Automated segmentation of craniopharyngioma on MR images using U-Net-based deep convolutional neural network.

Journal: European radiology
PMID: 36396792

Abstract

OBJECTIVES: To develop a U-Net-based deep learning model for automated segmentation of craniopharyngioma.

Authors

  • Chaoyue Chen
    Department of Neurosurgery, Sichuan University, West China Hospital, No. 37, GuoXue Alley, Chengdu, 610041, People's Republic of China.
  • Ting Zhang
    Beijing Municipal Key Laboratory of Child Development and Nutriomics, Capital Institute of Pediatrics, Beijing 100020, China.
  • Yuen Teng
    Department of Neurosurgery, Sichuan University, West China Hospital, No. 37, GuoXue Alley, Chengdu, 610041, People's Republic of China.
  • Yijie Yu
    College of Computer Science, Sichuan University, Chengdu, 610065, People's Republic of China.
  • Xin Shu
    College of Computer Science, Sichuan University, Section 4, Southern 1st Ring Rd, Chengdu, Sichuan 610065, P. R. China.
  • Lei Zhang
    Division of Gastroenterology, Union Hospital, Tongji Medical College Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Fumin Zhao
  • Jianguo Xu

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