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In the context of vessel tree structures segmentation with implicit deformable models, we propose to exploit convolution surfaces to introduce a novel variational formulation, robust to bifurcations, tangential vessels and aneurysms. Vessels are represented by an implicit function resulting from the convolution of the centerlines of the vessels, modeled as a second implicit function, with localized...
Micro-tomography produces high resolution images of biological structures such as vascular networks. In this paper, we present a new approach for segmenting vascular network into pathological and normal regions from considering their micro-vessel 3D structure only. We define and use a conditional random field for segmenting the output of a watershed algorithm. The tumoral and normal classes are thus...
Segmentation of 3D cerebral vasculature is important for clinical diagnosis. However, many relevant thin vessels are not visible in 1.5T and 3T MRA. With the recent introduction of 7T MRA, images of higher resolution can be acquired, which contain much more thin vessels. We propose a fully automatic hybrid approach for segmenting vessels from 7T MRA images of the human cerebrovascular system. First,...
Segmentation of cerebral vascular networks from 3D angiographic data remains a challenge. Automation generally induces a high computational cost and possible errors, while interactive methods are hard to use due to the dimension and complexity of images. This article presents a compromise between both approaches, by using the concept of example-based segmentation. Segmentation examples of vascular...
The segmentation and classification of the major intra-hepatic blood vessels are critical for the robust identification of the segmental anatomy of the liver. We propose a novel 4D graph-based method to segment and label the hepatic and portal veins. The algorithm uses multi-phase CT images to model the differential enhancement of the liver structures and Hessian-based vesselness likelihood to avoid...
This paper presents a geodesic voting method to segment tree structures, such as cardiac or cerebral blood vessels. Many authors have used minimal cost paths, or similarly geodesics relative to a weight potential P, to find a vessel between two end points. Our goal focuses on the use of a set of such geodesic paths for finding a tubular tree structure, using minimal interaction. This work adapts the...
Blood vessel segmentation, that is, extraction of the center lines and corresponding local cylinder radii are important for the study of vascular diseases, and in the brain also important for the modeling and understanding of relationships between hemodynamics and electrical neural activity. Several image processing methods have been proposed for vessel extraction in many domains including those that...
In this work, we present a novel content-based 3D shape retrieval system for Abdominal Aortic Aneurysm (AAA) rupture risk prediction. The algorithms incorporate shape context, RANdom SAmple Consensus (RANSAC) and thin plate spline (TPS) to achieve a reliable AAA rupture risk assessment system. Pre-labeled unruptured and ruptured cases (`-1' for unruptured and `1' for ruptured cases) are built and...
In this paper, we present a novel vasculature segmentation algorithm that incorporates the knowledge of both vascular anatomy and imaging modality. In particular, emphasis is put on the segmentation of main cerebral vessels such as the Circle of Wills. The algorithm segments cerebral vasculature in two major steps. One is vasculature candidate calculation using local intensity distribution, where...
Segmentation of vessel structures in 3D volume data is of great interest for diagnosis and surgical planning. There are a number of methods that employ various intensity-based, textural, or geometric features for vessel extraction from 3D volume data. However, these methods are not successful in the low-contrast and inhomogeneous environments, especially in case of thinner blood vessels. In this study,...
This paper presents an efficient algorithm for segmenting pulmonary artery tree in 3D images from Computed Tomography Angiography (CTA) scans. A new algorithm based on region growing and slice marching (RGSM) is proposed to segment pulmonary artery and track the artery tree section. To avoid the leakage and other false positive such as pulmonary vein, thresholds are automatically determined based...
Enhancement of vessels in medical images is still an unsolved problem. Multiscale approaches were proposed to improve the vessel enhancement effect based on the structure size and image resolution. Vessel enhancing diffusion (VED) filter is one of the multiscale approaches, which was based on the scale space theory. VED performs well on enhancing vessel structures but cannot preserve complex structures...
A new level-set based active contour method for the segmentation of small blood vessels and other elongated structures is presented. Its main particularity is the presence of a length increasing force in the contour driving equation. The effect of this force is to push the active contour in the direction of thin elongated shapes. Although the proposed force is not stable in general, our experiments...
During an Intravascular Ultrasound (IVUS) examination, a catheter with an ultrasound transducer is introduced in the body through a blood vessel and then pulled back to image a sequence of vessel cross-sections. An IVUS exam results in several hundred noisy images often hard to analyze. Hence, developing powerful automatic analysis tool would facilitate the interpretation of structures in IVUS images...
Efficient visualization of vascular structures is essential for diagnosis, therapy planning and medical education. In this paper, we present an approach which is based on a prior binary segmentation result, point extraction and Poisson surface reconstruction. The proposed method has been applied to liver vessel trees and aortic vessel trees. The experimental results show that it can effectively achieve...
CTA technology is characterized by the higher clinically practical value in the inspection of the vascular diseases compared with other similar technologies. The bone-subtraction is the key method to improve the quality of CTA subtraction image and promotion of CTA technology. In this paper, a bone-subtraction method of the 3D CTA was proposed. The method includes a bone segmentation algorithm with...
The segmentation of vascular structures in 3D medical images is of great importance for many clinical applications, ranging from the detection and measurement of vascular disease to providing information for surgical intervention. Accurate and robust vascular segmentation is made difficult by variations in the vessel's contrast enhancement and its surrounding background, both within the same patient...
The proposed model is devoted to the segmentation and reconstruction of 3D vascular trees. We rely on an explicit representation of a deformable tree, where topological relationships between segments are modeled. This allows easy posterior interactions and quantitative analysis, such as measuring diameters or lengths of vessels. Starting from a unique user-provided root point, an initial tree is built...
In this paper we present a method for coronary artery motion tracking in 4D cardiac CT data sets. The algorithm allows the automatic construction of a 4D coronary motion model from pre-operative CT which can be used for guiding totally-endoscopic coronary artery bypass surgery (TECAB). The proposed approach is based on two steps: In the first step, the coronary arteries are extracted in the end-diastolic...
We present an approach for accurate localization of the neck of intracranial aneurysms and quantification of their geometry that is useful for their treatment through endovascular embolization. In particular, we first obtain a vessel segmentation using a topology-preserving level set method and extract the surface of the segmented vessel. We then separate the aneurysm from the parent vessels and localize...
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