An artificial intelligence algorithm that identifies middle turbinate pneumatisation (concha bullosa) on sinus computed tomography scans.

Journal: The Journal of laryngology and otology
PMID: 32234081

Abstract

OBJECTIVE: Convolutional neural networks are a subclass of deep learning or artificial intelligence that are predominantly used for image analysis and classification. This proof-of-concept study attempts to train a convolutional neural network algorithm that can reliably determine if the middle turbinate is pneumatised (concha bullosa) on coronal sinus computed tomography images.

Authors

  • P Parmar
    Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Australia.
  • A-R Habib
    Department of Otolaryngology - Head and Neck Surgery, Westmead Hospital, Sydney, Australia.
  • D Mendis
    Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Australia.
  • A Daniel
    Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Australia.
  • M Duvnjak
    Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Australia.
  • J Ho
    Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Australia.
  • M Smith
    Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Australia.
  • D Roshan
    Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Australia.
  • E Wong
    Department of Otolaryngology - Head and Neck Surgery, Westmead Hospital, Sydney, Australia.
  • N Singh
    Department of Otolaryngology - Head and Neck Surgery, Westmead Hospital, Sydney, Australia.

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