Diabetic retinopathy (DR) results in vision loss if not treated early. A computer-aided
diagnosis (CAD) system based on retinal fundus images is an efficient and effective method …

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 …

Deep learning is quickly becoming the leading methodology for medical image analysis.
Given a large medical archive, where each image is associated with a diagnosis, efficient …

Retinal image analysis holds an imperative position for the identification and classification of
retinal diseases such as Diabetic Retinopathy (DR), Age Related Macular Degeneration …

Deep learning (DL) enables the creation of computational models comprising multiple
processing layers that learn data representations at multiple levels of abstraction. In the …

The prevalence of Alzheimer's disease (AD) in the growing elderly population makes
accurately predicting AD progression crucial. Due to AD's complex etiology and …

Retinal vessels identification and localization aim to separate the different retinal
vasculature structure tissues, either wide or narrow ones, from the fundus image background …

Vision impairment due to pathological damage of the retina can largely be prevented
through periodic screening using fundus color imaging. However the challenge with large …

Recently, there has been an advancement in the development of innovative computer-aided
techniques for the segmentation and classification of retinal vessels, the application of which …

Retinal illnesses such as diabetic retinopathy (DR) are the main causes of vision loss. In the
early recognition of eye diseases, the segmentation of blood vessels in retina images plays …