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Segmentation of brain blood vessels is essential in medical diagnostic applications. In this study, a new active contour model (ACM) implemented by the level-set framework is proposed for segmenting vessels from TOF-MRA data. The energy function of the proposed model, combining region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global...
Blood vessel segmentation is important for diagnosis of different vascular pathologies and planning of surgical treatments. In this study, we present an efficient approach for the brain vasculature extraction. The proposed method is based on multiview projection and an integrated active contour model. First, the magnetic resonance angiography (MRA) dataset is enhanced by Frangi filter and then projected...
Segmentation is one of the most challenging problems in the field of medical image analysis, and blood vessels are especially difficult to extract. In this paper, we propose a novel method for segmentation of cerebral blood vessels from magnetic resonance angiography (MRA) images based on Frangi's vesselness measure and ball B-Spline. First, we apply Frangi's vesselness measure to find putative centerlines...
Blood vessel segmentation is an essential step of the diagnoses of various brain diseases. In this paper, we propose a novel method for segmentation of cerebral blood vessels from magnetic resonance angiography (MRA) images based on Gaussian Mixture Model and the SEM algorithm. First the MIP algorithm is applied to decrease the quantity of mixing elements. Then the Gaussian Mixture Model is put forward...
Segmentation is one of the most challenging problems in the field of medical image analysis, and blood vessels are especially difficult to extract. In this paper, we propose a novel method for segmentation of cerebral blood vessels from magnetic resonance angiography (MRA) images based on Boltzmann theory. The method is composed of three major steps: first, power-law transformation is applied to enhance...
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