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

Various structures in human physiology follow a treelike morphology, which often expresses
complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal …

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 …

Goal: In this work, we present an extensive description and evaluation of our method for
blood vessel segmentation in fundus images based on a discriminatively trained fully …

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 …

In this research, we propose two variants of the Firefly Algorithm (FA), namely inward
intensified exploration FA (IIEFA) and compound intensified exploration FA (CIEFA), for …

Fundus images have been established as an important factor in analyzing and recognizing
many cardiovascular and ophthalmological diseases. Consequently, precise segmentation …

Background and objective Deep learning techniques are instrumental in developing network
models that aid in the early diagnosis of life-threatening diseases. To screen and diagnose …

The change in morphology, diameter, branching pattern or tortuosity of retinal blood vessels
is an important indicator of various clinical disorders of the eye and the body. This paper …