Reducing motion artifacts in the aorta: super-resolution deep learning reconstruction with motion reduction algorithm.

Journal: Japanese journal of radiology
Published Date: Aug 9, 2025

Abstract

PURPOSE: To assess the efficacy of super-resolution deep learning reconstruction (SR-DLR) with motion reduction algorithm (SR-DLR-M) in mitigating aorta motion artifacts compared to SR-DLR and deep learning reconstruction with motion reduction algorithm (DLR-M).

Authors

  • Koichiro Yasaka
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.
  • Rin Tsujimoto
    Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-8655, Japan.
  • Rintaro Miyo
    Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
  • Osamu Abe
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.

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