A Deep Learning Framework for Analysis of the Eustachian Tube and the Internal Carotid Artery.

Journal: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
PMID: 38686594

Abstract

OBJECTIVE: Obtaining automated, objective 3-dimensional (3D) models of the Eustachian tube (ET) and the internal carotid artery (ICA) from computed tomography (CT) scans could provide useful navigational and diagnostic information for ET pathologies and interventions. We aim to develop a deep learning (DL) pipeline to automatically segment the ET and ICA and use these segmentations to compute distances between these structures.

Authors

  • Ameen Amanian
    Division of Otolaryngology-Head and Neck Surgery, Department of Surgery, University of British Columbia, Vancouver, Canada.
  • Aseem Jain
    Department of Biomedical Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
  • Yuliang Xiao
    Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA.
  • Chanha Kim
    Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA.
  • Andy S Ding
    Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine.
  • Manish Sahu
    Zuse Institute Berlin, Berlin, Germany. sahu@zib.de.
  • Russell Taylor
    Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
  • Mathias Unberath
    Johns Hopkins University, Baltimore, MD, USA.
  • Bryan K Ward
    Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Deepa Galaiya
    Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Masaru Ishii
    Department of Otolaryngology-Head and Neck Surgery, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
  • Francis X Creighton
    Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University, Baltimore, MD, USA.

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