Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
Published Date: Aug 1, 2020

Abstract

BACKGROUND: Convolutional neural networks (CNNs) have been extensively applied to two-dimensional (2D) medical image segmentation, yielding excellent performance. However, their application to three-dimensional (3D) nodule segmentation remains a challenge.

Authors

  • Xianling Dong
    Present Address: Department of Biomedical Engineering, Chengde Medical University, Chengde City, Hebei Province, China.
  • Shiqi Xu
    Department of Electrical & System Engineering, Washington University in St. Louis.
  • Yanli Liu
    Baodi Clinical College, Tianjin Medical University, 8 Guangchuan Road, Tianjin, 301800, China.
  • Aihui Wang
    Department of Nuclear Medicine, Affiliated Hospital, Chengde Medical University, Chengde City, China.
  • M Iqbal Saripan
    Faculty of Engineering, Universiti Putra Malaysia, Serdang, Malaysia.
  • Li Li
    Department of Gastric Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
  • Xiaolei Zhang
    College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, 310058, China; Key Laboratory of on Site Processing Equipment for Agricultural Products, Ministry of Agriculture and Rural Affairs, China.
  • Lijun Lu
    School of Biomedical Engineering, Southern Medical University, Guangzhou, China.

Keywords

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