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 …
A comprehensive review of deep learning strategies in retinal disease diagnosis using fundus images
In recent years, there has been an unprecedented growth in computer vision and deep
learning implementation owing to the exponential rise of computation infrastructure. The …
learning implementation owing to the exponential rise of computation infrastructure. The …
Modified U-net architecture for segmentation of skin lesion
Dermoscopy images can be classified more accurately if skin lesions or nodules are
segmented. Because of their fuzzy borders, irregular boundaries, inter-and intra-class …
segmented. Because of their fuzzy borders, irregular boundaries, inter-and intra-class …
Explainable framework for Glaucoma diagnosis by image processing and convolutional neural network synergy: analysis with doctor evaluation
Glaucoma causes blindness in long-time untreated cases. So, its early diagnosis is very
important. Moving from that, there have been lots of Deep Learning oriented studies to …
important. Moving from that, there have been lots of Deep Learning oriented studies to …
Synergic deep learning model–based automated detection and classification of brain intracranial hemorrhage images in wearable networks
With an intention of improving healthcare performance, wearable technology products utilize
several digital health sensors which are classically linked into sensor networks, including …
several digital health sensors which are classically linked into sensor networks, including …
A novel computer-aided diagnostic system for early detection of diabetic retinopathy using 3D-OCT higher-order spatial appearance model
Early diagnosis of diabetic retinopathy (DR) is of critical importance to suppress severe
damage to the retina and/or vision loss. In this study, an optical coherence tomography …
damage to the retina and/or vision loss. In this study, an optical coherence tomography …
Edldr: An ensemble deep learning technique for detection and classification of diabetic retinopathy
Diabetic retinopathy (DR) is an ophthalmological disease that causes damage in the blood
vessels of the eye. DR causes clotting, lesions or haemorrhage in the light-sensitive region …
vessels of the eye. DR causes clotting, lesions or haemorrhage in the light-sensitive region …
[HTML][HTML] A novel few-shot classification framework for diabetic retinopathy detection and grading
Diabetes Retinopathy (DR) is a major microvascular complication of diabetes. Computer-
Aided Diagnosis (CAD) tools for DR management are primarily developed using Artificial …
Aided Diagnosis (CAD) tools for DR management are primarily developed using Artificial …
Untangling computer-aided diagnostic system for screening diabetic retinopathy based on deep learning techniques
Diabetic Retinopathy (DR) is a predominant cause of visual impairment and loss.
Approximately 285 million worldwide population is affected with diabetes, and one-third of …
Approximately 285 million worldwide population is affected with diabetes, and one-third of …
An enhanced swarm optimization-based deep neural network for diabetic retinopathy classification in fundus images
AM Dayana, WRS Emmanuel - Multimedia Tools and Applications, 2022 - Springer
Diabetic Retinopathy (DR) is one of the long-lasting Diabetic retinal disorders that leads to
vision impairment eventually blindness in most of the working-age population. The process …
vision impairment eventually blindness in most of the working-age population. The process …