The retinal vascular tree is an important biomarker for the diagnosis of ocular disease,
where an efficient segmentation is highly required. Recently, various standard Convolutional …

Automated retinal vessel segmentation technology has become an important tool for
disease screening and diagnosis in clinical medicine. However, most of the available …

Background and objectives: Retinal vessel segmentation (RVS) helps in diagnosing
diseases such as hypertension, cardiovascular diseases, and others. Convolutional neural …

Morphological and functional changes in retinal vessels are indicators of a variety of chronic
diseases, such as diabetes, stroke, and hypertension. However, without a large number of …

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 …

Precise segmentation of retinal vessels is crucial for a computer-aided diagnosis system of
retinal fundus images. However, this task remains challenging due to large variations in …

The segmentation results of retinal blood vessels are crucial for automatically diagnosing
ophthalmic diseases such as diabetic retinopathy, hypertension, cardiovascular and …

Retinal vessel segmentation is a critical procedure towards the accurate visualization,
diagnosis, early treatment, and surgery planning of ocular diseases. Recent deep learning …

Retinal vessel segmentation is a crucial focus within the realm of medical image analysis,
playing a pivotal role in early disease diagnosis, notably retinopathy. Deep learning has …

Feature extraction of the retinal blood vessel is one of the crucial tasks in the prediction of
ophthalmologic diseases. Important features are extracted based on image segmentation …