Multicenter Study of the Utility of Convolutional Neural Network and Transformer Models for the Detection and Segmentation of Meningiomas.

Journal: Journal of computer assisted tomography
Published Date:

Abstract

PURPOSE: This study aimed to investigate the effectiveness and practicality of using models like convolutional neural network and transformer in detecting and precise segmenting meningioma from magnetic resonance images.

Authors

  • Xin Ma
    Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
  • Lingxiao Zhao
    Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou.
  • Shijie Dang
    Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou.
  • Yajing Zhao
    Department of Radiology, Huashan Hospital Affiliated to Fudan University.
  • Yiping Lu
    Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Rd. Middle, Shanghai, 200040, China.
  • Xuanxuan Li
    Department of Radiology, Huashan Hospital Affiliated to Fudan University, 12 Wulumuqi Rd. Middle, Shanghai 200040, China.
  • Peng Li
    WuXi AppTec Co, Shanghai, China.
  • Yibo Chen
  • Nan Mei
    Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd., Jing'an District, Shanghai, 200040, China.
  • Bo Yin
    College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou, 730000 People's Republic of China.
  • Daoying Geng
    Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Rd. Middle, Shanghai, 200040, China. GengdaoyingGDY@163.com.