MS-ResNet: disease-specific survival prediction using longitudinal CT images and clinical data.

Journal: International journal of computer assisted radiology and surgery
Published Date: Apr 20, 2022

Abstract

PURPOSE: Medical imaging data of lung cancer in different stages contain a large amount of time information related to its evolution (emergence, development, or extinction). We try to explore the evolution process of lung images in time dimension to improve the prediction of lung cancer survival by using longitudinal CT images and clinical data jointly.

Authors

  • Jiahao Han
    College of Information and Computer, Taiyuan University of Technology, Taiyuan, China.
  • Ning Xiao
    National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, China.
  • Wanting Yang
  • Shichao Luo
    College of Information and Computer, Taiyuan University of Technology, Taiyuan, China.
  • Jun Zhao
  • Yan Qiang
    College of Information and Computer, Taiyuan University of Technology, Taiyuan, China.
  • Suman Chaudhary
    College of Information and Computer, Taiyuan University of Technology, Taiyuan, China.
  • Juanjuan Zhao
    Guanlan Networks (Hangzhou) Co, Ltd, Hangzhou, Zhejiang, China.

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