Optimization of psoriasis assessment system based on patch images

Abstract Psoriasis is a chronic inflammatory skin disease that occurs in various forms throughout the body and is associated with certain conditions such as heart disease, diabetes, and depression. The psoriasis area severity index (PASI) score, a tool used to evaluate the severity of psoriasis, is...

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Autores principales:	Cho-I. Moon, Jiwon Lee, HyunJong Yoo, YooSang Baek, Onseok Lee
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/578fe97b1ee24526b38eb68e9ad70c7b
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spelling	oai:doaj.org-article:578fe97b1ee24526b38eb68e9ad70c7b2021-12-02T18:33:46ZOptimization of psoriasis assessment system based on patch images10.1038/s41598-021-97211-92045-2322https://doaj.org/article/578fe97b1ee24526b38eb68e9ad70c7b2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97211-9https://doaj.org/toc/2045-2322Abstract Psoriasis is a chronic inflammatory skin disease that occurs in various forms throughout the body and is associated with certain conditions such as heart disease, diabetes, and depression. The psoriasis area severity index (PASI) score, a tool used to evaluate the severity of psoriasis, is currently used in clinical trials and clinical research. The determination of severity is based on the subjective judgment of the clinician. Thus, the disease evaluation deviations are induced. Therefore, we propose optimal algorithms that can effectively segment the lesion area and classify the severity. In addition, a new dataset on psoriasis was built, including patch images of erythema and scaling. We performed psoriasis lesion segmentation and classified the disease severity. In addition, we evaluated the best-performing segmentation method and classifier and analyzed features that are highly related to the severity of psoriasis. In conclusion, we presented the optimal techniques for evaluating the severity of psoriasis. Our newly constructed dataset improved the generalization performance of psoriasis diagnosis and evaluation. It proposed an optimal system for specific evaluation indicators of the disease and a quantitative PASI scoring method. The proposed system can help to evaluate the severity of localized psoriasis more accurately.Cho-I. MoonJiwon LeeHyunJong YooYooSang BaekOnseok LeeNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Cho-I. Moon Jiwon Lee HyunJong Yoo YooSang Baek Onseok Lee Optimization of psoriasis assessment system based on patch images
description	Abstract Psoriasis is a chronic inflammatory skin disease that occurs in various forms throughout the body and is associated with certain conditions such as heart disease, diabetes, and depression. The psoriasis area severity index (PASI) score, a tool used to evaluate the severity of psoriasis, is currently used in clinical trials and clinical research. The determination of severity is based on the subjective judgment of the clinician. Thus, the disease evaluation deviations are induced. Therefore, we propose optimal algorithms that can effectively segment the lesion area and classify the severity. In addition, a new dataset on psoriasis was built, including patch images of erythema and scaling. We performed psoriasis lesion segmentation and classified the disease severity. In addition, we evaluated the best-performing segmentation method and classifier and analyzed features that are highly related to the severity of psoriasis. In conclusion, we presented the optimal techniques for evaluating the severity of psoriasis. Our newly constructed dataset improved the generalization performance of psoriasis diagnosis and evaluation. It proposed an optimal system for specific evaluation indicators of the disease and a quantitative PASI scoring method. The proposed system can help to evaluate the severity of localized psoriasis more accurately.
format	article
author	Cho-I. Moon Jiwon Lee HyunJong Yoo YooSang Baek Onseok Lee
author_facet	Cho-I. Moon Jiwon Lee HyunJong Yoo YooSang Baek Onseok Lee
author_sort	Cho-I. Moon
title	Optimization of psoriasis assessment system based on patch images
title_short	Optimization of psoriasis assessment system based on patch images
title_full	Optimization of psoriasis assessment system based on patch images
title_fullStr	Optimization of psoriasis assessment system based on patch images
title_full_unstemmed	Optimization of psoriasis assessment system based on patch images
title_sort	optimization of psoriasis assessment system based on patch images
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/578fe97b1ee24526b38eb68e9ad70c7b
work_keys_str_mv	AT choimoon optimizationofpsoriasisassessmentsystembasedonpatchimages AT jiwonlee optimizationofpsoriasisassessmentsystembasedonpatchimages AT hyunjongyoo optimizationofpsoriasisassessmentsystembasedonpatchimages AT yoosangbaek optimizationofpsoriasisassessmentsystembasedonpatchimages AT onseoklee optimizationofpsoriasisassessmentsystembasedonpatchimages
_version_	1718377921142325248

Optimization of psoriasis assessment system based on patch images

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