Machine Learning Applications for Head and Neck Imaging.

Journal: Neuroimaging clinics of North America
Published Date: Nov 1, 2020

Abstract

The head and neck (HN) consists of a large number of vital anatomic structures within a compact area. Imaging plays a central role in the diagnosis and management of major disorders affecting the HN. This article reviews the recent applications of machine learning (ML) in HN imaging with a focus on deep learning approaches. It categorizes ML applications in HN imaging into deep learning and traditional ML applications and provides examples of each category. It also discusses the main challenges facing the successful deployment of ML-based applications in the clinical setting and provides suggestions for addressing these challenges.

Authors

  • Farhad Maleki
    Augmented Intelligence & Precision Health Laboratory (AIPHL), Department of Radiology and Research Institute of the McGill University Health Centre, 1001 Decarie Boulevard, Montreal, Quebec H4A 3J1, Canada.
  • William Trung Le
    Polytechnique Montreal, PO Box 6079, succ. Centre-ville, Montreal, Quebec H3C 3A7, Canada; CHUM Research Center, 900 St Denis Street, Montreal, Quebec H2X 0A9, Canada.
  • Thiparom Sananmuang
    Department of Diagnostic and Therapeutic Radiology and Research, Faculty of Medicine Ramathibodi Hospital, Ratchathewi, Bangkok 10400, Thailand.
  • Samuel Kadoury
    École Polytechnique de Montréal, Montreal, Canada. samuel.kadoury@polymtl.ca.
  • Reza Forghani
    Department of Radiology, McGill University Health Centre, 1001 Decarie Blvd, Room C02.5821, Montreal, QC, Canada H4A 3J1; Augmented Intelligence & Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, Montreal, Canada; Segal Cancer Centre and Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, Canada; and Department of Otolaryngology-Head and Neck Surgery, McGill University, Montreal, Canada.

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