Parametric image generation with the uEXPLORER total-body PET/CT system through deep learning.

Journal: European journal of nuclear medicine and molecular imaging
Published Date: Mar 21, 2022

Abstract

PURPOSE: Total-body dynamic positron emission tomography/computed tomography (PET/CT) provides much sensitivity for clinical imaging and research, bringing new opportunities and challenges regarding the generation of total-body parametric images. This study investigated parametric [Formula: see text] images directly generated from static PET images without an image-derived input function on a 2-m total-body PET/CT scanner (uEXPLORER) using a deep learning model to significantly reduce the dynamic scanning time and improve patient comfort.

Authors

  • Zhenxing Huang
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.
  • Yaping Wu
    Department of Imaging, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Fangfang Fu
    Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, Henan, China.
  • Nan Meng
  • Fengyun Gu
    Central Research Institute, United Imaging Healthcare Group, Shanghai, 201807, China.
  • Qi Wu
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Yun Zhou
    MOE Key Lab of Environmental and Occupational Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, China.
  • Yongfeng Yang
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.
  • Xin Liu
    Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences, Weifang, Shandong, China.
  • Hairong Zheng
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.
  • Dong Liang
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.
  • Meiyun Wang
  • Zhanli Hu
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.

Keywords

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