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Efficiently obtaining a reliable coronary artery centerline from computed tomography coronary angiography (CTCA) data is relevant in clinical practice. In this paper, open-snake is presented to extract the vessel centerline, which is drove by two external forces, one is Gradient Vector Flow (GVF), and the other one is an adaptive stretching force acted on the two ends of open-snake. To make the open-snake...
In the recent years, reconstructing 3D liver and its vessels from abdominal CT volume images becomes an inevitable and necessary research field. In this paper, a method of 3D reconstruction of liver with its vessels has been implemented, which involves volume preprocessing, de-noising, segmentation, contouring, and combination of different modalities. An advanced liver segmentation algorithms have...
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...
A new method of reconstructing three-dimensional (3D) tubular structures from cone-beam projections is proposed in this paper. Minimal path method is applied to detect 2D tubular structures in the cone-beam projections. The extracted 2D information are fused to design a weight function over the 3D volume so that minimal path method can be applied again to extract centerlines of 3D tubular structures...
Plaque composition analysis is a critical tool in identifying vulnerable atherosclerotic plaques. Intravascular ultrasound with spectral analysis of the backscattered radio frequency (RF) signals (IVUS-VH) is currently considered as the gold standard for the evaluation of coronary plaque composition, while CT coronary angiography (CTA) has been proposed as a potential non-invasive counterpart. In...
Time sequences of 3D images of cerebral and other vasculature blood flow during surgery and other medical procedures allow enhanced visual feedback. The visual feedback constitutes an enhancement over the existing 2D time series of X-ray projections as it facilitates the detection and observation of pathological abnormalities such as stenoses, aneurysms, and blood clots. An algorithm that outputs...
Computed Tomography Angiography (CTA) of the heart is a non-invasive procedure to rule out coronary artery disease or measure its extent and plan treatments and interventions. The need for coronary tree tracking methods that require minimum human interaction and produce accurate and robust measurements is therefore of great clinical importance. In this work we present a probabilistic coronary artery...
The current study presents an automatic algorithm for detection of myocardial infarction and ischemia using cardiac CT image data. The classification is based on probabilistic tissue modeling, where a pixel is classified according to its maximum a-posteriori probability (MAP) as belonging to a normal or abnormal tissue segment. The pixels are represented in a two-dimensional space, where the first...
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...
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,...
Graphs are useful representations of the liver vasculature. They support tree matching algorithms in landmark-based registration algorithms, they are useful to separate connected vessels from two different vessel systems and are the basis of vessel annotation tools. In this paper, we propose a hierarchical decomposition of vessel skeletons into sub-branches. This simplifies the process of creating...
Stenos is of the internal carotid artery (ICA) is implicated in approximately one quarter of stroke cases. The degree of stenos is is currently used to decide whether to undertake a surgical procedure to reduce the risk of further stroke. However it is known that the degree of stenos is is not a good predictor of stroke risk. It is hoped that prediction might be improved by incorporation of other...
The accurate segmentation of liver vessels is an important step for further computer assisted analysis in oncologic planning tools. Multiscale based vessel enhancement methods are very famous and many papers about this topic were published. Vesselness filters proposed by Sato et al., Frangi et al. and Erdt et al. are based on eigenvalue analysis of the Hessian matrix. They were developed using completely...
Different imaging modalities have been developed over the last several years in order to better characterize the atherosclerotic plaque and attempt to predict those in peril of complication. Specific information such as variations in temperature, plaque stiffness and calcification level is currently being researched as well as biological and chemical markers. Since vulnerable plaques cannot be identified...
This paper proposes a method for the semi-automatic segmentation of cerebral aneurysms from CTA datasets. The method consists of two phases: a region growing-based approach followed by a level set method, firstly to extract the cerebral artery and then to segment the aneurysm. The first phase automatically locates a seed point for initialization of the region growing in a seed slice, detection of...
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...
Computer aided diagnosis plays an important role in automatic detection of abnormal shadow area on CT images. The method of an automatic detection of lung nodules regions of interest (ROI) is presented in this paper. Firstly, the lung areas are segmented from CT images. Then, the initial ROI including nodules and blood vessels in lung areas are extracted by Top-hat filter. Thirdly, the second ROI...
A semi-automatic digital liver reconstruction method based on CT serial images for hepatobiliary is presented. Firstly, interesting regions such as liver, blood vessels and tumor are segmented by machine. Then, blood vessels are identified interactively with doctor's points. A 3D minimum distance is used to partition the sub-area of liver that blood vessel branches supply. As a result, a 3D virtual...
The purpose of this study was to describe the upslope method-derived myocardial perfusion index using the parameters based on a tracer kinetic model of iodixanol contrast agent and to validate this theoretically derived relationship using an ischemic canine model. The established modified Kety model was used to describe the extravascular diffusion of iodixanol contrast agent, which undergoes no cellular...
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