Automatic segmentation of retinal images is an important task in computer-assisted medical
image analysis for the diagnosis of diseases such as hypertension, diabetic and …

Diabetic retinopathy is characteristic of a local distribution that involves early‐stage risk
factors and can forecast the evolution of the illness or morphological lesions related to the …

Retinal blood vessels possess a complex structure in the retina and are considered an
important biomarker for several retinal diseases. Ophthalmic diseases result in specific …

Artificial Intelligence (AI) stands at the forefront of innovation in ophthalmology, harnessing
vast datasets to redefine diagnostics and treatment strategies. This Research Topic collates …

In this paper, a new mean matting method based on mean correlation is proposed to extract
thin blood vessels precisely. The proposed algorithm is the combination of both supervised …

Retinal vascular patterns are unique and individual. They provide highly secure and correct
identity authentication. In this study, we exploit an image alignment approach based on a …

At present, many of visual disease happened from the abnormality of retinal vessels. The
automatic vascular extraction from fundus images is essential for the diagnosis to reduce …

Retinal imaging is a powerful tool for detecting and diagnosing various health conditions.
Locating retinal vessels is important because it allows for the specification of different tissues …

Introduction Ophthalmic diseases are approaching an alarming count across the globe.
Typically, ophthalmologists depend on manual methods for the analysis of different …

Diabetic retinopathy is characteristic of a local distribution that involves early-stage risk
factors and can forecast the evolution of the illness or morphological lesions related to the …