In the realm of medical diagnosis, the challenge posed by retinal diseases is considerable,
given their potential to complicate vision and overall ocular health. A promising avenue for …

Optical coherence tomography (OCT) images coupled with many learning techniques have
been developed to diagnose retinal disorders. This work aims to develop a novel framework …

Purpose Early detection of retinal disorders using optical coherence tomography (OCT)
images can prevent vision loss. Since manual screening can be time-consuming, tedious …

In this paper, we deconstruct and demonstrate a detection framework to classify Retinal
Optical Coherence Tomography (OCT) images across three classes namely, Diabetic …

Purpose With the aging population and the global diabetes epidemic, the prevalence of age-
related macular degeneration (AMD) and diabetic macular edema (DME) diseases which …

A new system based on binary Deep Learning (DL) convolutional neural networks has been
developed to recognize specific retinal abnormality signs on Optical Coherence …

With the development of convolutional neural network, deep learning has shown its success
for retinal disease detection from optical coherence tomography (OCT) images. However …

Diagnosing different retinal diseases from Spectral Domain Optical Coherence Tomography
(SD-OCT) images is a challenging task. Different automated approaches such as image …

Optical coherence tomography (OCT) scanning is useful in detecting various retinal
diseases. However, there are not enough ophthalmologists who can diagnose retinal OCT …

Diabetic retinopathy occurs due to damage to the blood vessels in the retina, and it is a
major health problem in recent years that progresses slowly without recognizable symptoms …