Complications of Sight Threatening Diabetic Retinopathy: A Review

Malik, Navneet

doi:10.30534/ijatcse/2019/09842019

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…Human retina is most important part and affected by diabetics [12]. The retinal tissue consists of layers in the back of the eye that senses light and sends signals to our brain.…”

Section: Introductionmentioning

confidence: 99%

Classification of Retinal Pathologies using Convolutional Neural Network

Amaladevi¹

2020

IJATCSE

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Deep Learning technique has emerged as a successful approach in applications with complex functions. It is used in the areas of computer vision, speech recognition and image processing applications. The most popular deep learning architecture is Convolution Neural Network (CNN). The proposed method a pre-trained CNN based on GoogLeNet and VGGNet is used to classify the retinal diseases such as Age-Related Macular Degeneration (AMD) and Diabetic Macular Edema (DME). Spectral Domain Optical Coherence Tomography (SD-OCT) images are used for identifying the retinal pathologies. Pre-trained GoogLeNet and VGGNet predict the nature of all the subjects of the test images. 94% of accuracy, 95% specificity and 96% sensitivity for the three classes are achieved using GoogLeNet and 96% of accuracy, 99% specificity and 96% of sensitivity for the three classes are achieved using VGGNet.

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“…Human retina is most important part and affected by diabetics [12]. The retinal tissue consists of layers in the back of the eye that senses light and sends signals to our brain.…”

Section: Introductionmentioning

confidence: 99%

Classification of Retinal Pathologies using Convolutional Neural Network

Amaladevi¹

2020

IJATCSE

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“…It arranges at that posterior pole fleeting of the optic plate. The fovea characterizes the focal point of the macula Furthermore maybe those districts of most elevated visual sharpness [10][9] [4].…”

Section: Introductionmentioning

confidence: 99%

An Effective Approach to Classify Retina Images for Diabetic Retinopathy

Rachapudi¹

2019

IJATCSE

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Diabetic Retinopathy (DR) is one of the complications that leads to visual impairment among patients who are suffering from diabetes mellitus. Diabetic Retinopathy (DR) is the abnormal swelling of new blood vessels in the retina. In this paper, a different novel and effective technique implemented to identify the abnormal new blood vessel by pre-processing the fundus images of the retina of the diabetic patient by utilizing difference inadequate adaptative histogram equalization (CLAHE). These blood vessels are enriched by implementing morphological process structures built on figure, brightness, region divergence are removed by enhancing the image and also categorizing as normal (or) abnormal by Support Vector Machine (SVM) algorithm.

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Complications of Sight Threatening Diabetic Retinopathy: A Review

Cited by 2 publications

References 26 publications

Classification of Retinal Pathologies using Convolutional Neural Network

Classification of Retinal Pathologies using Convolutional Neural Network

An Effective Approach to Classify Retina Images for Diabetic Retinopathy

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