Artificial intelligence for automatic cerebral ventricle segmentation and volume calculation: a clinical tool for the evaluation of pediatric hydrocephalus.

Journal: Journal of neurosurgery. Pediatrics
Published Date: Dec 1, 2020

Abstract

OBJECTIVE: Imaging evaluation of the cerebral ventricles is important for clinical decision-making in pediatric hydrocephalus. Although quantitative measurements of ventricular size, over time, can facilitate objective comparison, automated tools for calculating ventricular volume are not structured for clinical use. The authors aimed to develop a fully automated deep learning (DL) model for pediatric cerebral ventricle segmentation and volume calculation for widespread clinical implementation across multiple hospitals.

Authors

  • Jennifer L Quon
    1Department of Neurosurgery, Stanford University School of Medicine.
  • Michelle Han
    Department of Radiology, Stanford University School of Medicine, 300 Pasteur Drive, H3630, Stanford, CA, 94305.
  • Lily H Kim
    School of Medicine, Stanford University, Stanford, California.
  • Mary Ellen Koran
    3Department of Radiology, Stanford University School of Medicine.
  • Leo C Chen
    4Department of Urology, Stanford University School of Medicine.
  • Edward H Lee
    Department of Radiology, Stanford University School of Medicine, 300 Pasteur Drive, H3630, Stanford, CA, 94305.
  • Jason Wright
    6Department of Radiology, Seattle Children's Hospital, University of Washington School of Medicine, Seattle, Washington.
  • Vijay Ramaswamy
    7Section of Neuro-Oncology, The Hospital for Sick Children, University of Toronto, Ontario, Canada.
  • Robert M Lober
    8Department of Neurosurgery, Dayton Children's Hospital, Wright State University Boonshoft School of Medicine, Dayton, Ohio.
  • Michael D Taylor
    Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada.
  • Gerald A Grant
    Departments of1Neurosurgery and.
  • Samuel H Cheshier
    10Department of Neurosurgery, University of Utah School of Medicine, Salt Lake City, Utah; and.
  • John R W Kestle
    10Department of Neurosurgery, University of Utah School of Medicine, Salt Lake City, Utah; and.
  • Michael S B Edwards
    1Department of Neurosurgery, Stanford University School of Medicine.
  • Kristen W Yeom
    Department of Radiology, Stanford University, Stanford, California, United States of America.

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