Automatic grading system for human tear films Beatriz Remeseiro López en Oliver,KM en Tomlinson,A en Martin,E en Barreira,N en Mosquera,A en 2018-01-16T19:32:37Z 2018-01-16T19:32:37Z 2015 en
dc.description.abstract 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. en
dc.identifier.uri en
dc.language eng en
dc.relation 6485 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title Automatic grading system for human tear films en
dc.type article en
dc.type Publication en
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