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Diabetic Retinopathy Detection Tool (DRDT)

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dc.contributor.advisor Gasmen, Perlita E.
dc.contributor.author Ocaña, Christine Eve
dc.date.accessioned 2016-08-11T06:24:45Z
dc.date.available 2016-08-11T06:24:45Z
dc.date.issued 2016-06
dc.identifier.uri http://dspace.cas.upm.edu.ph:8080/jspui/handle/123456789/415
dc.description.abstract Diabetic retinopathy is one common cause of vision impairment. If not detected and treated, this can also cause blindness. Diabetic Retinopathy Detection Tool (DRDT) is a non-proprietary decision support tool. It classifies fundus/eye images as normal or diabetic retinopathy positive through the use of image processing and support vector machines. The classification is based on the areas of retinal structures and GLCM texture features. DRDT could be used as a starting point for other developers who want to create a decision support tool for DR. Since DRDT’s trained classifier gives an average accuracy of 66.6667%, the methods used in the creation of the tool needs to be enhanced to achieve higher accuracy. If the tool is improved, it could be used to provide second opinion to ophthalmologists on detecting DR in patients. en_US
dc.language.iso en_US en_US
dc.subject diabetic retinopathy en_US
dc.subject decision support tool en_US
dc.subject support vector machine en_US
dc.subject image processing en_US
dc.title Diabetic Retinopathy Detection Tool (DRDT) en_US
dc.type Thesis en_US


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