CLASSIFICATION OF DIABETIC RETINOPATHY USING IMAGE PROCESSING IN DIABETIC PATIENTS

Diabetic retinopathy is a retinal condition that affects people with diabetes and is the leading cause of blindness in the elderly. It's an asymptomatic illness characterized by abnormalities in blood vessels that might cause them to bleed or leak fluid, resulting in visual distortion. As a res...

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Autores principales:	Madhuri V. Kakade, C. N. Deshmukh
Formato:	article
Lenguaje:	EN
Publicado:	Yeshwantrao Chavan College of Engineering, India 2021
Materias:	retinopathy image processing diabetic patient machine learning Electrical engineering. Electronics. Nuclear engineering TK1-9971 Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/9126246b354f4731b0b5c8169abf6971
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spelling	oai:doaj.org-article:9126246b354f4731b0b5c8169abf69712021-11-23T11:25:09ZCLASSIFICATION OF DIABETIC RETINOPATHY USING IMAGE PROCESSING IN DIABETIC PATIENTS10.46565/jreas.2021.v06i04.0032456-6403https://doaj.org/article/9126246b354f4731b0b5c8169abf69712021-10-01T00:00:00Zhttp://www.mgijournal.com/Data/Issues_AdminPdf/311/ID3.pdfhttps://doaj.org/toc/2456-6403Diabetic retinopathy is a retinal condition that affects people with diabetes and is the leading cause of blindness in the elderly. It's an asymptomatic illness characterized by abnormalities in blood vessels that might cause them to bleed or leak fluid, resulting in visual distortion. As a result, blood vessel extraction is critical in assisting ophthalmologists in detecting this illness at an early stage and preventing vision loss. Diabetes Retinopathy (DR) is a debilitating chronic illness that is one of the primary causes of blindness and vision impairment in diabetic individuals in industrialized nations. According to studies, the majority of instances may be avoided with early identification and treatment. Physicians utilize retinal imaging to detect lesions associated with this illness during eye screening. The amount of pictures that must be manually examined is getting expensive because of the rising number of diabetics.. In this research, we used Image Processing to offer a technique for automatically classifying diabetic retinopathy disease based on retina fundus pictures. For this, we combined a feature extraction approach based on a pre-trained deep neural network model with a machine learning-based support vector machine classification algorithm. In MATLAB software, the proposed system is examined and analyzed.Madhuri V. KakadeC. N. DeshmukhYeshwantrao Chavan College of Engineering, Indiaarticleretinopathyimage processingdiabetic patientmachine learningElectrical engineering. Electronics. Nuclear engineeringTK1-9971Mechanical engineering and machineryTJ1-1570ENJournal of Research in Engineering and Applied Sciences, Vol 6, Iss 4, Pp 159-164 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	retinopathy image processing diabetic patient machine learning Electrical engineering. Electronics. Nuclear engineering TK1-9971 Mechanical engineering and machinery TJ1-1570
spellingShingle	retinopathy image processing diabetic patient machine learning Electrical engineering. Electronics. Nuclear engineering TK1-9971 Mechanical engineering and machinery TJ1-1570 Madhuri V. Kakade C. N. Deshmukh CLASSIFICATION OF DIABETIC RETINOPATHY USING IMAGE PROCESSING IN DIABETIC PATIENTS
description	Diabetic retinopathy is a retinal condition that affects people with diabetes and is the leading cause of blindness in the elderly. It's an asymptomatic illness characterized by abnormalities in blood vessels that might cause them to bleed or leak fluid, resulting in visual distortion. As a result, blood vessel extraction is critical in assisting ophthalmologists in detecting this illness at an early stage and preventing vision loss. Diabetes Retinopathy (DR) is a debilitating chronic illness that is one of the primary causes of blindness and vision impairment in diabetic individuals in industrialized nations. According to studies, the majority of instances may be avoided with early identification and treatment. Physicians utilize retinal imaging to detect lesions associated with this illness during eye screening. The amount of pictures that must be manually examined is getting expensive because of the rising number of diabetics.. In this research, we used Image Processing to offer a technique for automatically classifying diabetic retinopathy disease based on retina fundus pictures. For this, we combined a feature extraction approach based on a pre-trained deep neural network model with a machine learning-based support vector machine classification algorithm. In MATLAB software, the proposed system is examined and analyzed.
format	article
author	Madhuri V. Kakade C. N. Deshmukh
author_facet	Madhuri V. Kakade C. N. Deshmukh
author_sort	Madhuri V. Kakade
title	CLASSIFICATION OF DIABETIC RETINOPATHY USING IMAGE PROCESSING IN DIABETIC PATIENTS
title_short	CLASSIFICATION OF DIABETIC RETINOPATHY USING IMAGE PROCESSING IN DIABETIC PATIENTS
title_full	CLASSIFICATION OF DIABETIC RETINOPATHY USING IMAGE PROCESSING IN DIABETIC PATIENTS
title_fullStr	CLASSIFICATION OF DIABETIC RETINOPATHY USING IMAGE PROCESSING IN DIABETIC PATIENTS
title_full_unstemmed	CLASSIFICATION OF DIABETIC RETINOPATHY USING IMAGE PROCESSING IN DIABETIC PATIENTS
title_sort	classification of diabetic retinopathy using image processing in diabetic patients
publisher	Yeshwantrao Chavan College of Engineering, India
publishDate	2021
url	https://doaj.org/article/9126246b354f4731b0b5c8169abf6971
work_keys_str_mv	AT madhurivkakade classificationofdiabeticretinopathyusingimageprocessingindiabeticpatients AT cndeshmukh classificationofdiabeticretinopathyusingimageprocessingindiabeticpatients
_version_	1718416778938286080

CLASSIFICATION OF DIABETIC RETINOPATHY USING IMAGE PROCESSING IN DIABETIC PATIENTS

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