Deep learning-based accurate delineation of primary gross tumor volume of nasopharyngeal carcinoma on heterogeneous magnetic resonance imaging: A large-scale and multi-center study.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PMID: 36657723

Abstract

BACKGROUND AND PURPOSE: The problem of obtaining accurate primary gross tumor volume (GTVp) segmentation for nasopharyngeal carcinoma (NPC) on heterogeneous magnetic resonance imaging (MRI) images with deep learning remains unsolved. Herein, we reported a new deep-learning method than can accurately delineate GTVp for NPC on multi-center MRI scans.

Authors

  • Xiangde Luo
    School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China.
  • Wenjun Liao
    Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Yuan He
    Department of Vascular and Endovascular Surgery, Chinese PLA General Hospital, Beijing, PR China. Electronic address: heyuan@301hospital.com.cn.
  • Fan Tang
    Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China.
  • Mengwan Wu
    Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China.
  • Yuanyuan Shen
    Knowledge Engineering and Discovery Research Institute (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand.
  • Hui Huang
    Department of Biobank, The Sixth Affiliated People's Hospital of Dalian Medical University, Dalian, Liaoning, China.
  • Tao Song
    Department of Cleft Lip and Palate, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing.
  • Kang Li
    Department of Otolaryngology, Longgang Otolaryngology hospital & Shenzhen Key Laboratory of Otolaryngology, Shenzhen Institute of Otolaryngology, Shenzhen, Guangdong, China.
  • Shichuan Zhang
    Department of Radiation Oncology, Sichuan Cancer Hospital and Institute, University of Electronic Science and Technology of China, Chengdu, China.
  • Shaoting Zhang
  • Guotai Wang
    Wellcome / EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, UK.

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