Deep Learning for Detecting Subretinal Fluid and Discerning Macular Status by Fundus Images in Central Serous Chorioretinopathy

Subretinal fluid (SRF) can lead to irreversible visual loss in patients with central serous chorioretinopathy (CSC) if not absorbed in time. Early detection and intervention of SRF can help improve visual prognosis and reduce irreversible damage to the retina. As fundus image is the most commonly us...

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Autores principales:	Fabao Xu, Shaopeng Liu, Yifan Xiang, Zhenzhe Lin, Cong Li, Lijun Zhou, Yajun Gong, Longhui Li, Zhongwen Li, Chong Guo, Chuangxin Huang, Kunbei Lai, Hongkun Zhao, Jiaming Hong, Haotian Lin, Chenjin Jin
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	deep learning central serous chorioretinopathy subretinal fluid serous retinal detachment fundus image Biotechnology TP248.13-248.65
Acceso en línea:	https://doaj.org/article/93b098124ef94205bc5407ce09325687
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spelling	oai:doaj.org-article:93b098124ef94205bc5407ce093256872021-11-05T13:14:06ZDeep Learning for Detecting Subretinal Fluid and Discerning Macular Status by Fundus Images in Central Serous Chorioretinopathy2296-418510.3389/fbioe.2021.651340https://doaj.org/article/93b098124ef94205bc5407ce093256872021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fbioe.2021.651340/fullhttps://doaj.org/toc/2296-4185Subretinal fluid (SRF) can lead to irreversible visual loss in patients with central serous chorioretinopathy (CSC) if not absorbed in time. Early detection and intervention of SRF can help improve visual prognosis and reduce irreversible damage to the retina. As fundus image is the most commonly used and easily obtained examination for patients with CSC, the purpose of our research is to investigate whether and to what extent SRF depicted on fundus images can be assessed using deep learning technology. In this study, we developed a cascaded deep learning system based on fundus image for automated SRF detection and macula-on/off serous retinal detachment discerning. The performance of our system is reliable, and its accuracy of SRF detection is higher than that of experienced retinal specialists. In addition, the system can automatically indicate whether the SRF progression involves the macula to provide guidance of urgency for patients. The implementation of our deep learning system could effectively reduce the extent of vision impairment resulting from SRF in patients with CSC by providing timely identification and referral.Fabao XuShaopeng LiuYifan XiangZhenzhe LinCong LiLijun ZhouYajun GongLonghui LiZhongwen LiChong GuoChuangxin HuangKunbei LaiHongkun ZhaoJiaming HongHaotian LinHaotian LinChenjin JinFrontiers Media S.A.articledeep learningcentral serous chorioretinopathysubretinal fluidserous retinal detachmentfundus imageBiotechnologyTP248.13-248.65ENFrontiers in Bioengineering and Biotechnology, Vol 9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	deep learning central serous chorioretinopathy subretinal fluid serous retinal detachment fundus image Biotechnology TP248.13-248.65
spellingShingle	deep learning central serous chorioretinopathy subretinal fluid serous retinal detachment fundus image Biotechnology TP248.13-248.65 Fabao Xu Shaopeng Liu Yifan Xiang Zhenzhe Lin Cong Li Lijun Zhou Yajun Gong Longhui Li Zhongwen Li Chong Guo Chuangxin Huang Kunbei Lai Hongkun Zhao Jiaming Hong Haotian Lin Haotian Lin Chenjin Jin Deep Learning for Detecting Subretinal Fluid and Discerning Macular Status by Fundus Images in Central Serous Chorioretinopathy
description	Subretinal fluid (SRF) can lead to irreversible visual loss in patients with central serous chorioretinopathy (CSC) if not absorbed in time. Early detection and intervention of SRF can help improve visual prognosis and reduce irreversible damage to the retina. As fundus image is the most commonly used and easily obtained examination for patients with CSC, the purpose of our research is to investigate whether and to what extent SRF depicted on fundus images can be assessed using deep learning technology. In this study, we developed a cascaded deep learning system based on fundus image for automated SRF detection and macula-on/off serous retinal detachment discerning. The performance of our system is reliable, and its accuracy of SRF detection is higher than that of experienced retinal specialists. In addition, the system can automatically indicate whether the SRF progression involves the macula to provide guidance of urgency for patients. The implementation of our deep learning system could effectively reduce the extent of vision impairment resulting from SRF in patients with CSC by providing timely identification and referral.
format	article
author	Fabao Xu Shaopeng Liu Yifan Xiang Zhenzhe Lin Cong Li Lijun Zhou Yajun Gong Longhui Li Zhongwen Li Chong Guo Chuangxin Huang Kunbei Lai Hongkun Zhao Jiaming Hong Haotian Lin Haotian Lin Chenjin Jin
author_facet	Fabao Xu Shaopeng Liu Yifan Xiang Zhenzhe Lin Cong Li Lijun Zhou Yajun Gong Longhui Li Zhongwen Li Chong Guo Chuangxin Huang Kunbei Lai Hongkun Zhao Jiaming Hong Haotian Lin Haotian Lin Chenjin Jin
author_sort	Fabao Xu
title	Deep Learning for Detecting Subretinal Fluid and Discerning Macular Status by Fundus Images in Central Serous Chorioretinopathy
title_short	Deep Learning for Detecting Subretinal Fluid and Discerning Macular Status by Fundus Images in Central Serous Chorioretinopathy
title_full	Deep Learning for Detecting Subretinal Fluid and Discerning Macular Status by Fundus Images in Central Serous Chorioretinopathy
title_fullStr	Deep Learning for Detecting Subretinal Fluid and Discerning Macular Status by Fundus Images in Central Serous Chorioretinopathy
title_full_unstemmed	Deep Learning for Detecting Subretinal Fluid and Discerning Macular Status by Fundus Images in Central Serous Chorioretinopathy
title_sort	deep learning for detecting subretinal fluid and discerning macular status by fundus images in central serous chorioretinopathy
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/93b098124ef94205bc5407ce09325687
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Deep Learning for Detecting Subretinal Fluid and Discerning Macular Status by Fundus Images in Central Serous Chorioretinopathy

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