Towards clinical implementation of automated segmentation of vestibular schwannomas: a reliability study comparing AI and human performance.

Journal: Neuroradiology
PMID: 40183966

Abstract

PURPOSE: To evaluate the clinimetric reliability of automated vestibular schwannoma (VS) segmentations by a comparison with human inter-observer variability on T1-weighted contrast-enhanced MRI scans.

Authors

  • Stefan Cornelissen
    Gamma Knife Center, Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, Netherlands. stefan.cornelissen@etz.nl.
  • Sammy M Schouten
    Gamma Knife Center, Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, Netherlands.
  • Patrick P J H Langenhuizen
    Gamma Knife Center, Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, Netherlands.
  • Henricus P M Kunst
    Department of Otorhinolaryngology and Head and Neck Surgery, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Jeroen B Verheul
    Gamma Knife Center, Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, Netherlands.
  • Peter H N de With
    Eindhoven University of Technology, 5612 AJ, Eindhoven, The Netherlands.

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