Detection of Vertebral Mass and Diagnosis of Spinal Cord Compression in Computed Tomography With Deep Learning Reconstruction: Comparison With Hybrid Iterative Reconstruction.

Journal: Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
PMID: 37795610

Abstract

PURPOSE: To compare the impact of deep learning reconstruction (DLR) and hybrid-iterative reconstruction (hybrid-IR) on vertebral mass depiction, detection, and diagnosis of spinal cord compression on computed tomography (CT).

Authors

  • Nana Fujita
    Department of Radiology, The University of Tokyo Hospital, Bunkyo-ku, Tokyo, Japan.
  • Koichiro Yasaka
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.
  • Yusuke Watanabe
    From the Departments of Diagnostic and Interventional Radiology (D.U., A.Y., S.L.W., H. Tatekawa, H. Takita, T.H., A.S., Y.M.), Neurosurgery (T. Ichinose, H.A., Y.W., T.G.), and Medical Statistics (D.K.), Graduate School of Medicine, Osaka City University, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan; and Department of Radiology, Osaka City University Hospital, 1-5-7 Asahi-machi, Abeno-ku, Osaka, 545-8586, Japan (Y.K., T. Ichida).
  • Naomasa Okimoto
  • Mao Konishiike
    Department of Radiology, The University of Tokyo Hospital, Bunkyo-ku, Tokyo, Japan.
  • Osamu Abe
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.

Keywords

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