Automatic tear film segmentation based on texture analysis and region growing

dc.contributor.author Beatriz Remeseiro López en
dc.contributor.author Oliver,KM en
dc.contributor.author Martin,E en
dc.contributor.author Tomlinson,A en
dc.contributor.author Villaverde,DG en
dc.contributor.author Penedo,MG en
dc.date.accessioned 2018-01-16T19:44:00Z
dc.date.available 2018-01-16T19:44:00Z
dc.date.issued 2014 en
dc.description.abstract Dry eye syndrome is a prevalent disease characterized by symptoms of discomfort and ocular surface damage. It can be identified by several types of diagnostic tests, one of which consists in capturing the appearance of the tear film by means of the Doane interferometer. Previous research has demonstrated that this manual test can be automated, with the benefits of saving time for experts and providing unbiased results. However, most images are made up of a combination of different patterns which makes their classification into one single category per eye not always possible. In this sense, this paper presents a first attempt to segment tear film images based on the interference patterns, and so to detect multiple categories in each individual subject. The adequacy of the proposed methodology was demonstrated since it provides reliable results in comparison with the practitioners’ annotations. © Springer International Publishing Switzerland 2014. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/6522
dc.identifier.uri http://dx.doi.org/10.1007/978-3-319-11755-3_21 en
dc.language eng en
dc.relation 6485 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title Automatic tear film segmentation based on texture analysis and region growing en
dc.type conferenceObject en
dc.type Publication en
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