AIMC Topic: Fundus Oculi

Clear Filters Showing 221 to 230 of 491 articles

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.

Deep learning for diabetic retinopathy detection and classification based on fundus images: A review.

Computers in biology and medicine
Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading cause of blindness globally. Early detection and treatment are necessary in order to delay or avoid vision deterioration and vision loss. To that end, many art...

Diagnosis of central serous chorioretinopathy by deep learning analysis of en face images of choroidal vasculature: A pilot study.

PloS one
PURPOSE: To diagnose central serous chorioretinopathy (CSC) by deep learning (DL) analyses of en face images of the choroidal vasculature obtained by optical coherence tomography (OCT) and to analyze the regions of interest for the DL from heatmaps.

A high resolution representation network with multi-path scale for retinal vessel segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automatic retinal vessel segmentation (RVS) in fundus images is expected to be a vital step in the early image diagnosis of ophthalmologic diseases. However, it is a challenging task to detect the retinal vessel accurately ...

Hemorrhage Detection Based on 3D CNN Deep Learning Framework and Feature Fusion for Evaluating Retinal Abnormality in Diabetic Patients.

Sensors (Basel, Switzerland)
Diabetic retinopathy (DR) is the main cause of blindness in diabetic patients. Early and accurate diagnosis can improve the analysis and prognosis of the disease. One of the earliest symptoms of DR are the hemorrhages in the retina. Therefore, we pro...