AIMC Topic: Fundus Oculi

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Neovascularization Detection and Localization in Fundus Images Using Deep Learning.

Sensors (Basel, Switzerland)
Proliferative Diabetic Retinopathy (PDR) is a severe retinal disease that threatens diabetic patients. It is characterized by neovascularization in the retina and the optic disk. PDR clinical features contain highly intense retinal neovascularization...

DeepUWF: An Automated Ultra-Wide-Field Fundus Screening System via Deep Learning.

IEEE journal of biomedical and health informatics
The emerging ultra-wide field of view (UWF) fundus color imaging is a powerful tool for fundus screening. However, manual screening is labor-intensive and subjective. Based on 2644 UWF images, a set of early fundus abnormal screening system named Dee...

Accuracy of automated machine learning in classifying retinal pathologies from ultra-widefield pseudocolour fundus images.

The British journal of ophthalmology
AIMS: Automated machine learning (AutoML) is a novel tool in artificial intelligence (AI). This study assessed the discriminative performance of AutoML in differentiating retinal vein occlusion (RVO), retinitis pigmentosa (RP) and retinal detachment ...

Automated detection of retinal exudates and drusen in ultra-widefield fundus images based on deep learning.

Eye (London, England)
BACKGROUND: Retinal exudates and/or drusen (RED) can be signs of many fundus diseases that can lead to irreversible vision loss. Early detection and treatment of these diseases are critical for improving vision prognosis. However, manual RED screenin...

Deep learning-assisted (automatic) diagnosis of glaucoma using a smartphone.

The British journal of ophthalmology
BACKGROUND/AIMS: To validate a deep learning algorithm to diagnose glaucoma from fundus photography obtained with a smartphone.

An interpretable multiple-instance approach for the detection of referable diabetic retinopathy in fundus images.

Scientific reports
Diabetic retinopathy (DR) is one of the leading causes of vision loss across the world. Yet despite its wide prevalence, the majority of affected people lack access to the specialized ophthalmologists and equipment required for monitoring their condi...

Artificial Intelligence-Assisted Early Detection of Retinitis Pigmentosa - the Most Common Inherited Retinal Degeneration.

Journal of digital imaging
The purpose of this study was to detect the presence of retinitis pigmentosa (RP) based on color fundus photographs using a deep learning model. A total of 1670 color fundus photographs from the Taiwan inherited retinal degeneration project and Natio...

Automatic detection of papilledema through fundus retinal images using deep learning.

Microscopy research and technique
Papilledema is a syndrome of the retina in which retinal optic nerve is inflated by elevation of intracranial pressure. The papilledema abnormalities such as retinal nerve fiber layer (RNFL) opacification may lead to blindness. These abnormalities co...

Self-Supervised Feature Learning and Phenotyping for Assessing Age-Related Macular Degeneration Using Retinal Fundus Images.

Ophthalmology. Retina
OBJECTIVE: Diseases such as age-related macular degeneration (AMD) are classified based on human rubrics that are prone to bias. Supervised neural networks trained using human-generated labels require labor-intensive annotations and are restricted to...

Deep learning-based automated detection for diabetic retinopathy and diabetic macular oedema in retinal fundus photographs.

Eye (London, England)
OBJECTIVES: To present and validate a deep ensemble algorithm to detect diabetic retinopathy (DR) and diabetic macular oedema (DMO) using retinal fundus images.