Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective
The simultaneous maturation of multiple digital and telecommunications technologies in
2020 has created an unprecedented opportunity for ophthalmology to adapt to new models …
2020 has created an unprecedented opportunity for ophthalmology to adapt to new models …
A scoping review of transfer learning research on medical image analysis using ImageNet
Objective Employing transfer learning (TL) with convolutional neural networks (CNNs), well-
trained on non-medical ImageNet dataset, has shown promising results for medical image …
trained on non-medical ImageNet dataset, has shown promising results for medical image …
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) …
Development and validation of a deep learning system to detect glaucomatous optic neuropathy using fundus photographs
Importance A deep learning system (DLS) that could automatically detect glaucomatous
optic neuropathy (GON) with high sensitivity and specificity could expedite screening for …
optic neuropathy (GON) with high sensitivity and specificity could expedite screening for …
A large-scale database and a CNN model for attention-based glaucoma detection
Glaucoma is one of the leading causes of irreversible vision loss. Many approaches have
recently been proposed for automatic glaucoma detection based on fundus images …
recently been proposed for automatic glaucoma detection based on fundus images …
Attention based glaucoma detection: A large-scale database and CNN model
Recently, the attention mechanism has been successfully applied in convolutional neural
networks (CNNs), significantly boosting the performance of many computer vision tasks …
networks (CNNs), significantly boosting the performance of many computer vision tasks …
Efficacy of a deep learning system for detecting glaucomatous optic neuropathy based on color fundus photographs
Purpose To assess the performance of a deep learning algorithm for detecting referable
glaucomatous optic neuropathy (GON) based on color fundus photographs. Design A deep …
glaucomatous optic neuropathy (GON) based on color fundus photographs. Design A deep …
[HTML][HTML] Development and validation of deep learning models for screening multiple abnormal findings in retinal fundus images
Purpose To develop and evaluate deep learning models that screen multiple abnormal
findings in retinal fundus images. Design Cross-sectional study. Participants For the …
findings in retinal fundus images. Design Cross-sectional study. Participants For the …
A novel hybrid approach based on deep CNN to detect glaucoma using fundus imaging
Glaucoma is one of the eye diseases stimulated by the fluid pressure that increases in the
eyes, damaging the optic nerves and causing partial or complete vision loss. As Glaucoma …
eyes, damaging the optic nerves and causing partial or complete vision loss. As Glaucoma …
Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Background With the advancement of powerful image processing and machine learning
techniques, Computer Aided Diagnosis has become ever more prevalent in all fields of …
techniques, Computer Aided Diagnosis has become ever more prevalent in all fields of …