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] Artificial intelligence in retina
U Schmidt-Erfurth, A Sadeghipour, BS Gerendas… - Progress in retinal and …, 2018 - Elsevier
Major advances in diagnostic technologies are offering unprecedented insight into the
condition of the retina and beyond ocular disease. Digital images providing millions of …
condition of the retina and beyond ocular disease. Digital images providing millions of …
Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Glaucoma is one of the leading causes of irreversible but preventable blindness in working
age populations. Color fundus photography (CFP) is the most cost-effective imaging …
age populations. Color fundus photography (CFP) is the most cost-effective imaging …
Indian diabetic retinopathy image dataset (IDRiD): a database for diabetic retinopathy screening research
Diabetic Retinopathy is the most prevalent cause of avoidable vision impairment, mainly
affecting the working-age population in the world. Recent research has given a better …
affecting the working-age population in the world. Recent research has given a better …
[HTML][HTML] Diabetic retinopathy detection through deep learning techniques: A review
Diabetic Retinopathy (DR) is a common complication of diabetes mellitus, which causes
lesions on the retina that effect vision. If it is not detected early, it can lead to blindness …
lesions on the retina that effect vision. If it is not detected early, it can lead to blindness …
Dual encoder-based dynamic-channel graph convolutional network with edge enhancement for retinal vessel segmentation
Retinal vessel segmentation with deep learning technology is a crucial auxiliary method for
clinicians to diagnose fundus diseases. However, the deep learning approaches inevitably …
clinicians to diagnose fundus diseases. However, the deep learning approaches inevitably …
A lightweight CNN for Diabetic Retinopathy classification from fundus images
Diabetic Retinopathy (DR) is a complication of diabetes mellitus that damages blood vessel
networks in the retina. This is a serious vision-threatening issue in most diabetic subjects …
networks in the retina. This is a serious vision-threatening issue in most diabetic subjects …
Automatic segmentation of nine retinal layer boundaries in OCT images of non-exudative AMD patients using deep learning and graph search
We present a novel framework combining convolutional neural networks (CNN) and graph
search methods (termed as CNN-GS) for the automatic segmentation of nine layer …
search methods (termed as CNN-GS) for the automatic segmentation of nine layer …
PAPILA: Dataset with fundus images and clinical data of both eyes of the same patient for glaucoma assessment
Glaucoma is one of the ophthalmological diseases that frequently causes loss of vision in
today's society. Previous studies assess which anatomical parameters of the optic nerve can …
today's society. Previous studies assess which anatomical parameters of the optic nerve can …
Performance of deep learning architectures and transfer learning for detecting glaucomatous optic neuropathy in fundus photographs
The ability of deep learning architectures to identify glaucomatous optic neuropathy (GON)
in fundus photographs was evaluated. A large database of fundus photographs (n= 14,822) …
in fundus photographs was evaluated. A large database of fundus photographs (n= 14,822) …