BACKGROUND Fuzzy connectedness method has shown its effectiveness for fuzzy object extraction in recent years. However, two problems may occur when applying it to hepatic vessel segmentation task. One is the excessive computational cost, and the other is the difficulty of choosing a proper threshold value for final segmentation. METHODS In this paper, an accelerated strategy based on a lookup...

Information about the retinal blood vessel network is important for diagnosis, treatment, screening, evaluation and the clinical study of many diseases such as diabetes, hypertension and arteriosclerosis. Automated segmentation and identification of retinal image structures had become one of the major research subjects in the fundus imaging and diagnostic ophthalmology. Automatic segmentation o...

A multiple hypothesis tracking approach to the segmentation of small 3D vessel structures is presented. By simultaneously tracking multiple hypothetical vessel trajectories, low contrast passages can be traversed, leading to an improved tracking performance in areas of low contrast. This work also contributes a novel mathematical vessel template model, with which an accurate vessel centerline e...

Image segmentation can be seen as a pattern classification problem, where each pixel is assigned, on the basis of, e.g., its gray level, either to the object or to the background class. In this setup, vessel segmentation is characterized by large class skew, as there are usually far more background pixels than vessel pixels and by weak separability, as there is a strong overlap between the two ...

Vessel segmentation in photographies of the retina is needed in a set of computer-supported medical applications related to diagnosis and surgery planning. Considering each pixel in an image as a point in a feature space, segmentation is a binary classification problem where pixels need to be assigned to one of two classes: object and background. We describe a paradigm of hysteresis-classifier ...

Angiography is a widely used method of vessel imaging for the diagnosis and treatment of pathological manifestations as well as for medical research. Vessel segmentation in angiograms is useful for analysis but also as a means to enhance the vessels. Often the vessel surface has to be quantified to evaluate the success of certain drugs treatment (e.g. aimed at angiogenesis in the case of transp...

The correct segmentation of blood vessels in optical coherence tomography (OCT) images may be an important requirement for the analysis of intra-retinal layer thickness in human retinal diseases. We developed a shape model based procedure for the automatic segmentation of retinal blood vessels in spectral domain (SD)-OCT scans acquired with the Spectralis OCT system. The segmentation procedure ...

The structure and appearance of the blood vessel network in retinal fundus images is an essential part of diagnosing various problems associated with the eyes, such as diabetes and hypertension. In this paper, an automatic retinal vessel segmentation method utilizing matched filter techniques coupled with an AdaBoost classifier is proposed. The fundus image is enhanced using morphological opera...

The automatic analysis of retinal blood vessels plays an important role in the computer-aided diagnosis. In this paper, we introduce a probabilistic tracking-based method for automatic vessel segmentation in retinal images. We take into account vessel edge detection on the whole retinal image and handle different vessel structures. During the tracking process, a Bayesian method with maximum a p...

The most important disease that cause vessels structure to change is diabetic retinopathy. When the pancreas does not secrete enough amount of insulin diabetic retinopathy occurs. The symptoms of diabetic retinopathy include cotton wool spots, hemorrhages, hard exudates and dilated retinal veins. There are advance care of diabetic is present but still vision loss is also present. The risk of vi...