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

Retinal fundus images play a crucial role in the early detection of eye problems, aiding in
timely diagnosis and treatment to prevent vision loss or blindness. With advancements in …

Retinal blood vessel segmentation in fundus images plays an important role in the early
diagnosis and treatment of retinal diseases. In recent years, the segmentation methods …

Since the retinal blood vessel has been acknowledged as an indispensable element in both
ophthalmological and cardiovascular disease diagnosis, the accurate segmentation of the …

This paper presents a comprehensive review of the principle and application of deep
learning in retinal image analysis. Many eye diseases often lead to blindness in the absence …

There has been steady progress in the field of deep learning-based blood vessel
segmentation. However, several challenging issues still continue to limit its progress …

Diabetic retinopathy (DR) is a primary cause of blindness in which damage occurs to the
retina due to an accretion of sugar levels in the blood. Therefore, prior detection …

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 …

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 …