Machine Learning Applications for Head and Neck Imaging.

Artificial intelligence Autosegmentation Classification Convolutional neural network Deep learning Head and neck cancer Head and neck imaging Machine learning

Journal

Neuroimaging clinics of North America
ISSN: 1557-9867
Titre abrégé: Neuroimaging Clin N Am
Pays: United States
ID NLM: 9211377

Informations de publication

Date de publication:
Nov 2020
Historique:
entrez: 11 10 2020
pubmed: 12 10 2020
medline: 12 8 2021
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 33039001
pii: S1052-5149(20)30058-7
doi: 10.1016/j.nic.2020.08.003
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

517-529

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Farhad Maleki (F)

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.

William Trung Le (WT)

Polytechnique Montreal, PO Box 6079, succ. Centre-ville, Montreal, Quebec H3C 3A7, Canada.

Thiparom Sananmuang (T)

Department of Diagnostic and Therapeutic Radiology and Research, Faculty of Medicine Ramathibodi Hospital, Ratchathewi, Bangkok 10400, Thailand.

Samuel Kadoury (S)

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.

Reza Forghani (R)

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: reza.forghani@mcgill.ca.

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