Real-time intraoperative glioma diagnosis using fluorescence imaging and deep convolutional neural networks.

Journal: European journal of nuclear medicine and molecular imaging
Published Date: Apr 27, 2021

Abstract

PURPOSE: Surgery is the predominant treatment modality of human glioma but suffers difficulty on clearly identifying tumor boundaries in clinic. Conventional practice involves neurosurgeon's visual evaluation and intraoperative histological examination of dissected tissues using frozen section, which is time-consuming and complex. The aim of this study was to develop fluorescent imaging coupled with artificial intelligence technique to quickly and accurately determine glioma in real-time during surgery.

Authors

  • Biluo Shen
    CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing, 100190, China.
  • Zhe Zhang
    Department of Urology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China.
  • Xiaojing Shi
  • Caiguang Cao
    CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing, 100190, China.
  • Zeyu Zhang
    Department of Rehabilitation Medicine, The First Affiliated Hospital of Shenzhen University, The Second People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
  • Zhenhua Hu
  • Nan Ji
    Xiamen Huli Center For Disease Control and Prevention, Xiamen, Fujian 361000, P.R. China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

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