AIMC Topic: Fundus Oculi

Clear Filters Showing 361 to 370 of 512 articles

Development of an artificial intelligence system to classify pathology and clinical features on retinal fundus images.

Clinical & experimental ophthalmology
IMPORTANCE: Artificial intelligence (AI) algorithms are under development for use in diabetic retinopathy photo screening pathways. To be clinically acceptable, such systems must also be able to classify other fundus abnormalities and clinical featur...

Fundus photograph-based deep learning algorithms in detecting diabetic retinopathy.

Eye (London, England)
Remarkable advances in biomedical research have led to the generation of large amounts of data. Using artificial intelligence, it has become possible to extract meaningful information from large volumes of data, in a shorter frame of time, with very ...

Exudate detection in fundus images using deeply-learnable features.

Computers in biology and medicine
Presence of exudates on a retina is an early sign of diabetic retinopathy, and automatic detection of these can improve the diagnosis of the disease. Convolutional Neural Networks (CNNs) have been used for automatic exudate detection, but with poor p...

A novel retinal vessel detection approach based on multiple deep convolution neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detec...

The possibility of the combination of OCT and fundus images for improving the diagnostic accuracy of deep learning for age-related macular degeneration: a preliminary experiment.

Medical & biological engineering & computing
Recently, researchers have built new deep learning (DL) models using a single image modality to diagnose age-related macular degeneration (AMD). Retinal fundus and optical coherence tomography (OCT) images in clinical settings are the most important ...

Development of a deep residual learning algorithm to screen for glaucoma from fundus photography.

Scientific reports
The Purpose of the study was to develop a deep residual learning algorithm to screen for glaucoma from fundus photography and measure its diagnostic performance compared to Residents in Ophthalmology. A training dataset consisted of 1,364 color fundu...

Feature Selection and Parameters Optimization of Support Vector Machines Based on Hybrid Glowworm Swarm Optimization for Classification of Diabetic Retinopathy.

Journal of medical systems
Diabetic Retinopathy (DR) has been a leading cause of blindness in case of human beings falling between the ages of 20 and 74 years. This will have a major influence on both the patient and the society as it can normally influence the humans in their...

An Intelligent Model for Blood Vessel Segmentation in Diagnosing DR Using CNN.

Journal of medical systems
Diabetic retinopathy (DR) is an eye disease, which affects the people who are all having the diabetes for more than 10 years. The ophthalmologist identifies when the dilated eye exam causes severe in any one of the following deviations in the retina:...