Comparison of the performances of machine learning and deep learning in improving the quality of low dose lung cancer PET images.

Journal: Japanese journal of radiology
Published Date: Jul 9, 2022

Abstract

PURPOSE: To compare the performances of machine learning (ML) and deep learning (DL) in improving the quality of low dose (LD) lung cancer PET images and the minimum counts required.

Authors

  • Ying-Hwey Nai
    Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore. mednyh@nus.edu.sg.
  • Hoi Yin Loi
    Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.
  • Sophie O'Doherty
    Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, 14 Medical Drive, #B1-01, Singapore, 117599, Singapore.
  • Teng Hwee Tan
    Radiation Oncology, National University Cancer Institute, Singapore.
  • Anthonin Reilhac
    Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore.

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