This paper studies the retinal vessel radius estimation and proposes a segmentation method for vessel center lines based on ridge descriptors. The study on radius estimation reveals that the radius estimation by the matched filters based on the second order derivatives of Gaussian kernels is only correct at the vessel center. The relation between the vessel radius and the scale of the Gaussian ...

OBJECTIVES Exact cerebrovascular segmentations are required for several applications in today's clinical routine. A major drawback of typical automatic segmentation methods is the occurrence of gaps within the segmentation. These gaps are typically located at small vessel structures exhibiting low intensities. Manual correction is very time-consuming and not suitable in clinical practice. This ...

PURPOSE The main purpose of the paper is to evaluate an automated method for blood vessels segmentation in color fundus images, due to its important role in the diagnosis of several pathologies such as diabetes. The final objective is to introduce the algorithm into a Computer Aided Diagnosis (CAD) tool that would be available in those local medical centers without specialists. METHOD An auto...

In this paper, we extend our published work [Cao et al., 2011] on methods to support the analysis of both vessel bed segmentation and microvascular centreline extraction in co-registered retinal angiogram sequences. These tools should allow researchers and clinicians to estimate and assess the (micro-)vessel diameter, capillary blood volume and microvascular topology for early stage disease det...

We propose an algorithm of blood vessel segmentation for MRA data in this paper. The generic region growing, as well as thresholding, is not appropriate to extract the whole part of the vessels on MRA data. This is because of the image property of the MRA, where the intensity of each pixel on the blood area depends on the amount of blood flow. Moreover, thin vessels are affected by the partial ...