Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography Images

Early diagnosis of oral cancer is critical to improve the survival rate of patients. The current strategies for screening of patients for oral premalignant and malignant lesions unfortunately miss a significant number of involved patients. Optical coherence tomography (OCT) is an optical imaging mod...

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Main Authors: Kousar Ramezani, Maryam Tofangchiha
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Radiology Research and Practice
Online Access:http://dx.doi.org/10.1155/2022/1614838
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author Kousar Ramezani
Maryam Tofangchiha
author_facet Kousar Ramezani
Maryam Tofangchiha
author_sort Kousar Ramezani
collection DOAJ
description Early diagnosis of oral cancer is critical to improve the survival rate of patients. The current strategies for screening of patients for oral premalignant and malignant lesions unfortunately miss a significant number of involved patients. Optical coherence tomography (OCT) is an optical imaging modality that has been widely investigated in the field of oncology for identification of cancerous entities. Since the interpretation of OCT images requires professional training and OCT images contain information that cannot be inferred visually, artificial intelligence (AI) with trained algorithms has the ability to quantify visually undetectable variations, thus overcoming the barriers that have postponed the involvement of OCT in the process of screening of oral neoplastic lesions. This literature review aimed to highlight the features of precancerous and cancerous oral lesions on OCT images and specify how AI can assist in screening and diagnosis of such pathologies.
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spelling doaj-art-184a552ab90a414bb2da2dc15bd659172025-08-20T03:54:12ZengWileyRadiology Research and Practice2090-195X2022-01-01202210.1155/2022/1614838Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography ImagesKousar Ramezani0Maryam Tofangchiha1Department of Oral and Maxillofacial RadiologyDepartment of Oral and Maxillofacial RadiologyEarly diagnosis of oral cancer is critical to improve the survival rate of patients. The current strategies for screening of patients for oral premalignant and malignant lesions unfortunately miss a significant number of involved patients. Optical coherence tomography (OCT) is an optical imaging modality that has been widely investigated in the field of oncology for identification of cancerous entities. Since the interpretation of OCT images requires professional training and OCT images contain information that cannot be inferred visually, artificial intelligence (AI) with trained algorithms has the ability to quantify visually undetectable variations, thus overcoming the barriers that have postponed the involvement of OCT in the process of screening of oral neoplastic lesions. This literature review aimed to highlight the features of precancerous and cancerous oral lesions on OCT images and specify how AI can assist in screening and diagnosis of such pathologies.http://dx.doi.org/10.1155/2022/1614838
spellingShingle Kousar Ramezani
Maryam Tofangchiha
Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography Images
Radiology Research and Practice
title Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography Images
title_full Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography Images
title_fullStr Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography Images
title_full_unstemmed Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography Images
title_short Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography Images
title_sort oral cancer screening by artificial intelligence oriented interpretation of optical coherence tomography images
url http://dx.doi.org/10.1155/2022/1614838
work_keys_str_mv AT kousarramezani oralcancerscreeningbyartificialintelligenceorientedinterpretationofopticalcoherencetomographyimages
AT maryamtofangchiha oralcancerscreeningbyartificialintelligenceorientedinterpretationofopticalcoherencetomographyimages