Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning.

Journal: European journal of nuclear medicine and molecular imaging
Published Date: Sep 6, 2023

Abstract

PURPOSE: The axial field of view (AFOV) of a positron emission tomography (PET) scanner greatly affects the quality of PET images. Although a total-body PET scanner (uEXPLORER) with a large AFOV is more sensitive, it is more expensive and difficult to widely use. Therefore, we attempt to utilize high-quality images generated by uEXPLORER to optimize the quality of images from short-axis PET scanners through deep learning technology while controlling costs.

Authors

  • Zhenxing Huang
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.
  • Wenbo Li
    Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Xianhu Hydrogen Valley, Foshan 528200, China.
  • Yaping Wu
    Department of Imaging, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Nannan Guo
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
  • Lin Yang
    National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
  • Na Zhang
    Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing, China.
  • Zhifeng Pang
    School of Mathematics and Statistics, Henan University, Kaifeng, 475004, China.
  • Yongfeng Yang
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 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.
  • Yue Shang
    Department of Endocrinology, Shenzhen Children's Hospital, No. 7019, Yitian Road, Futian District, Shenzhen, 518038, Guangdong Province, People's Republic of 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.

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