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 …
[HTML][HTML] Deep learning for diabetic retinopathy detection and classification based on fundus images: A review
Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading
cause of blindness globally. Early detection and treatment are necessary in order to delay or …
cause of blindness globally. Early detection and treatment are necessary in order to delay or …
[HTML][HTML] Diabetic retinopathy identification using parallel convolutional neural network based feature extractor and ELM classifier
Diabetic retinopathy (DR) is an incurable retinal condition caused by excessive blood sugar
that, if left untreated, can result in even blindness. A novel automated technique for DR …
that, if left untreated, can result in even blindness. A novel automated technique for DR …
Classification of diabetic retinopathy with feature selection over deep features using nature-inspired wrapper methods
M Canayaz - Applied Soft Computing, 2022 - Elsevier
Diabetic retinopathy (DR) is the most common cause of blindness in middle-aged people. It
shows that an automatic image evaluation system is needed in the diagnosis of this disease …
shows that an automatic image evaluation system is needed in the diagnosis of this disease …
Multi-scale attention network for diabetic retinopathy classification
MT Al-Antary, Y Arafa - IEEE Access, 2021 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) is a highly prevalent complication of diabetes mellitus, which
causes lesions on the retina that affect vision which may lead to blindness if it is not detected …
causes lesions on the retina that affect vision which may lead to blindness if it is not detected …
A systematic review on diabetic retinopathy detection using deep learning techniques
Segmentation is an essential requirement to accurately access diabetic retinopathy (DR)
and it becomes extremely time-consuming and challenging to detect manually. As a result …
and it becomes extremely time-consuming and challenging to detect manually. As a result …
A systematic literature review of machine learning based risk prediction models for diabetic retinopathy progression
Diabetic Retinopathy (DR) is the most popular debilitating impairment of diabetes and it
progresses symptom-free until a sudden loss of vision occurs. Understanding the …
progresses symptom-free until a sudden loss of vision occurs. Understanding the …
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 …
Grading diabetic retinopathy using multiresolution based CNN
Diabetic Retinopathy (DR) refers to a medical condition that affects the eye; it occurs due to
diabetes, and, if not detected early on, results in a reduction of visual capacity and may even …
diabetes, and, if not detected early on, results in a reduction of visual capacity and may even …
Image quality-aware diagnosis via meta-knowledge co-embedding
Medical images usually suffer from image degradation in clinical practice, leading to
decreased performance of deep learning-based models. To resolve this problem, most …
decreased performance of deep learning-based models. To resolve this problem, most …