Various ocular diseases, such as cataract, diabetic retinopathy, and glaucoma have affected
a large proportion of the population worldwide. In ophthalmology, fundus photography is …

This paper concerns the validation of automatic retinal image analysis (ARIA) algorithms.
For reasons of space and consistency, we concentrate on the validation of algorithms …

Objective and quantitative assessment of fundus image quality is essential for the diagnosis
of retinal diseases. The major factors in fundus image quality assessment are image artifact …

Poor-quality retinal images do not allow an accurate medical diagnosis, and it is
inconvenient for a patient to return to a medical center to repeat the fundus photography …

Automated fundus screening is becoming a significant programme of telemedicine in
ophthalmology. Instant quality evaluation of uploaded retinal images could decrease …

A retinal image gradability assessment algorithm based on the fusion of generic image
quality indicators is introduced. Four features quantifying image colour, focus, contrast and …

Fundus images obtained in a telemedicine program are acquired at different sites that are
captured by people who have varying levels of experience. These result in a relatively high …

Morphological changes in the retinal vascular network are associated with future risk of
many systemic and vascular diseases. However, uncertainty over the presence and nature …

Automatic retinal image analysis has remained an important topic of research in the last ten
years. Various algorithms and methods have been developed for analysing retinal images …

Automatically determining image quality of a machine generated image may generate a
local saliency map of the image to obtain a set of unsupervised features. The image is run …