This paper presents an automatic application that provides several retinal image analysis functionalities, namely vessel segmentation, vessel width estimation, artery/vein classification and optic disc segmentation. A pipeline of these methods allows the computation of important vessel related indexes, namely the Central Retinal Arteriolar Equivalent (CRAE), Central Retinal Venular Equivalent (...

Retinal images are analyzed to identify the glaucoma or the diabetic disease. The accuracy of disease detection depends on the extracted features. In this paper, segmentation and mathematical filters based statistical approach is presented to identify the retinal disease. At first stage of this statistical model, the features from retinal image are extracted using segmentation method. This segm...

Automated fundus image analysis plays an important role in the computer aided diagnosis of ophthalmologic disorders. A lot of eye disorders, as well as cardiovascular disorders, are known to be related with retinal vasculature changes. Many studies has been done to explore these relationships. However, most of the studies are based on limited data obtained using manual or semi-automated methods...

Retinal image analysis is becoming eminent as a nonintrusive diagnosis method in modern ophthalmology. This paper is mainly focused on the early diagnosis of diabetic retinopathy by analysing and detecting of vascular structures in retinal images. When small vessels in the retina have high level of glucose, it produces blur vision which eventually leads to blindness. Usually retinal images are ...

Retinal image alignment is fundamental to many applications in diagnosis of eye diseases. In this paper, we address the problem of landmark matching based retinal image alignment. We propose a novel landmark matching formulation by enforcing sparsity in the correspondence matrix and offer its solutions based on linear programming. The proposed formulation not only enables a joint estimation of ...

PURPOSE To assess the suitability of retinal images held in the UK Biobank--the largest retinal data repository in a prospective population-based cohort--for computer assisted vascular morphometry, generating measures that are commonly investigated as candidate biomarkers of systemic disease. METHODS Non-mydriatic fundus images from both eyes of 2,690 participants--people with a self-reported...

Retinal vasculature analysis is important for the early diagnostics of various eye and systemic diseases, making it a potentially useful biomarker, especially for resource-limited regions and countries. Here we developed a smartphone-based retinal image analysis system for point-of-care diagnostics that is able to load a fundus image, segment retinal vessels, analyze individual vessel width, an...

We present an automatic image processing algorithm to detect hard exudates. Automatic detection of hard exudates from retinal images is an important problem since hard exudates are associated with diabetic retinopathy and have been found to be one of the most prevalent earliest signs of retinopathy. The algorithm is based on Fisher's linear discriminant analysis and makes use of colour informat...