Related papers: Convolutional Neural Network Model for Diabetic Re…
Diabetic Retinopathy (DR), a prevalent complication in diabetes patients, can lead to vision impairment due to lesions formed on the retina. Detecting DR at an advanced stage often results in irreversible blindness. The traditional process…
In this work, we propose a novel microaneurysm (MA) detection for early diabetic retinopathy screening using color fundus images. Since MA usually the first lesions to appear as an indicator of diabetic retinopathy, accurate detection of MA…
Diabetic Retinopathy (DR) is a retinal disorder that affects the people having diabetes mellitus for a long time (20 years). DR is one of the main reasons for the preventable blindness all over the world. If not detected early the patient…
Deep learning is currently the state-of-the-art for automated detection of referable diabetic retinopathy (DR) from color fundus photographs (CFP). While the general interest is put on improving results through methodological innovations,…
In this work, deep learning algorithms are used to classify fundus images in terms of diabetic retinopathy severity. Six different combinations of two model architectures, the Dense Convolutional Network-121 and the Residual Neural…
Fundus images are widely used for diagnosing various eye diseases, such as diabetic retinopathy, glaucoma, and age-related macular degeneration. However, manual analysis of fundus images is time-consuming and prone to errors. In this…
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world,. In the past few Diabetic Retinopathy (DR) is a leading cause of vision loss in the world. In the past few years, Artificial Intelligence (AI) based approaches have…
All people with diabetes have the risk of developing diabetic retinopathy (DR), a vision-threatening complication. Early detection and timely treatment can reduce the occurrence of blindness due to DR. Computer-aided diagnosis has the…
Diabetic retinopathy is an eye-related pathology creating abnormalities and causing visual impairment, proper treatment of which requires identifying irregularities. This research uses a hemorrhage detection method and compares…
Though deep learning has shown successful performance in classifying the label and severity stage of certain diseases, most of them give few explanations on how to make predictions. Inspired by Koch's Postulates, the foundation in…
Diabetic Retinopathy (DR), a leading cause of vision impairment in individuals with diabetes, affects approximately 34.6% of diabetes patients globally, with the number of cases projected to reach 242 million by 2045. Traditional DR…
People with diabetes are at risk of developing an eye disease called diabetic retinopathy (DR). This disease occurs when high blood glucose levels cause damage to blood vessels in the retina. Computer-aided DR diagnosis is a promising tool…
Diabetic Retinopathy (DR) is a complication of long-standing, unchecked diabetes and one of the leading causes of blindness in the world. This paper focuses on improved and robust methods to extract some of the features of DR, viz. Blood…
In this report, we applied integrated gradients to explaining a neural network for diabetic retinopathy detection. The integrated gradient is an attribution method which measures the contributions of input to the quantity of interest. We…
Diabetic retinopathy is a common complication of diabetes, and monitoring the progression of retinal abnormalities using fundus imaging is crucial. Because the images must be interpreted by a medical expert, it is infeasible to screen all…
Diabetic retinopathy is an ocular condition that affects individuals with diabetes mellitus. It is a common complication of diabetes that can impact the eyes and lead to vision loss. One method for diagnosing diabetic retinopathy is the…
Diabetes is a globally prevalent disease that can cause visible microvascular complications such as diabetic retinopathy and macular edema in the human eye retina, the images of which are today used for manual disease screening. This…
Background: To determine the ability of a commercially available deep learning system, RetCAD v.1.3.1 (Thirona, Nijmegen, The Netherlands) for the automatic detection of referable diabetic retinopathy (DR) on a dataset of colour fundus…
Diabetic Retinopathy is a critical health problem influences 100 million individuals worldwide, and these figures are expected to rise, particularly in Asia. Diabetic Retinopathy is a chronic eye disease which can lead to irreversible…
Diabetic retinopathy (DR) grading is crucial in determining the adequate treatment and follow up of patients, but the screening process can be tiresome and prone to errors. Deep learning approaches have shown promising performance as…