Fully Automated Delineation of Gross Tumor Volume for Head and Neck Cancer on PET-CT Using Deep Learning: A Dual-Center Study.

Journal: Contrast media & molecular imaging
Published Date:

Abstract

PURPOSE: In this study, we proposed an automated deep learning (DL) method for head and neck cancer (HNC) gross tumor volume (GTV) contouring on positron emission tomography-computed tomography (PET-CT) images.

Authors

  • Bin Huang
    Department of Clinical Laboratory, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
  • Zhewei Chen
    School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
  • Po-Man Wu
    Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong.
  • Yufeng Ye
    Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, China.
  • Shi-Ting Feng
    Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
  • Ching-Yee Oliver Wong
    University of Southern California, Los Angeles, USA.
  • Liyun Zheng
    School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
  • Yong Liu
    Department of Critical care medicine, Shenzhen Hospital, Southern Medical University, Guangdong, Shenzhen, China.
  • Tianfu Wang
    School of Biomedical Engineering, Shenzhen University Health Sciences Center, Shenzhen, Guangdong 518060, P.R.China.
  • Qiaoliang Li
    School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
  • Bingsheng Huang
    School of Biomedical Engineering, Shenzhen University Health Sciences Center, Shenzhen, Guangdong 518060, P.R.China.