Deep learning for risk stratification of thymoma pathological subtypes based on preoperative CT images.

Journal: BMC cancer
Published Date: May 28, 2024

Abstract

OBJECTIVES: This study aims to develop an innovative, deep model for thymoma risk stratification using preoperative CT images. Current algorithms predominantly focus on radiomic features or 2D deep features and require manual tumor segmentation by radiologists, limiting their practical applicability.

Authors

  • Wei Liu
    Department of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, United States.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Ruihua Guo
    School of Computer Science, The University of Sydney, Sydney, Australia.
  • Hanyi Zhang
  • MiaoRan Guo
    Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China.

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