CT based automatic clinical target volume delineation using a dense-fully connected convolution network for cervical Cancer radiation therapy.

Journal: BMC cancer
Published Date: Mar 8, 2021

Abstract

BACKGROUND: It is very important to accurately delineate the CTV on the patient's three-dimensional CT image in the radiotherapy process. Limited to the scarcity of clinical samples and the difficulty of automatic delineation, the research of automatic delineation of cervical cancer CTV based on CT images for new patients is slow. This study aimed to assess the value of Dense-Fully Connected Convolution Network (Dense V-Net) in predicting Clinical Target Volume (CTV) pre-delineation in cervical cancer patients for radiotherapy.

Authors

  • Zhongjian Ju
    Department of Radiation Oncology, People's Liberation Army General Hospital, Beijing 100853, P.R.China.
  • Wen Guo
    School of Physics Science and Technology, Wuhan University, Wuhan, China.
  • Shanshan Gu
    Department of Radiation Oncology, People's Liberation Army General Hospital, Beijing 100853, P.R.China.
  • Jin Zhou
  • Wei Yang
    Key Laboratory of Structure-Based Drug Design and Discovery (Shenyang Pharmaceutical University), Ministry of Education, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Wenhua Road 103, Shenyang 110016, PR China. Electronic address: 421063202@qq.com.
  • Xiaohu Cong
    Radiotherapy Department, First Medical Center, General Hospital of Chinese People's Liberation Army, Beijing, 100853.
  • Xiangkun Dai
    Department of Radiotherapy, First Medical Center of PLA General Hospital, BeiJing 100853, P.R.China.
  • Hong Quan
    School of Physics Science and Technology, Wuhan University, Wuhan 430072, P.R.China.
  • Jie Liu
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.
  • Baolin Qu
    Department of Radiotherapy, First Medical Center of PLA General Hospital, BeiJing 100853, P.R.China.
  • Guocai Liu
    College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China.

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