Quantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions

Abstract Laryngoscopes are widely used in the clinical diagnosis of laryngeal lesions, but such diagnosis relies heavily on the physician's subjective experience. The purpose of this study was to develop a computer-aided diagnostic system for the detection of laryngeal lesions based on objectiv...

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Autores principales:	Chung Feng Jeffrey Kuo, Wen-Sen Lai, Jagadish Barman, Shao-Cheng Liu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2e32079d1acb48b4897cb56376a75dbf
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spelling	oai:doaj.org-article:2e32079d1acb48b4897cb56376a75dbf2021-12-02T17:15:24ZQuantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions10.1038/s41598-021-89680-92045-2322https://doaj.org/article/2e32079d1acb48b4897cb56376a75dbf2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89680-9https://doaj.org/toc/2045-2322Abstract Laryngoscopes are widely used in the clinical diagnosis of laryngeal lesions, but such diagnosis relies heavily on the physician's subjective experience. The purpose of this study was to develop a computer-aided diagnostic system for the detection of laryngeal lesions based on objective criteria. This study used the distinct features of the image contour to find the clearest image in the laryngoscopic video. First to reduce the illumination problem caused by the laryngoscope lens, which could not fix the position of the light source, this study proposed image compensation to provide the image with a consistent brightness range for better performance. Second, we also proposed a method to automatically screen clear images from laryngoscopic film. Third, we used ACM to segment automatically them based on structural features of the pharynx and larynx, using hue and geometric analysis in the vocal cords and other zones. Finally, the support vector machine was used to classify laryngeal lesions based on a decision tree. This study evaluated the performance of the proposed system by assessing the laryngeal images of 284 patients. The accuracy of the detection for vocal cord polyps, cysts, leukoplakia, tumors, and healthy vocal cords were 93.15%, 95.16%, 100%, 96.42%, and 100%, respectively. The cross-validation accuracy for the five classes were 93.1%, 94.95%, 99.4%, 96.01% and 100%, respectively, and the average test accuracy for the laryngeal lesions was 93.33%. Our results showed that it was feasible to take the hue and geometric features of the larynx as signs to identify laryngeal lesions and that they could effectively assist physicians in diagnosing laryngeal lesions.Chung Feng Jeffrey KuoWen-Sen LaiJagadish BarmanShao-Cheng LiuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chung Feng Jeffrey Kuo Wen-Sen Lai Jagadish Barman Shao-Cheng Liu Quantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions
description	Abstract Laryngoscopes are widely used in the clinical diagnosis of laryngeal lesions, but such diagnosis relies heavily on the physician's subjective experience. The purpose of this study was to develop a computer-aided diagnostic system for the detection of laryngeal lesions based on objective criteria. This study used the distinct features of the image contour to find the clearest image in the laryngoscopic video. First to reduce the illumination problem caused by the laryngoscope lens, which could not fix the position of the light source, this study proposed image compensation to provide the image with a consistent brightness range for better performance. Second, we also proposed a method to automatically screen clear images from laryngoscopic film. Third, we used ACM to segment automatically them based on structural features of the pharynx and larynx, using hue and geometric analysis in the vocal cords and other zones. Finally, the support vector machine was used to classify laryngeal lesions based on a decision tree. This study evaluated the performance of the proposed system by assessing the laryngeal images of 284 patients. The accuracy of the detection for vocal cord polyps, cysts, leukoplakia, tumors, and healthy vocal cords were 93.15%, 95.16%, 100%, 96.42%, and 100%, respectively. The cross-validation accuracy for the five classes were 93.1%, 94.95%, 99.4%, 96.01% and 100%, respectively, and the average test accuracy for the laryngeal lesions was 93.33%. Our results showed that it was feasible to take the hue and geometric features of the larynx as signs to identify laryngeal lesions and that they could effectively assist physicians in diagnosing laryngeal lesions.
format	article
author	Chung Feng Jeffrey Kuo Wen-Sen Lai Jagadish Barman Shao-Cheng Liu
author_facet	Chung Feng Jeffrey Kuo Wen-Sen Lai Jagadish Barman Shao-Cheng Liu
author_sort	Chung Feng Jeffrey Kuo
title	Quantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions
title_short	Quantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions
title_full	Quantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions
title_fullStr	Quantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions
title_full_unstemmed	Quantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions
title_sort	quantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/2e32079d1acb48b4897cb56376a75dbf
work_keys_str_mv	AT chungfengjeffreykuo quantitativelaryngoscopywithcomputeraideddiagnosticsystemforlaryngeallesions AT wensenlai quantitativelaryngoscopywithcomputeraideddiagnosticsystemforlaryngeallesions AT jagadishbarman quantitativelaryngoscopywithcomputeraideddiagnosticsystemforlaryngeallesions AT shaochengliu quantitativelaryngoscopywithcomputeraideddiagnosticsystemforlaryngeallesions
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Quantitative laryngoscopy with computer-aided diagnostic system for laryngeal lesions

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