Machine learning and deep learning based strategies for diagnosis of diabetic maculopathy from sdoct retinal scans

dc.contributor.guideUmamaheswari R
dc.coverage.spatialMachine learning and deep learning based strategies for diagnosis of diabetic maculopathy from sdoct retinal scans
dc.creator.researcherPadmasini N
dc.date.accessioned2023-02-16T05:19:15Z
dc.date.available2023-02-16T05:19:15Z
dc.date.awarded2021
dc.date.completed2021
dc.date.registered
dc.description.abstractOne of the major complications in human eyes due to Diabetes is newlineDiabetic Retinopathy (DR). Diabetic retinopathy occurs when the blood or newlineother fluids leaks from tiny blood vessels of the light-sensitive retinal tissues newlineand accumulate. Due to this the retinal layers gets swollen, resulting in cloudy newlineor blurred vision. It can cause loss of vision if it is left undiagnosed and newlineuntreated. newlineDR includes mainly three stages background retinopathy, newlinepreproliferative stage and proliferative stage. Diabetic Maculopathy (DM) is a newlinecondition of DR and is the main cause of vision loss. In DM, the macula newlineregion, center portion of retina gets affected. DM can occur in any stage of newlineDR, but it likely increases as DR worsens. The chances of occurrence of DM newlineare high in persons with uncontrolled Type 1 or Type 2 diabetes for more than newline10 years duration. newlineRetina is a ten layered structure and the breakdown of blood retinal newlinebarrier leads to Diabetic Macular Edema (DME), which is the cause of DM. newlineInitially, edema starts occurring in the outer nuclear layer or outer plexiform newlinelayer and hence the entire retinal layer thickness increases. In the advanced newlineDM stage, DME may cause several structural changes in the retinal layers. newlineThe crucial task is automated detection of DM in the early stage and newlineidentification of the structural pattern involved in the latter stage. Therefore newlineanalysis of retinal layers is the foremost task in the prevention of vision loss. newline
dc.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensions21cm
dc.format.extentxviii,148p.
dc.identifier.urihttp://hdl.handle.net/10603/458432
dc.languageEnglish
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.relationp.140-147
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordDiabetic Maculopathy
dc.subject.keywordDiabetic Retinopathy
dc.subject.keywordRetinal Layers
dc.titleMachine learning and deep learning based strategies for diagnosis of diabetic maculopathy from sdoct retinal scans
dc.title.alternative
dc.type.degreePh.D.

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