Deep learning in pulmonary nodule detection and segmentation: a systematic review.

Journal: European radiology
Published Date: Jul 10, 2024

Abstract

OBJECTIVES: The accurate detection and precise segmentation of lung nodules on computed tomography are key prerequisites for early diagnosis and appropriate treatment of lung cancer. This study was designed to compare detection and segmentation methods for pulmonary nodules using deep-learning techniques to fill methodological gaps and biases in the existing literature.

Authors

  • Chuan Gao
    Department of Cardiothoracic Surgery, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, 305 East Zhongshan Road, Nanjing, Jiangsu, People's Republic of China.
  • Linyu Wu
    Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
  • Wei Wu
    Department of Pharmacy, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
  • Yichao Huang
    Department of Toxicology, School of Public Health, Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei, China; Department of Gynecology and Obstetrics, The Second Affiliated Hospital, Anhui Medical University, Hefei, China; Clinical Research Center, Suzhou Hospital of Anhui Medical University, Anhui Medical University, Suzhou, China. Electronic address: yichao.huang@ahmu.edu.cn.
  • Xinyue Wang
    Department of Otorhinolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
  • Zhichao Sun
    Beidou Academic & Research Center, Beidou Life Science, Guangzhou, China.
  • Maosheng Xu
    Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
  • Chen Gao
    Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.

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