The eye affords a unique opportunity to inspect a rich part of the human microvasculature
non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are …

The visual exploration of retinal blood vessels assists ophthalmologists in the diagnoses of
different abnormalities of the eyes such as diabetic retinopathy, glaucoma, cardiovascular …

Deep learning (DL) based semantic segmentation methods have been providing state-of-the-
art performance in the last few years. More specifically, these techniques have been …

Deep learning (DL)-based semantic segmentation methods have been providing state-of-
the-art performance in the past few years. More specifically, these techniques have been …

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 …

This paper presents a new supervised method for vessel segmentation in retinal images.
This method remolds the task of segmentation as a problem of cross-modality data …

A number of imaging techniques are being used for diagnosis and treatment of vascular
pathologies like stenoses, aneurysms, embolisms, malformations and remodelings, which …

Timely and affordable computer-aided diagnosis of retinal diseases is pivotal in precluding
blindness. Accurate retinal vessel segmentation plays an important role in disease …

In recent years, semantic segmentation method based on deep learning provides advanced
performance in medical image segmentation. As one of the typical segmentation networks …

The morphology of retinal vessels is closely associated with many kinds of ophthalmic
diseases. Although huge progress in retinal vessel segmentation has been achieved with …