Clinical evaluation of deep learning-enhanced lymphoma pet imaging with accelerated acquisition.

Journal: Journal of applied clinical medical physics
Published Date:

Abstract

PURPOSE: This study aims to evaluate the clinical performance of a deep learning (DL)-enhanced two-fold accelerated PET imaging method in patients with lymphoma.

Authors

  • Xu Li
    Department of Critical Care Medicine, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
  • Boyang Pan
    RadioDynamic Healthcare, Shanghai, People's Republic of China.
  • Congxia Chen
    Department of Nuclear Medicine, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
  • Dongyue Yan
    Department of Nuclear Medicine, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
  • Zhenglin Pan
    RadioDynamic Healthcare, Shanghai, China.
  • Tao Feng
    School of Pharmacy, Anhui University of Chinese Medicine, Anhui Key Laboratory of Modern Chinese Materia Medica Hefei 230012 People's Republic of China tfeng@mail.scuec.edu.cn wanggk@ahtcm.edu.cn.
  • Hui Liu
    Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Nan-Jie Gong
    Vector Lab for Intelligent Medical Imaging and Neural Engineering, International Innovation Center of Tsinghua University, Shanghai, China.
  • Fugeng Liu
    Department of Nuclear Medicine, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.