Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis
Deep learning (DL) has the potential to transform medical diagnostics. However, the
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …
Ophthalmic diagnosis using deep learning with fundus images–A critical review
An overview of the applications of deep learning for ophthalmic diagnosis using retinal
fundus images is presented. We describe various retinal image datasets that can be used for …
fundus images is presented. We describe various retinal image datasets that can be used for …
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 …
Primary open-angle glaucoma preferred practice pattern®
SJ Gedde, K Vinod, MM Wright, KW Muir, JT Lind… - Ophthalmology, 2021 - Elsevier
Background Primary open angle glaucoma (POAG) is a chronic, progressive ocular disease
causing loss of the optic nerve rim and retinal nerve fiber layer (RNFL) with associated …
causing loss of the optic nerve rim and retinal nerve fiber layer (RNFL) with associated …
A combined convolutional and recurrent neural network for enhanced glaucoma detection
Glaucoma, a leading cause of blindness, is a multifaceted disease with several patho-
physiological features manifesting in single fundus images (eg, optic nerve cupping) as well …
physiological features manifesting in single fundus images (eg, optic nerve cupping) as well …
Detection of anaemia from retinal fundus images via deep learning
A Mitani, A Huang, S Venugopalan… - Nature biomedical …, 2020 - nature.com
Owing to the invasiveness of diagnostic tests for anaemia and the costs associated with
screening for it, the condition is often undetected. Here, we show that anaemia can be …
screening for it, the condition is often undetected. Here, we show that anaemia can be …
[HTML][HTML] Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs
Purpose To develop and validate a deep learning (DL) algorithm that predicts referable
glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color …
glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color …
Isocitrate dehydrogenase (IDH) status prediction in histopathology images of gliomas using deep learning
Mutations in isocitrate dehydrogenase genes IDH1 and IDH2 are frequently found in diffuse
and anaplastic astrocytic and oligodendroglial tumours as well as in secondary …
and anaplastic astrocytic and oligodendroglial tumours as well as in secondary …
Weak label based Bayesian U-Net for optic disc segmentation in fundus images
Fundus images have been widely used in routine examinations of ophthalmic diseases. For
some diseases, the pathological changes mainly occur around the optic disc area; therefore …
some diseases, the pathological changes mainly occur around the optic disc area; therefore …
Machine learning applied to retinal image processing for glaucoma detection: review and perspective
Introduction This is a systematic review on the main algorithms using machine learning (ML)
in retinal image processing for glaucoma diagnosis and detection. ML has proven to be a …
in retinal image processing for glaucoma diagnosis and detection. ML has proven to be a …