Automatic segmentation of lung tumors on CT images based on a 2D & 3D hybrid convolutional neural network.

Journal: The British journal of radiology
Published Date: Aug 4, 2021

Abstract

OBJECTIVE: A stable and accurate automatic tumor delineation method has been developed to facilitate the intelligent design of lung cancer radiotherapy process. The purpose of this paper is to introduce an automatic tumor segmentation network for lung cancer on CT images based on deep learning.

Authors

  • Wutian Gan
    Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Hao Wang
    Department of Cardiology, Second Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Hengle Gu
    Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Yanhua Duan
    Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Yan Shao
    Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Hua Chen
    Management College, Beijing Union University, Beijing, China.
  • Aihui Feng
    Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Ying Huang
    Department of Otolaryngology, Head and Neck Surgery, Affiliated Hospital of Southwest Medical University Luzhou, Sichuan, China.
  • Xiaolong Fu
    Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Yanchen Ying
    Department of Radiation Physics, Zhejiang Cancer Hospital, University of Chinese Academy of Sciences, Zhejiang, China.
  • Hong Quan
    School of Physics Science and Technology, Wuhan University, Wuhan 430072, P.R.China.
  • Zhiyong Xu

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