A deep-learning method for the denoising of ultra-low dose chest CT in coronary artery calcium score evaluation.

Journal: Clinical radiology
Published Date: Apr 9, 2022

Abstract

AIM: To evaluate a novel deep-learning denoising method for ultra-low dose CT (ULDCT) in the assessment of coronary artery calcium score (CACS).

Authors

  • M Klug
    Division of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel; Tel Aviv University Sackler Faculty of Medicine, Tel-Aviv, Israel. Electronic address: maxiklug@hotmail.com.
  • J Shemesh
    Tel Aviv University Sackler Faculty of Medicine, Tel-Aviv, Israel; Department of Cardiology, The Grace Ballas Cardiac Research Unit, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel.
  • M Green
    Division of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel; Tel Aviv University Sackler Faculty of Medicine, Tel-Aviv, Israel.
  • A Mayer
    Division of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel; Tel Aviv University Sackler Faculty of Medicine, Tel-Aviv, Israel.
  • A Kerpel
    Division of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel; Tel Aviv University Sackler Faculty of Medicine, Tel-Aviv, Israel.
  • E Konen
    Division of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel; Tel Aviv University Sackler Faculty of Medicine, Tel-Aviv, Israel.
  • E M Marom
    Division of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel; Tel Aviv University Sackler Faculty of Medicine, Tel-Aviv, Israel.

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