Automatic retinal blood vessel segmentation is a key link in the diagnosis of ophthalmic
diseases. Recent deep learning methods have achieved high accuracy in vessel …

Background Retinal blood vessel segmentation has an important guiding significance for the
analysis and diagnosis of cardiovascular diseases such as hypertension and diabetes. But …

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 …

Aiming at the current problem of insufficient extraction of small retinal blood vessels, we
propose a retinal blood vessel segmentation algorithm that combines supervised learning …

Refined and automatic retinal vessel segmentation is crucial for computer-aided early
diagnosis of retinopathy. However, existing methods often suffer from mis-segmentation …

Purpose. Retinal blood vessel image segmentation is an important step in ophthalmological
analysis. However, it is difficult to segment small vessels accurately because of low contrast …

Purpose Changes in the appearance of retinal blood vessels are an important indicator for
various ophthalmologic and cardiovascular diseases, including diabetes, hypertension …

Purpose The segmentation results of retinal blood vessels have a significant impact on the
automatic diagnosis of various ophthalmic diseases. In order to further improve the …

Accurate retinal vessel segmentation plays a critical role in the diagnosis of many relevant
diseases. However, it remains a challenging task due to (1) the great scale variation of …

The pathological changes of the retina are closely related to many human diseases, such as
hypertension and diabetes. In clinical medicine, the pathological conditions of retinal blood …