Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …

Retinal vessel segmentation algorithms are a fundamental component of automatic retinal
disease screening systems. This work examines the blood vessel segmentation …

Automatic segmentation of retinal vessels in fundus images plays an important role in the
diagnosis of some diseases such as diabetes and hypertension. In this paper, we propose …

Objective: Deep learning based methods for retinal vessel segmentation are usually trained
based on pixel-wise losses, which treat all vessel pixels with equal importance in pixel-to …

Automatic retinal vessel segmentation is a fundamental step in the diagnosis of eye-related
diseases, in which both thick vessels and thin vessels are important features for symptom …

Automatic segmentation of the retinal vasculature and the optic disc is a crucial task for
accurate geometric analysis and reliable automated diagnosis. In recent years …

Retinal imaging provides a non-invasive opportunity for the diagnosis of several medical
pathologies. The automatic segmentation of the vessel tree is an important pre-processing …

This paper presents a robust and fully automatic filter-based approach for retinal vessel
segmentation. We propose new filters based on 3D rotating frames in so-called orientation …

One of the most common modalities to examine the human eye is the eye‐fundus
photograph. The evaluation of fundus photographs is carried out by medical experts during …

Automated detection of blood vessel structures is becoming of crucial interest for better
management of vascular disease. In this paper, we propose a new infinite active contour …