coronary heart disease has been one of the main threats of human health. coronary angiography is taken as the “gold standard” for the assessment of coronary artery disease. but sometimes, the images are difficult to interpret visually because of the crossing and overlapping of the vessels in the angiograms. vessel extraction from x-ray angiograms has been a challenging problem for several years...

detecting blood vessels is an important task in retinal image analysis.  the task is more challenging with the presence of bright and dark lesions in retinal images. here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. first, the negative impact of bright lesions is reduced by using k-means segmentation in a perceptive sp...

Background and Objective: Cerebral Arteriovenous Malformation (CAVM) hemodynamic is disease condition, results changes in the flow and pressure level in cerebral blood vessels. Measuring flow and pressure without catheter intervention along the vessel is big challenge due to vessel bifurcations/complex bifurcations in Arteriovenous Malformation patients. The vessel geometry in CAVM patients are...

background and objective: cerebral arteriovenous malformation (cavm) hemodynamic is disease condition, results changes in the flow and pressure level in cerebral blood vessels. measuring flow and pressure without catheter intervention along the vessel is big challenge due to vessel bifurcations/complex bifurcations in arteriovenous malformation patients. the vessel geometry in cavm patients are...

to investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal imagequality, a comparative study was carried out. we studied and implemented a few illumination correction and contrast enhancementtechniques on color retinal images to find out the best technique for optimum image enhancement. to compare and choose thebest illumination c...

In this paper we consider the problem of blood vessel segmentation in retinal images. After enhancing the retinal image we use green channel of images for segmentation as it provides better discrimination between vessels and background. We consider the negative of retinal green channel image as a topographical surface and extract ridge points on this surface. The points with this property are l...

this paper presents a new procedure for automatic extraction of the blood vessels and optic disk (od) in fundus fluorescein angiogram (ffa). in order to extract blood vessel centerlines, the algorithm of vessel extraction starts with the analysis of directional images resulting from sub‑bands of fast discrete curvelet transform (fdct) in the similar directions and different scales. for this pur...

Retinal image processing is a standard medical repetition and offers number of profitable products for physicians. In the field of retinal image processing retinal vessel segmentation is the crucial task for detection of cardiovascular diseases in advance. The recognition of erroneous blood vessel may cause in incorrect clinical diagnosis. Various processing steps are required for the extractio...

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...