Histological Subtypes Classification of Lung Cancers on CT Images Using 3D Deep Learning and Radiomics.

Journal: Academic radiology
Published Date: Jul 1, 2020

Abstract

RATIONALE AND OBJECTIVES: Histological subtypes of lung cancers are critical for clinical treatment decision. In this study, we attempt to use 3D deep learning and radiomics methods to automatically distinguish lung adenocarcinomas (ADC), squamous cell carcinomas (SCC), and small cell lung cancers (SCLC) respectively on Computed Tomography images, and then compare their performance.

Authors

  • Yixian Guo
    Department of Radiology, Zhongshan Hospital of Fudan University, Fudan University, No 130, Dongan Rd, Xuhui District, Shanghai, 200032, P.R. of China.
  • Qiong Song
    Xuzhou Mining Group General Hospital, radiology department, Xuzhou, Jiangsu, 221000, P.R. of China; Shanghai Aitrox Technology Corporation Limited, Shanghai, 200032, P.R. of China.
  • Mengmeng Jiang
    Department of Radiology, Shanghai Institute of Medical Imaging, Zhongshan Hospital of Fudan University, Fudan University, No 130, Dongan Rd, Xuhui District, Shanghai, 200032, P.R. of China.
  • Yinglong Guo
    Department of Radiology, Zhongshan Hospital of Fudan University, Fudan University, No138, Fenglin Rd, Xuhui District, Shanghai, 200032, P.R. of China.
  • Peng Xu
    Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
  • Yiqian Zhang
    Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University, 55N-06-10, 3-4-1 Okubo Shinjuku-ku, Tokyo, 169-8555, Japan.
  • Chi-Cheng Fu
    Howard Hughes Medical Institute, Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA Departments of Bioengineering, Electrical Engineering and Computer Science, and Biophysics Graduate Program, University of California, Berkeley, CA 94720, USA.
  • Qu Fang
    Shanghai Aitrox Technology Corporation Limited, Shanghai, 200032, P.R. of China.
  • Mengsu Zeng
    Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Xiuzhong Yao
    Department of Radiology, Shanghai Institute of Medical Imaging, Zhongshan Hospital of Fudan University, Fudan University, No 130, Dongan Rd, Xuhui District, Shanghai, 200032, P.R. of China. Electronic address: zsyyyxz@163.com.

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