Applications of deep learning in fundus images: A review

T Li, W Bo, C Hu, H Kang, H Liu, K Wang, H Fu - Medical Image Analysis, 2021‏ - Elsevier
The use of fundus images for the early screening of eye diseases is of great clinical
importance. Due to its powerful performance, deep learning is becoming more and more …

Deep learning for diabetic retinopathy assessments: a literature review

A Skouta, A Elmoufidi, S Jai-Andaloussi… - Multimedia Tools and …, 2023‏ - Springer
Diabetic retinopathy (DR) is the most important complication of diabetes. Early diagnosis by
performing retinal image analysis helps avoid visual loss or blindness. A computer-aided …

SSMD-UNet: Semi-supervised multi-task decoders network for diabetic retinopathy segmentation

Z Ullah, M Usman, S Latif, A Khan, J Gwak - Scientific Reports, 2023‏ - nature.com
Diabetic retinopathy (DR) is a diabetes complication that can cause vision loss among
patients due to damage to blood vessels in the retina. Early retinal screening can avoid the …

SESV: Accurate medical image segmentation by predicting and correcting errors

Y **e, J Zhang, H Lu, C Shen… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Medical image segmentation is an essential task in computer-aided diagnosis. Despite their
prevalence and success, deep convolutional neural networks (DCNNs) still need to be …

Joint learning of multi-level tasks for diabetic retinopathy grading on low-resolution fundus images

X Wang, M Xu, J Zhang, L Jiang, L Li… - IEEE Journal of …, 2021‏ - ieeexplore.ieee.org
Diabetic retinopathy (DR) is a leading cause of permanent blindness among the working-
age people. Automatic DR grading can help ophthalmologists make timely treatment for …

[HTML][HTML] Artificial intelligence for diabetic retinopathy detection: A systematic review

A Senapati, HK Tripathy, V Sharma… - Informatics in Medicine …, 2024‏ - Elsevier
The incidence of diabetic retinopathy (DR) has increased at a rapid pace in recent years all
over the world. Diabetic eye illness is identified as one of the most common reasons for …

Machine learning techniques for ophthalmic data processing: a review

MH Sarhan, MA Nasseri, D Zapp… - IEEE Journal of …, 2020‏ - ieeexplore.ieee.org
Machine learning and especially deep learning techniques are dominating medical image
and data analysis. This article reviews machine learning approaches proposed for …

[HTML][HTML] Automated microaneurysms detection for early diagnosis of diabetic retinopathy: A Comprehensive review

V Mayya, S Kamath, U Kulkarni - Computer Methods and Programs in …, 2021‏ - Elsevier
Diabetic retinopathy (DR), a chronic disease in which the retina is damaged due to small
vessel damage caused by diabetes mellitus, is one of the leading causes of vision …

CLC-Net: Contextual and local collaborative network for lesion segmentation in diabetic retinopathy images

X Wang, Y Fang, S Yang, D Zhu, M Wang, J Zhang… - Neurocomputing, 2023‏ - Elsevier
Diabetic retinopathy (DR) is the leading cause of blindness among people of working age.
Fundus lesions are clinical signs of DR, and their recognition and delineation are important …

Deep multi-task learning for diabetic retinopathy grading in fundus images

X Wang, M Xu, J Zhang, L Jiang, L Li - Proceedings of the AAAI …, 2021‏ - ojs.aaai.org
Recent years have witnessed the growing interest in disease severity grading, especially for
ocular diseases based on fundus images. The existing grading methods are usually trained …