This paper presents a comprehensive review of retinal blood vessel segmentation based on
deep learning. The geometric characteristics of retinal vessels reflect the health status of …

In recent years, enormous research has been carried out on the segmentation of blood
vessels. Segmentation of blood vessels in retinal images is crucial for diagnosing, treating …

Retinal vasculature provides an opportunity for direct observation of vessel morphology,
which is linked to multiple clinical conditions. However, objective and quantitative …

Retinal vessel segmentation is an important task in medical image analysis and has a
variety of applications in the diagnosis and treatment of retinal diseases. In this paper, we …

In this paper, a novel attention augmented Wasserstein generative adversarial network (AA-
WGAN) is proposed for fundus retinal vessel segmentation, where a U-shaped network with …

The segmentation of retinal vasculature from eye fundus images is a fundamental task in
retinal image analysis. Over recent years, increasingly complex approaches based on …

Segmentation of retinal vessels on fundus images plays a critical role in the diagnosis of
micro-vascular and ophthalmological diseases. Although being extensively studied, this task …

Retinal illnesses such as diabetic retinopathy (DR) are the main causes of vision loss. In the
early recognition of eye diseases, the segmentation of blood vessels in retina images plays …

Diabetic retinopathy (DR) is the main cause of blindness in diabetic patients. Early and
accurate diagnosis can improve the analysis and prognosis of the disease. One of the …

Motivation Retinal microvasculature is a unique window for predicting and monitoring major
cardiovascular diseases, but high throughput tools based on deep learning for in-detail …