Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …

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 …

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 …

The blood vessels are the primary anatomical structure that can be visible in retinal images.
The segmentation of retinal blood vessels has been accepted worldwide for the diagnosis of …

Recent advancements in deep learning architectures have extended their application to
computer vision tasks, one of which is the segmentation of retinal blood vessels from retinal …

In this paper, a deep convolutional neural network (CNN) is proposed for accurate
segmentation of retinal blood vessels. This method plays a significant role in observing …

In recent years, the influence of deep learning on retinal vessel segmentation has grown
rapidly. Most of the available deep learning based methods use relatively shallow structures …

Background and objectives Retinal vessels are a major feature used for the physician to
diagnose many retinal diseases, such as cardiovascular disease and Glaucoma. Therefore …

To further improve retinal vessel segmentation accuracy, we propose a deformable
convolutional neural network based on cascade U-Net for retinal vessel segmentation: DCU …

In this paper, we have developed a new method of accurate detection of retinal blood
vessels based on a deep convolutional neural network (CNN) model. This method plays an …