamaguchi, Japan.
  • Ryoko Morooka
    Department of Radiology, Yamaguchi University Graduate School of Medicine, Ube, Yamaguchi, Japan.
  • Mayumi Higashi
    Department of Radiology, Yamaguchi University Graduate School of Medicine, Japan.
  • Katsuyoshi Ito
    Department of Radiology, Yamaguchi University Graduate School of Medicine, Japan.

Keywords

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