Identification of Benign and Malignant Lung Nodules in CT Images Based on Ensemble Learning Method.

Journal: Interdisciplinary sciences, computational life sciences
Published Date:

Abstract

BACKGROUND AND OBJECTIVE: Under the background of urgent need for computer-aided technology to provide physicians with objective decision support, aiming at reducing the false positive rate of nodule CT detection in pulmonary nodules detection and improving the accuracy of lung nodule recognition, this paper puts forward a method based on ensemble learning to distinguish between malignant and benign pulmonary nodules.

Authors

  • Yifei Xu
    Gansu Institute of Food Inspection, Lanzhou, China.
  • Shijie Wang
    Lab of Image Science and Technology, Key Laboratory of Computer Network and Information Integration (Ministry of Education), Southeast University, Nanjing, 210096, China.
  • Xiaoqian Sun
    Medical Engineering Technology and Data Mining Institute, Zhengzhou University, Zhengzhou, 450001, Henan, China.
  • Yanjun Yang
    Medical Engineering Technology and Data Mining Institute, Zhengzhou University, Zhengzhou, 450001, Henan, China.
  • Jiaxing Fan
    Medical Engineering Technology and Data Mining Institute, Zhengzhou University, Zhengzhou, 450001, Henan, China.
  • Wenwen Jin
    Medical Engineering Technology and Data Mining Institute, Zhengzhou University, Zhengzhou, 450001, Henan, China.
  • Yingyue Li
    Medical Engineering Technology and Data Mining Institute, Zhengzhou University, Zhengzhou, 450001, Henan, China.
  • Fangchu Su
    Medical Engineering Technology and Data Mining Institute, Zhengzhou University, Zhengzhou, 450001, Henan, China.
  • Weihua Zhang
  • Qingli Cui
    Henan Cancer Hospital, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, 450004, Henan, China.
  • Yanhui Hu
    Henan Cancer Hospital, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, 450004, Henan, China.
  • Sheng Wang
    Intensive Care Medical Center, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, People's Republic of China.
  • Jianhua Zhang
  • Chuanliang Chen
    Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, P. R. China.