Multi-atlas segmentation of the facial nerve from clinical CT for virtual reality simulators

  • Bradley M. GareEmail author
  • Thomas Hudson
  • Seyed A. Rohani
  • Daniel G. Allen
  • Sumit K. Agrawal
  • Hanif M. Ladak
Original Article



To create a novel, multi-atlas-based segmentation algorithm of the facial nerve (FN) requiring minimal user intervention that could be easily deployed into an existing open-source toolkit. Specifically, the mastoid, tympanic and labyrinthine segments of the FN would be segmented.


High-resolution micro-computed tomography (micro-CT) scans were pre-segmented and used as atlases of the FN. The algorithm requires the user to place four fiducials to orient the target, low-resolution clinical CT scan, and generate a centerline along the nerve. Based on this data, the appropriate atlas is chosen by the algorithm and then rigidly and non-rigidly registered to provide an automated segmentation of the FN.


The algorithm was successfully developed and implemented into an existing open-source software framework. Validation was performed on 28 temporal bones, where the automated segmentation was compared against gold-standard manual segmentation by an expert. The algorithm achieved an average Dice metric of 0.76 and an average Hausdorff distance of 0.17 mm for the tympanic and mastoid portions of the FN when segmenting healthy facial nerves, which are similar to previously published algorithms.


A successful FN segmentation algorithm was developed using a high-resolution micro-CT multi-atlas approach. The algorithm was unique in its ability to segment the entire intratemporal FN, with the exception of the meatal segment, which was not included in the segmentation as it was not discernible from the vestibulocochlear nerve within the internal auditory canal. It will be published as an open-source extension to allow use in virtual reality simulators for automatic segmentation, greatly reducing the time for expert segmentation and verification.


Facial nerve Image segmentation Image registration Otolaryngology Atlas-based segmentation 



This research was supported through a Collaborative Health Research Project grant from the Natural Sciences and Engineering Research Council of Canada (381117) and the Canadian Institutes of Health Research (381117). We thank Ms. Lauren Hayley Siegel for editing the manuscript.

Compliance with ethical standards

Conflict of interest

This study was funded through a Collaborative Health Research Project grant from the Natural Sciences and Engineering Research Council of Canada and the Canadian Institutes of Health Research.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

For this type of study, formal consent is not required.


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Copyright information

© CARS 2019

Authors and Affiliations

  1. 1.Electrical and Computer Engineering Graduate ProgramWestern UniversityLondonCanada
  2. 2.Schulich School of MedicineWestern UniversityLondonCanada
  3. 3.Department of Otolaryngology – Head and Neck SurgeryWestern UniversityLondonCanada
  4. 4.Department of Medical BiophysicsWestern UniversityLondonCanada
  5. 5.Department of Electrical and Computer EngineeringWestern UniversityLondonCanada
  6. 6.Department of Electrical and Computer EngineeringThe University of Western OntarioLondonCanada

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