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Deep Learning Techniques and Imaging in Otorhinolaryngology—A State-of-the-Art Review.

Authors :
Tsilivigkos, Christos
Athanasopoulos, Michail
Micco, Riccardo di
Giotakis, Aris
Mastronikolis, Nicholas S.
Mulita, Francesk
Verras, Georgios-Ioannis
Maroulis, Ioannis
Giotakis, Evangelos
Source :
Journal of Clinical Medicine. Nov2023, Vol. 12 Issue 22, p6973. 16p.
Publication Year :
2023

Abstract

Over the last decades, the field of medicine has witnessed significant progress in artificial intelligence (AI), the Internet of Medical Things (IoMT), and deep learning (DL) systems. Otorhinolaryngology, and imaging in its various subspecialties, has not remained untouched by this transformative trend. As the medical landscape evolves, the integration of these technologies becomes imperative in augmenting patient care, fostering innovation, and actively participating in the ever-evolving synergy between computer vision techniques in otorhinolaryngology and AI. To that end, we conducted a thorough search on MEDLINE for papers published until June 2023, utilizing the keywords 'otorhinolaryngology', 'imaging', 'computer vision', 'artificial intelligence', and 'deep learning', and at the same time conducted manual searching in the references section of the articles included in our manuscript. Our search culminated in the retrieval of 121 related articles, which were subsequently subdivided into the following categories: imaging in head and neck, otology, and rhinology. Our objective is to provide a comprehensive introduction to this burgeoning field, tailored for both experienced specialists and aspiring residents in the domain of deep learning algorithms in imaging techniques in otorhinolaryngology. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20770383
Volume :
12
Issue :
22
Database :
Academic Search Index
Journal :
Journal of Clinical Medicine
Publication Type :
Academic Journal
Accession number :
173830803
Full Text :
https://doi.org/10.3390/jcm12226973