Fusing radiomics and deep learning features for automated classification of multi-type pulmonary nodule.

Journal: Medical physics
Published Date: May 20, 2025

Abstract

BACKGROUND: The accurate classification of lung nodules is critical to achieving personalized lung cancer treatment and prognosis prediction. The treatment options for lung cancer and the prognosis of patients are closely related to the type of lung nodules, but there are many types of lung nodules, and the distinctions between certain types are subtle, making accurate classification based on traditional medical imaging technology and doctor experience challenging.

Authors

  • Lingyan Du
    School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, People's Republic of China.
  • Guozhi Tang
    School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, People's Republic of China.
  • Yue Che
    School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, 100083, China.
  • Shihai Ling
    School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, People's Republic of China.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.
  • Xingliang Pan
    The School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, Sichuan 643000, P. R. China.

Keywords

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