Machine Learning Applications for Head and Neck Imaging.

Neuroimaging Clin N Am

Augmented Intelligence & Precision Health Laboratory (AIPHL), Department of Radiology & Research Institute of the McGill University Health Centre, 5252 Boulevard de Maisonneuve Ouest, Montreal, Quebec H4A 3S5, Canada; Department of Radiology, McGill University, 1650 Cedar Avenue, Montreal, Quebec H3G1A4, Canada; Segal Cancer Centre, Lady Davis Institute for Medical Research, Jewish General Hospital, 3755 Cote Ste-Catherine Road, Montreal, Quebec H3T 1E2, Canada; Gerald Bronfman Department of Oncology, McGill University, Suite 720, 5100 Maisonneuve Boulevard West, Montreal, Quebec H4A3T2, Canada; Department of Otolaryngology, Head and Neck Surgery, Royal Victoria Hospital, McGill University Health Centre, 1001 boul. Decarie Boulevard, Montreal, Quebec H3A 3J1, Canada. Electronic address:

Published: November 2020

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.

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Source
http://dx.doi.org/10.1016/j.nic.2020.08.003DOI Listing

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