@article{scholars1319,
            year = {2010},
            note = {cited By 15},
           pages = {5632--5635},
           title = {Analysis of foveal avascular zone in colour fundus images for grading of diabetic retinopathy severity.},
         journal = {Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference},
          author = {Ahmad Fadzil, M. and Ngah, N. F. and George, T. M. and Izhar, L. I. and Nugroho, H. and Adi Nugroho, H.},
            issn = {1557170X},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903875118&partnerID=40&md5=b77f893bf9cf7c3a797f1fbe96ce4d6e},
        keywords = {algorithm; article; Bayes theorem; capillary; color; diabetic retinopathy; disease course; eye fundus; human; methodology; normal distribution; pathology; retina fovea; severity of illness index; three dimensional imaging; vascularization, Algorithms; Bayes Theorem; Capillaries; Color; Diabetic Retinopathy; Disease Progression; Fovea Centralis; Fundus Oculi; Humans; Imaging, Three-Dimensional; Normal Distribution; Severity of Illness Index},
        abstract = {Diabetic retinopathy (DR) is a sight threatening complication due to diabetes mellitus that affects the retina. At present, the classification of DR is based on the International Clinical Diabetic Retinopathy Disease Severity. In this paper, FAZ enlargement with DR progression is investigated to enable a new and an effective grading protocol DR severity in an observational clinical study. The performance of a computerised DR monitoring and grading system that digitally analyses colour fundus image to measure the enlargement of FAZ and grade DR is evaluated. The range of FAZ area is optimised to accurately determine DR severity stage and progression stages using a Gaussian Bayes classifier. The system achieves high accuracies of above 96, sensitivities higher than 88 and specificities higher than 96, in grading of DR severity. In particular, high sensitivity (100), specificity ({\ensuremath{>}}98) and accuracy (99) values are obtained for No DR (normal) and Severe NPDR/PDR stages. The system performance indicates that the DR system is suitable for early detection of DR and for effective treatment of severe cases.}
}