Automatic Detection of Diabetic Retinopathy using Image Processing
نویسندگان
چکیده
منابع مشابه
Early Detection of Diabetic Retinopathy in Fluorescent Angiography Retinal Images Using Image Processing Methods
Introduction: Diabetic retinopathy (DR) is the single largest cause of sight loss and blindness in the working age population of Western countries; it is the most common cause of blindness in adults between 20 and 60 years of age. Early diagnosis of DR is critical for preventing vision loss so early detection of microaneurysms (MAs) as the first signs of DR is important. This paper addresses th...
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Diabetic retinopathy (DR) is a diabetes related eye disease which occurs when blood vessels in the retina become swelled and leaks fluid which ultimately leads to vision loss. Several image processing techniques including Image Enhancement, Segmentation, Image Fusion, Morphology, Classification, and registration has been developed for the early detection of DR on the basis of features such as b...
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introduction: diabetic retinopathy (dr) is the single largest cause of sight loss and blindness in the working age population of western countries; it is the most common cause of blindness in adults between 20 and 60 years of age. early diagnosis of dr is critical for preventing vision loss so early detection of microaneurysms (mas) as the first signs of dr is important. this paper addresses th...
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Diabetic retinopathy is the leading disease that occurs due to the diabetic mellitus. Several computer aided diagnosis helps ophthalmologists to diagnosis the severity of retinopathy but still the annual screening of retinal images is very important to detect diabetic retinopathy by an automatic assessment system for analyzing the images through region based method, filtering techniques, templa...
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Automatic diagnosis and display of diabetic retinopathy from images of retina using the techniques of digital signal and image processing is presented in this paper. The acquired images undergo pre-processing to equalize uneven illumination associated with the acquired fundus images. This stage also removes noise present in the image. Segmentation stage clusters the image into two distinct clas...
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ژورنال
عنوان ژورنال: Research in Computing Science
سال: 2016
ISSN: 1870-4069
DOI: 10.13053/rcs-123-1-4