Deep learning for diabetic retinopathy analysis: a review, research challenges, and future directions
Deep learning (DL) enables the creation of computational models comprising multiple
processing layers that learn data representations at multiple levels of abstraction. In the …
processing layers that learn data representations at multiple levels of abstraction. In the …
Automated detection and diagnosis of diabetic retinopathy: A comprehensive survey
V Lakshminarayanan, H Kheradfallah, A Sarkar… - Journal of …, 2021 - mdpi.com
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world. In the past few
years, artificial intelligence (AI) based approaches have been used to detect and grade DR …
years, artificial intelligence (AI) based approaches have been used to detect and grade DR …
Using deep learning architectures for detection and classification of diabetic retinopathy
Diabetic retinopathy (DR) is a common complication of long-term diabetes, affecting the
human eye and potentially leading to permanent blindness. The early detection of DR is …
human eye and potentially leading to permanent blindness. The early detection of DR is …
Development of revised ResNet-50 for diabetic retinopathy detection
CL Lin, KC Wu - BMC bioinformatics, 2023 - Springer
Background Diabetic retinopathy (DR) produces bleeding, exudation, and new blood vessel
formation conditions. DR can damage the retinal blood vessels and cause vision loss or …
formation conditions. DR can damage the retinal blood vessels and cause vision loss or …
[HTML][HTML] Towards automated eye cancer classification via VGG and ResNet networks using transfer learning
DF Santos-Bustos, BM Nguyen, HE Espitia - Engineering Science and …, 2022 - Elsevier
Complex tasks such as disease diagnosis or semantic segmentation are now becoming
easier to tackle in part due to increasing advances in computing and storage. This study …
easier to tackle in part due to increasing advances in computing and storage. This study …
A literature review of early-stage diabetic retinopathy detection using deep learning and evolutionary computing techniques
Soft computing approaches are contributing to various areas of real-world problems. These
techniques are being used in optimization problems, feature selection, classification as well …
techniques are being used in optimization problems, feature selection, classification as well …
Deep learning based computer-aided automatic prediction and grading system for diabetic retinopathy
Diabetic Retinopathy (DR) is a consequence of diabetes mellitus that results in damage to
the retina's blood vessel networks. It is now the major cause of irreversible blindness among …
the retina's blood vessel networks. It is now the major cause of irreversible blindness among …
Wavelet scattering transform application in classification of retinal abnormalities using OCT images
To assist ophthalmologists in diagnosing retinal abnormalities, Computer Aided Diagnosis
has played a significant role. In this paper, a particular Convolutional Neural Network based …
has played a significant role. In this paper, a particular Convolutional Neural Network based …
The role of different retinal imaging modalities in predicting progression of diabetic retinopathy: A survey
Diabetic retinopathy (DR) is a devastating condition caused by progressive changes in the
retinal microvasculature. It is a leading cause of retinal blindness in people with diabetes …
retinal microvasculature. It is a leading cause of retinal blindness in people with diabetes …
An Improved Model for Diabetic Retinopathy Detection by using Transfer Learning and Ensemble Learning
MSH Talukder, AK Sarkar, S Akter… - arXiv preprint arXiv …, 2023 - arxiv.org
Diabetic Retinopathy (DR) is an ocular condition caused by a sustained high level of sugar
in the blood, which causes the retinal capillaries to block and bleed, causing retinal tissue …
in the blood, which causes the retinal capillaries to block and bleed, causing retinal tissue …