Transfer learning with convolutional neural networks for diabetic retinopathy image classification. A review
I Kandel, M Castelli - Applied Sciences, 2020 - mdpi.com
Diabetic retinopathy (DR) is a dangerous eye condition that affects diabetic patients. Without
early detection, it can affect the retina and may eventually cause permanent blindness. The …
early detection, it can affect the retina and may eventually cause permanent blindness. The …
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 …
performing retinal image analysis helps avoid visual loss or blindness. A computer-aided …
Transfer learning based robust automatic detection system for diabetic retinopathy grading
Diabetic retinopathy (DR) can be categorized on the basis of prolonged complication in the
retinal blood vessels which may lead to severe blindness. Early stage prediction and …
retinal blood vessels which may lead to severe blindness. Early stage prediction and …
Deep learning–based diabetic retinopathy severity grading system employing quadrant ensemble model
The diabetic retinopathy accounts in the deterioration of retinal blood vessels leading to a
serious compilation affecting the eyes. The automated DR diagnosis frameworks are …
serious compilation affecting the eyes. The automated DR diagnosis frameworks are …
Features extraction using encoded local binary pattern for detection and grading diabetic retinopathy
MA Berbar - Health Information Science and Systems, 2022 - Springer
Introduction Reliable computer diagnosis of diabetic retinopathy (DR) is needed to rescue
many with diabetes who may be under threat of blindness. This research aims to detect the …
many with diabetes who may be under threat of blindness. This research aims to detect the …
On the robustness of pretraining and self-supervision for a deep learning-based analysis of diabetic retinopathy
There is an increasing number of medical use-cases where classification algorithms based
on deep neural networks reach performance levels that are competitive with human medical …
on deep neural networks reach performance levels that are competitive with human medical …
To pretrain or not? A systematic analysis of the benefits of pretraining in diabetic retinopathy
There is an increasing number of medical use cases where classification algorithms based
on deep neural networks reach performance levels that are competitive with human medical …
on deep neural networks reach performance levels that are competitive with human medical …
A hybrid deep learning-metaheuristic model for diagnosis of diabetic retinopathy
International Diabetes Federation (IDF) reports that diabetes is a rapidly growing illness.
About 463 million adults between 20-79 years have diabetes. There are also millions of …
About 463 million adults between 20-79 years have diabetes. There are also millions of …
A systematic review of transfer learning-based approaches for diabetic retinopathy detection
Diabetic retinopathy, which is extreme visual blindness due to diabetes, has become an
alarming issue worldwide. Early and accurate detection of DR is necessary to prevent the …
alarming issue worldwide. Early and accurate detection of DR is necessary to prevent the …
An optimized deep learning based technique for grading and extraction of diabetic retinopathy severities
Q Zhang, J Luo, K Cengiz - Informatica, 2021 - informatica.si
Abstract The prognosis of Diabetic Retinopathy (DR) requires regular eye examinations, as
ophthalmologists depends on fundus segmentation to treat DR pathologies. Automated …
ophthalmologists depends on fundus segmentation to treat DR pathologies. Automated …