Pulmonary nodule segmentation with CT sample synthesis using adversarial networks.

Journal: Medical physics
Published Date: Jan 31, 2019

Abstract

PURPOSE: Segmentation of pulmonary nodules is critical for the analysis of nodules and lung cancer diagnosis. We present a novel framework of segmentation for various types of nodules using convolutional neural networks (CNNs).

Authors

  • Yulei Qin
    Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, 800 Dongchuan RD. Minhang District, Shanghai, 200240, China.
  • Hao Zheng
    Gilead Sciences, Inc, Foster City, California, USA.
  • Xiaolin Huang
    Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, 200240, Shanghai, P.R. China.
  • Jie Yang
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.
  • Yue-Min Zhu
    University Lyon, INSA Lyon, CNRS, INSERM, CREATIS UMR 5220, U1206, F-69621, Lyon, France.

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