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|Title:||Towards automatic detection of age-related macular degeneration in retinal fundus images|
|Citation:||Liang, Z., Wong, D.W.K., Liu, J., Chan, K.L., Wong, T.Y. (2010). Towards automatic detection of age-related macular degeneration in retinal fundus images. 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 : 4100-4103. ScholarBank@NUS Repository. https://doi.org/10.1109/IEMBS.2010.5627289|
|Abstract:||Age-related macular degeneration (AMD) is a leading cause of blindness worldwide. The disease is highly associated with age, and becoming increasingly prevalent in our aging societies. Drusen is a pathological feature that is well-associated with AMD. In this paper, we present a method of detecting drusen in retinal fundus images. The method first determines the location of the macula, which is used as a landmark for a clinical drusen grading overlay. Subsequently, regions of drusen are identified though a maximal region-based pixel intensity approach via RGB and HSV channels. Methods of reducing the effect of retinal and choroidal vessels are also described. The system is tested on a sample set of 16 fundus images from a clinical study, with half having drusen. Experiments on the results show a sensitivity and specificity of 0.75 on the test image set. © 2010 IEEE.|
|Source Title:||2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10|
|Appears in Collections:||Staff Publications|
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