Fusion of CT images and clinical variables based on deep learning for predicting invasiveness risk of stage I lung adenocarcinoma.

Abstract

Authors

• Haozhe Huang
  Department of Interventional Radiology, Fudan University Shanghai Cancer Center, Xuhui District, Shanghai, China.
• Dezhong Zheng
  Laboratory for Medical Imaging Informatics, Shanghai Institute of Technical Physics, Chinese Academy of Science, Hongkou District, Shanghai, China.
• Hong Chen
  Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
• Ying Wang
  Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
• Chao Chen
  Department of Neonatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
• Lichao Xu
• Guodong Li
  Department of Interventional Radiology, Fudan University Shanghai Cancer Center, Xuhui District, Shanghai, China.
• Yaohui Wang
  Department of Interventional Radiology, Fudan University Shanghai Cancer Center, Xuhui District, Shanghai, China.
• Xinhong He
  Department of Interventional Radiology, Fudan University Shanghai Cancer Center, Xuhui District, Shanghai, China.
• Wentao Li
  State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, Hubei, People's Republic of China.

Keywords

External Resources