Automatic grading system for human tear films
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://repositorio.inesctec.pt/handle/123456789/6511 http://dx.doi.org/10.1007/s10044-014-0402-x |
Resumo: | Dry eye syndrome is a prevalent disease which affects a wide range of the population and has a negative impact on their daily activities, such as driving or working with computers. Its diagnosis and monitoring require a battery of tests which measure different physiological characteristics. One of these clinical tests consists in capturing the appearance of the tear film using the Doane interferometer. Once acquired, the interferometry images are classified into one of the five categories considered in this research. The variability in appearance makes the use of a computer-based analysis system highly desirable. For this reason, a general methodology for the automatic analysis and categorization of interferometry images is proposed. The development of this methodology included a deep study based on several techniques for image texture analysis, three color spaces and different machine learning algorithms. The adequacy of this methodology was demonstrated, achieving classification rates over 93 %. Also, it provides unbiased results and allows important time savings for experts. © 2014, Springer-Verlag London. |
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Automatic grading system for human tear filmsDry eye syndrome is a prevalent disease which affects a wide range of the population and has a negative impact on their daily activities, such as driving or working with computers. Its diagnosis and monitoring require a battery of tests which measure different physiological characteristics. One of these clinical tests consists in capturing the appearance of the tear film using the Doane interferometer. Once acquired, the interferometry images are classified into one of the five categories considered in this research. The variability in appearance makes the use of a computer-based analysis system highly desirable. For this reason, a general methodology for the automatic analysis and categorization of interferometry images is proposed. The development of this methodology included a deep study based on several techniques for image texture analysis, three color spaces and different machine learning algorithms. The adequacy of this methodology was demonstrated, achieving classification rates over 93 %. Also, it provides unbiased results and allows important time savings for experts. © 2014, Springer-Verlag London.2018-01-16T19:32:37Z2015-01-01T00:00:00Z2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/6511http://dx.doi.org/10.1007/s10044-014-0402-xengBeatriz Remeseiro LópezOliver,KMTomlinson,AMartin,EBarreira,NMosquera,Ainfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:23Zoai:repositorio.inesctec.pt:123456789/6511Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:02.051424Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Automatic grading system for human tear films |
title |
Automatic grading system for human tear films |
spellingShingle |
Automatic grading system for human tear films Beatriz Remeseiro López |
title_short |
Automatic grading system for human tear films |
title_full |
Automatic grading system for human tear films |
title_fullStr |
Automatic grading system for human tear films |
title_full_unstemmed |
Automatic grading system for human tear films |
title_sort |
Automatic grading system for human tear films |
author |
Beatriz Remeseiro López |
author_facet |
Beatriz Remeseiro López Oliver,KM Tomlinson,A Martin,E Barreira,N Mosquera,A |
author_role |
author |
author2 |
Oliver,KM Tomlinson,A Martin,E Barreira,N Mosquera,A |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Beatriz Remeseiro López Oliver,KM Tomlinson,A Martin,E Barreira,N Mosquera,A |
description |
Dry eye syndrome is a prevalent disease which affects a wide range of the population and has a negative impact on their daily activities, such as driving or working with computers. Its diagnosis and monitoring require a battery of tests which measure different physiological characteristics. One of these clinical tests consists in capturing the appearance of the tear film using the Doane interferometer. Once acquired, the interferometry images are classified into one of the five categories considered in this research. The variability in appearance makes the use of a computer-based analysis system highly desirable. For this reason, a general methodology for the automatic analysis and categorization of interferometry images is proposed. The development of this methodology included a deep study based on several techniques for image texture analysis, three color spaces and different machine learning algorithms. The adequacy of this methodology was demonstrated, achieving classification rates over 93 %. Also, it provides unbiased results and allows important time savings for experts. © 2014, Springer-Verlag London. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01T00:00:00Z 2015 2018-01-16T19:32:37Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.inesctec.pt/handle/123456789/6511 http://dx.doi.org/10.1007/s10044-014-0402-x |
url |
http://repositorio.inesctec.pt/handle/123456789/6511 http://dx.doi.org/10.1007/s10044-014-0402-x |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/embargoedAccess |
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embargoedAccess |
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application/pdf |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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