3 results for “Hard Exudates”

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Research ArticleOpen accessIn the keywordsSegmentation of Exudates via Color-based K-means Clustering and Statistical-based ThresholdingAtef Zaki Ghalwash, Aliaa Abdel-Halim Youssif, Ali Mohamed Nabil AllamThis paper provides a novel approach for the problem of detecting the yellowish lesions in the eye fundus images, such as hard and soft exudates, in a fully-automated manner. To solve this problem of segmenting exudates automatically, the fundus image was first converted into the L*a*b* color space to decouple the chromaticity information of the image. Next, the fundus image … …Journal of Computer Science, Vol. 13, Issue 10 · 14 Oct 2017 · 7,725 accessesView PDF Cite

Research ArticleOpen accessIn the abstractRetinal Image Analysis for Abnormality Detection-An OverviewR. Karthikeyan, P. AlliProblem statement: Classification plays a major role in retinal image analysis for detecting the various abnormalities in retinal images. Classification refers to one of the mining concepts using supervised or unsupervised learning techniques. Approach: Diabetic retinopathy is one of the common complications of diabetes. Unfortunately, in many cases, the patient is not aware any symptoms until it is too late … …Journal of Computer Science, Vol. 8, Issue 3 · 24 Jan 2012 · 7,280 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAdaptive Neuro-Fuzzy Inference System Approach for the Automatic Screening of Diabetic Retinopathy in Fundus ImagesS. Kavitha, K. DuraiswamyProblem statement: Diabetic retinopathy is one of the most significant factors contributing to blindness and so early diagnosis and timely treatment is particularly important to prevent visual loss. Approach: An integrated approach for extraction of blood vessels and exudates detection was proposed to screen diabetic retinopathy. An automated classifier was developed based on Adaptive Neuro-Fuzzy Inference System (ANFIS) to differentiate … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,785 accessesView PDF Cite