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Applications of deep learning in fundus images: A review
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 …
importance. Due to its powerful performance, deep learning is becoming more and more …
Deep learning for diabetic retinopathy assessments: a literature review
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 …
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
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 …
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
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 …
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
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 …
age people. Automatic DR grading can help ophthalmologists make timely treatment for …
[HTML][HTML] Artificial intelligence for diabetic retinopathy detection: A systematic review
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 …
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
Machine learning and especially deep learning techniques are dominating medical image
and data analysis. This article reviews machine learning approaches proposed for …
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
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 …
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
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 …
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
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 …
ocular diseases based on fundus images. The existing grading methods are usually trained …