Retinal fundus imaging is widely used for eye examinations. The acquired images provide a unique view on the eye vasculature. The analysis of the vasculature has a high importance especially for detecting cardiovascular diseases. We present a multiscale algorithm for automatic retinal blood vessel segmentation, which is considered as a requirement for the diagnosis of vascular diseases. The alg...

Blood vessel extraction is an important step for abnormality detection and for obtaining good retinopathy diabetic diagnosis in digital retinal images. The use of filter bank has shown to be a powerful technique for detecting blood vessels. In particular, the Matched Filter is appropriate and efficient for this task and in combination with other methods the blood vessel detection can be improve...

Automated image processing techniques have the ability to assist in the early detection of diabetic retinopathy disease which can be regarded as a manifestation of diabetes on the retina. Blood vessel segmentation is the basic foundation while developing retinal screening systems, since vessels serve as one of the main retinal landmark features. This paper proposes an automated method for ident...

Two moving-window methods, using either flat or Gaussian weighted windows, for local thresholding with Robust Automatic Threshold Selection are developed. The results show that fast segmentation of blood vessels against a varying background and noise is possible at modest computational cost. Volumes of 128 × 256 and 256 can be segmented in 3.1 s and 6.6 s, for flat, and 12.6 s and 30.8 s for Ga...

Vascular diseases are nowadays one of the serious issues which have a huge impact on someone's life. Number of researchers at different universities as well as medical device manufacturers are working in this field for better understanding of the vascular characteristics. It is expected that three dimensional structure of blood vessels can provide comprehensive visualization of vessel geometry....

The segmentation of blood vessels is a common problem in medical imaging and various applications are found in diagnostics, surgical planning, training and more. Among many different techniques, the use of multiple scales and line detectors is a popular approach. However, the typical line filters used are sensitive to intensity variations and do not target the detection of vessel walls explicit...

The change in morphology, diameter, branching pattern and/or tortuosity of retinal blood vessels is an important indicator of various clinical disorders of the eye and the body. This paper reports an automated method for segmentation of blood vessels in retinal images by means of a unique combination of differential filtering and morphological processing. The centerlines are extracted by the ap...

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...

The morphological changes of retinal blood vessels are important indicators used to diagnose and monitor the progression of various diseases. A number of retinal blood vessel segmentation methods have been introduced, including the line operator based methods, which have shown satisfactory results. However, the basic line operator method cannot discriminate the pixels around the retinal optic d...

Computed tomography angiography (CTA) data sets without hardware based bone subtraction have the disadvantage of containing the bone structures which particularly overlap with vessel intensities; therefore vessel segmentation is hampered. Segmentation methods developed for CTA without bones can not handle these data sets and manual cerebral vessel segmentation is not realizable in clinical rout...