Performance comparison of publicly available retinal blood vessel segmentation methods

Performance comparison of publicly available retinal blood vessel segmentation methods

Retinal blood vessel structure is an important indicator of many retinal and systemic diseases, which has motivated the development of various image segmentation methods for the blood vessels. In this study, two supervised and three unsupervised segmentation methods with a publicly available implementation are reviewed and quantitatively compared with each other on five public databases with gr...

Blood Vessel Segmentation in Retinal Images

Segmentation of blood vessels in retinal images allows early diagnosis of disease; automating this process provides several benefits including minimizing subjectivity and eliminating a painstaking, tedious task. Previous approaches, while satisfactory in some cases, still leave room for improvement, especially in abnormal retinal images. We propose to utilize a tracking based algorithm based on...

Blood Vessel Segmentation in Retinal Fundus Images

The segmentation of retinal blood vessels in the retina is a critical step in diagnosis of diabetic retinopathy. In this paper, we present a new method for automatically segmenting blood vessels in retinal images. Five basic algorithms for segmenting retinal blood vessels, based on different image processing techniques, are described and their strengths and weaknesses are compared. A hybrid alg...

Blood Vessel Segmentation from Retinal Images

Automatic Retinal Vessel Segmentation

Diabetic Retinopathy is the most common cause of blindness in the working population of the western world and is very common among people who suffer from diabetes. Fortunately, during a clinical examination an ophthalmologist is able to determine the onset of the disease by taking certain features of the retinal vessels of the fundus into account. These features include the narrowing of vessels...