Automatic Segmentation of Vestibular Schwannomas: A Systematic Review.

Journal: World neurosurgery
Published Date: Apr 27, 2024

Abstract

BACKGROUND: Vestibular schwannomas (VSs) are benign tumors often monitored over time, with measurement techniques for assessing growth rates subject to significant interobserver variability. Automatic segmentation of these tumors could provide a more reliable and efficient for tracking their progression, especially given the irregular shape and growth patterns of VS.

Authors

  • Kerem Nernekli
    Stanford University Medical School, Department of Radiology, Stanford, CA, USA. Electronic address: kerem.nernekli@stanford.edu.tr.
  • Amit R Persad
    Department of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA.
  • Yusuke S Hori
    Department of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA.
  • Ulas Yener
    Department of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA.
  • Emrah Celtikci
    University of Pittsburgh Medical Center, Department of Neurological Surgery, Pittsburgh, PA, USA.
  • Mustafa Caglar Sahin
    Gazi University Faculty of Medicine, Department of Neurosurgery, Ankara, Turkey. Electronic address: mcaglarsahin@gazi.edu.tr.
  • Alperen Sozer
    Gazi University Faculty of Medicine, Department of Neurosurgery, Ankara, Turkey. Electronic address: alperen.sozer@gazi.edu.tr.
  • Batuhan Sozer
    Department of Neurosurgery, Gazi University, Ankara, Turkey.
  • David J Park
    Department of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA. Electronic address: djpark@stanford.edu.
  • Steven D Chang
    Department of Neurosurgery Stanford University School of Medicine Stanford, California, USA.

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