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 …

Retinal vessel segmentation is a key step towards the accurate visualization, diagnosis,
early treatment and surgery planning of ocular diseases. For the last two decades, a …

Retinal vessel image is an important biological information that can be used for personal
identification in the social security domain, and for disease diagnosis in the medical domain …

We developed a contour detection based image processing algorithm based on Mamdani
(Type-2) fuzzy rules for detection of blood vessels in retinal fundus images. The method …

The retinal vascular condition is a reliable biomarker of several ophthalmologic and
cardiovascular diseases, so automatic vessel segmentation may be crucial to diagnose and …

Retinal blood vessels analysis is of interest for medical screening, especially in the
diagnosis of diabetic retinopathy. In this paper, we propose a new method for the …

This paper presents a supervised retinal vessel segmentation by incorporating vessel
filtering and wavelet transform features from orientation scores (OSs), and green intensity …

Early detection of vessels from fundus images can effectively prevent the permanent retinal
damages caused by retinopathies such as glaucoma, hyperextension, and diabetes …

Detection of curvilinear structures from microscopic images, which help the clinicians to
make an unambiguous diagnosis is assuming paramount importance in recent clinical …

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 …