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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16324
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dc.contributor.authorRaman, Sundaresan-
dc.date.accessioned2024-11-11T09:58:13Z-
dc.date.available2024-11-11T09:58:13Z-
dc.date.issued2022-01-
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0026286221001072#ks0005-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16324-
dc.description.abstractProblems and diseases with eye are common in diabetic patients. Early diagnosis and detection of various diseases like retinopathy, neuropathy and nephropathy is crucial in diabetic patients. Certain demographic and diagnostic parameters play a significant role in predicting diseases related to diabetes. Development of a novel diagnostic method which helps to predict the disease by establishing a significant correlation with the demographic and diagnostic parameters is of prime importance. This study proposes a new methodology in which retinal fractals are obtained for the images and the derived retinal fractals are analysed to aid in disease prediction. This study comprises of images from patients with retinopathy, non retinopathy, neuropathy, nephropathy and hypertension. The proposed research is carried out in two aspects: 1) to correlate the retinal fractals of retinopathy and non retinopathy images with certain demographic and diagnostic parameters and interpret its significance, and 2) to exhibit a relationship between the retinal fractals and various diseases/addictive habit to facilitate the prediction of the disease/addictive habit. Hausdorff fractal dimension (HFD) was applied and higher fractal dimension was obtained for healthy cases. Then using Statistical Package for the Social Sciences (SPSS) various statistical parameters and significance were calculated to analyse the relationship. Analysis results showed that fractal value helped in distinguishing between the retinopathy and non retinopathy conditions. It also helped in diagnosing the presence and absence of hypertension. Correlation analysis between certain demographic parameters and fractal value showed a positive correlation whereas few exhibited negative correlation.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectComputer Scienceen_US
dc.subjectBlood vessel extractionen_US
dc.subjectFractal analysisen_US
dc.subjectDiabetic retinopathyen_US
dc.subjectNeuropathyen_US
dc.subjectNephropathyen_US
dc.titleRelationship of fractal analysis in retinal microvascularity with demographic and diagnostic parametersen_US
dc.typeArticleen_US
Appears in Collections:Department of Computer Science and Information Systems

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