A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date: May 4, 2021

Abstract

BACKGROUND AND PURPOSE: Delineating organs at risk (OARs) on computed tomography (CT) images is an essential step in radiation therapy; however, it is notoriously time-consuming and prone to inter-observer variation. Herein, we report a deep learning-based automatic segmentation (AS) algorithm (WBNet) that can accurately and efficiently delineate all major OARs in the entire body directly on CT scans.

Authors

  • Xuming Chen
    Department of Radiation Oncology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Shanlin Sun
    DeepVoxel Inc., Irvine, USA; Department of Computer Science, University of California, Irvine, USA.
  • Narisu Bai
    DeepVoxel Inc., Irvine, USA.
  • Kun Han
    DeepVoxel Inc., Irvine, USA.
  • Qianqian Liu
    The First Clinical Medical College, Lanzhou University, Lanzhou, China.
  • Shengyu Yao
    Department of Radiation Oncology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Hao Tang
    Department of Urology, Eastern Theater General Hospital of Chinese People's Liberation Army, Nanjing， Jiangsu 210000, China.
  • Chupeng Zhang
    DeepVoxel Inc., Irvine, USA.
  • Zhipeng Lu
    DeepVoxel Inc., Irvine, USA.
  • Qian Huang
    Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
  • Guoqi Zhao
    Department of Radiation Oncology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Yi Xu
    School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
  • Tingfeng Chen
    Department of Radiation Oncology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Xiaohui Xie
    Department of Computer Science, University of California, Irvine, CA, USA.
  • Yong Liu
    Department of Critical care medicine, Shenzhen Hospital, Southern Medical University, Guangdong, Shenzhen, China.

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