Artificial intelligence: the unstoppable revolution in ophthalmology

D Benet, OJ Pellicer-Valero - Survey of ophthalmology, 2022 - Elsevier
Artificial intelligence (AI) is an unstoppable force that is starting to permeate all aspects of
our society as part of the revolution being brought into our lives (and into medicine) by the …

Artificial intelligence for the detection of age-related macular degeneration in color fundus photographs: A systematic review and meta-analysis

L Dong, Q Yang, RH Zhang, WB Wei - EClinicalMedicine, 2021 - thelancet.com
Background Age-related macular degeneration (AMD) is one of the leading causes of vision
loss in the elderly population. The application of artificial intelligence (AI) provides …

Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs

JI Orlando, H Fu, JB Breda, K Van Keer… - Medical image …, 2020 - Elsevier
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-related macular degeneration detection using deep convolutional neural network

JH Tan, SV Bhandary, S Sivaprasad… - Future Generation …, 2018 - Elsevier
Abstract Age-related Macular Degeneration (AMD) is an eye condition that affects the
elderly. Further, the prevalence of AMD is rising because of the aging population in the …

Optimized deep convolutional neural networks for identification of macular diseases from optical coherence tomography images

Q Ji, J Huang, W He, Y Sun - Algorithms, 2019 - mdpi.com
Finetuning pre-trained deep neural networks (DNN) delicately designed for large-scale
natural images may not be suitable for medical images due to the intrinsic difference …

[HTML][HTML] Multiscale sequential convolutional neural networks for simultaneous detection of fovea and optic disc

B Al-Bander, W Al-Nuaimy, BM Williams… - … Signal Processing and …, 2018 - Elsevier
Detecting the locations of the optic disc and fovea is a crucial task towards developing
automatic diagnosis and screening tools for retinal disease. We propose to address this …

A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification

MRK Mookiah, S Hogg, TJ MacGillivray, V Prathiba… - Medical Image …, 2021 - Elsevier
The eye affords a unique opportunity to inspect a rich part of the human microvasculature
non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are …

Automated age-related macular degeneration and diabetic macular edema detection on oct images using deep learning

S Kaymak, A Serener - 2018 IEEE 14th international conference …, 2018 - ieeexplore.ieee.org
Age-related macular degeneration (AMD) is an eye disease that damages the retina,
causing vision loss. Diabetic macular edema (DME) is also a form of vision loss for diabetic …

Fully automated macular pathology detection in retina optical coherence tomography images using sparse coding and dictionary learning

Y Sun, S Li, Z Sun - Journal of biomedical optics, 2017 - spiedigitallibrary.org
We propose a framework for automated detection of dry age-related macular degeneration
(AMD) and diabetic macular edema (DME) from retina optical coherence tomography (OCT) …

Development and validation of a deep‐learning algorithm for the detection of neovascular age‐related macular degeneration from colour fundus photographs

S Keel, Z Li, J Scheetz, L Robman… - Clinical & …, 2019 - Wiley Online Library
Importance Detection of early onset neovascular age‐related macular degeneration (AMD)
is critical to protecting vision. Background To describe the development and validation of a …