Improving detection accuracy of perfusion defect in standard dose SPECT-myocardial perfusion imaging by deep-learning denoising.

Journal: Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
PMID: 34282538

Abstract

BACKGROUND: We previously developed a deep-learning (DL) network for image denoising in SPECT-myocardial perfusion imaging (MPI). Here we investigate whether this DL network can be utilized for improving detection of perfusion defects in standard-dose clinical acquisitions.

Authors

  • Junchi Liu
    Medical Imaging Research Center & Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, 60616, USA.
  • Yongyi Yang
    Medical Imaging Research Center, Illinois Institute of Technology, 3440 S. Dearborn St., Suite 100, Chicago, IL, 60616, USA.
  • Miles N Wernick
    ADM Diagnostics, Northbrook, IL, USA.
  • P Hendrik Pretorius
  • Piotr J Slomka
    Department of Imaging, Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California Piotr.Slomka@cshs.org.
  • Michael A King

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