Performance of Convolutional Neural Network Models in Meningioma Segmentation in Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis.

Journal: Neuroinformatics
Published Date:

Abstract

BACKGROUND: Meningioma, the most common primary brain tumor, presents significant challenges in MRI-based diagnosis and treatment planning due to its diverse manifestations. Convolutional Neural Networks (CNNs) have shown promise in improving the accuracy and efficiency of meningioma segmentation from MRI scans. This systematic review and meta-analysis assess the effectiveness of CNN models in segmenting meningioma using MRI.

Authors

  • Ting-Wei Wang
    Department of Medical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
  • Jia-Sheng Hong
    Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan.
  • Wei-Kai Lee
    Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan.
  • Yi-Hui Lin
    School of Pharmacy, Kaohsiung Medical University, 100 Shihchuan 1st Rd., Kaohsiung, 80708, Taiwan.
  • Huai-Che Yang
    Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang-Ming University, Taipei, Taiwan.
  • Cheng-Chia Lee
    Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang-Ming University, Taipei, Taiwan; Brain Research Center, National Yang-Ming University, Taipei, Taiwan.
  • Hung-Chieh Chen
    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, 112304, Taiwan.
  • Hsiu-Mei Wu
    Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang-Ming University, Taipei, Taiwan.
  • Weir Chiang You
    Department of Radiation Oncology, Taichung Veterans General Hospital, Taichung, 407219, Taiwan.
  • Yu-Te Wu
    Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan. ytwu@ym.edu.tw.