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AN EFFICIENT APP. FOR DETECTING DIABETIC RETINOPATHY. (DR APP)
AN EFFICIENT APP. FOR DETECTING DIABETIC RETINOPATHY. (DR APP)
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机译：高效的应用程序。用于检测糖尿病性视网膜病变。 （DR APP）
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摘要
Abstract Advances in the eye care telemedicine system aid the diabetic patients in remote areas to stop the unwanted visit to ophthalmologist, reduces overall cost, time and money. Diabetic Retinopathy, which is the primary cause of sight loss, has the most common symptoms like microaneurysms, hemorrhages, cotton-wool spots, exudates and druses. In this work, an efficient approach for the automatic detection of Diabetic Retinopathy in color retinal images is proposed and validated. The color retinal images captured from the diabetic patients are partitioned into segments by modified K-means and hierarchical segmentation. A bag of features based on color, visual appearance and texture are extracted from each segment. Finally, the best features are classified with the help of Partial Least Square (PLS) classifier. The classifier performance is validated on two publicly available databanks. The developed method requires an average execution time of 12 sec. This application outperforms the existing approaches with high robustness and efficiency.
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