Machine Learning Applications for Head and Neck Imaging.

Clicks: 355
ID: 128173
2020
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Ranked #3 of 9 articles by views in neuroimaging clinics of north america

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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.
Reference Key
maleki2020machineneuroimaging Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Maleki, Farhad;Le, William Trung;Sananmuang, Thiparom;Kadoury, Samuel;Forghani, Reza;
Journal neuroimaging clinics of north america
Year 2020
DOI
S1052-5149(20)30058-7
URL
Keywords
Deep learning artificial intelligence Machine learning Convolutional neural network classification head and neck cancer autosegmentation head and neck imaging

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