Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks

Abstract Skin pigmentation is associated with skin damages and skin cancers, and ultraviolet (UV) photography is used as a minimally invasive mean for the assessment of pigmentation. Since UV photography equipment is not usually available in general practice, technologies emphasizing pigmentation in...

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Autores principales:	Kaname Kojima, Kosuke Shido, Gen Tamiya, Kenshi Yamasaki, Kengo Kinoshita, Setsuya Aiba
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/51777abb8aa04ae0bffb0c67e6a36e44
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spelling	oai:doaj.org-article:51777abb8aa04ae0bffb0c67e6a36e442021-12-02T14:01:38ZFacial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks10.1038/s41598-020-79995-42045-2322https://doaj.org/article/51777abb8aa04ae0bffb0c67e6a36e442021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-79995-4https://doaj.org/toc/2045-2322Abstract Skin pigmentation is associated with skin damages and skin cancers, and ultraviolet (UV) photography is used as a minimally invasive mean for the assessment of pigmentation. Since UV photography equipment is not usually available in general practice, technologies emphasizing pigmentation in color photo images are desired for daily care. We propose a new method using conditional generative adversarial networks, named UV-photo Net, to generate synthetic UV images from color photo images. Evaluations using color and UV photo image pairs taken by a UV photography system demonstrated that pigment spots were well reproduced in synthetic UV images by UV-photo Net, and some of the reproduced pigment spots were difficult to be recognized in color photo images. In the pigment spot detection analysis, the rate of pigment spot areas in cheek regions for synthetic UV images was highly correlated with the rate for UV photo images (Pearson’s correlation coefficient 0.92). We also demonstrated that UV-photo Net was effective for floating up pigment spots for photo images taken by a smartphone camera. UV-photo Net enables an easy assessment of pigmentation from color photo images and will promote self-care of skin damages and early signs of skin cancers for preventive medicine.Kaname KojimaKosuke ShidoGen TamiyaKenshi YamasakiKengo KinoshitaSetsuya AibaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kaname Kojima Kosuke Shido Gen Tamiya Kenshi Yamasaki Kengo Kinoshita Setsuya Aiba Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks
description	Abstract Skin pigmentation is associated with skin damages and skin cancers, and ultraviolet (UV) photography is used as a minimally invasive mean for the assessment of pigmentation. Since UV photography equipment is not usually available in general practice, technologies emphasizing pigmentation in color photo images are desired for daily care. We propose a new method using conditional generative adversarial networks, named UV-photo Net, to generate synthetic UV images from color photo images. Evaluations using color and UV photo image pairs taken by a UV photography system demonstrated that pigment spots were well reproduced in synthetic UV images by UV-photo Net, and some of the reproduced pigment spots were difficult to be recognized in color photo images. In the pigment spot detection analysis, the rate of pigment spot areas in cheek regions for synthetic UV images was highly correlated with the rate for UV photo images (Pearson’s correlation coefficient 0.92). We also demonstrated that UV-photo Net was effective for floating up pigment spots for photo images taken by a smartphone camera. UV-photo Net enables an easy assessment of pigmentation from color photo images and will promote self-care of skin damages and early signs of skin cancers for preventive medicine.
format	article
author	Kaname Kojima Kosuke Shido Gen Tamiya Kenshi Yamasaki Kengo Kinoshita Setsuya Aiba
author_facet	Kaname Kojima Kosuke Shido Gen Tamiya Kenshi Yamasaki Kengo Kinoshita Setsuya Aiba
author_sort	Kaname Kojima
title	Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks
title_short	Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks
title_full	Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks
title_fullStr	Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks
title_full_unstemmed	Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks
title_sort	facial uv photo imaging for skin pigmentation assessment using conditional generative adversarial networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/51777abb8aa04ae0bffb0c67e6a36e44
work_keys_str_mv	AT kanamekojima facialuvphotoimagingforskinpigmentationassessmentusingconditionalgenerativeadversarialnetworks AT kosukeshido facialuvphotoimagingforskinpigmentationassessmentusingconditionalgenerativeadversarialnetworks AT gentamiya facialuvphotoimagingforskinpigmentationassessmentusingconditionalgenerativeadversarialnetworks AT kenshiyamasaki facialuvphotoimagingforskinpigmentationassessmentusingconditionalgenerativeadversarialnetworks AT kengokinoshita facialuvphotoimagingforskinpigmentationassessmentusingconditionalgenerativeadversarialnetworks AT setsuyaaiba facialuvphotoimagingforskinpigmentationassessmentusingconditionalgenerativeadversarialnetworks
_version_	1718392139832885248

Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks

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