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Please use this identifier to cite or link to this item: https://wslhd.intersearch.com.au/wslhdjspui/handle/1/6986
TitleConvolutional Neural Networks in ENT Radiology: Systematic Review of the Literature
Authors: Hasan, Z.;Key, S.;Habib, A. R.;Wong, E.;Aweidah, L.;Kumar, A.;Sacks, R.;Singh, N.
WSLHD Author: Hasan, Zubair;Habib, Al-Rahim;Wong, Eugene;Singh, Narinder
Issue Date: 2023
Citation: Annals of Otology, Rhinology & Laryngology 132(4):417-430, 2023
Abstract: INTRODUCTION: Convolutional neural networks (CNNs) represent a state-of-the-art methodological technique in AI and deep learning, and were specifically created for image classification and computer vision tasks. CNNs have been applied in radiology in a number of different disciplines, mostly outside otolaryngology, potentially due to a lack of familiarity with this technology within the otolaryngology community. CNNs have the potential to revolutionize clinical practice by reducing the time required to perform manual tasks. This literature search aims to present a comprehensive systematic review of the published literature with regard to CNNs and their utility to date in ENT radiology.METHODS: Data were extracted from a variety of databases including PubMED, Proquest, MEDLINE Open Knowledge Maps, and Gale OneFile Computer Science. Medical subject headings (MeSH) terms and keywords were used to extract related literature from each databases inception to October 2020. Inclusion criteria were studies where CNNs were used as the main intervention and CNNs focusing on radiology relevant to ENT. Titles and abstracts were reviewed followed by the contents. Once the final list of articles was obtained, their reference lists were also searched to identify further articles.RESULTS: Thirty articles were identified for inclusion in this study. Studies utilizing CNNs in most ENT subspecialties were identified. Studies utilized CNNs for a number of tasks including identification of structures, presence of pathology, and segmentation of tumors for radiotherapy planning. All studies reported a high degree of accuracy of CNNs in performing the chosen task.CONCLUSION: This study provides a better understanding of CNN methodology used in ENT radiology demonstrating a myriad of potential uses for this exciting technology including nodule and tumor identification, identification of anatomical variation, and segmentation of tumors. It is anticipated that this field will continue to evolve and these technologies and methodologies will become more entrenched in our everyday practice.
URI: https://wslhd.intersearch.com.au/wslhdjspui/handle/1/6986
DOI: https://dx.doi.org/10.1177/00034894221095899
Journal: Annals of Otology, Rhinology & Laryngology
Type: Journal Article
Department: Otolaryngology - Head and Neck Surgery
Facility: Westmead
Keywords: Radiology
Otolaryngology
Appears in Collections:Westmead Hospital 2019 - 2024

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