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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...
Choroidal Neovascularization (CNV) is a severe retinal disease characterized by abnormal growth of blood vessels in the choroidal layer. Current diagnosis of CNV depends mainly on qualitative assessment of a temporal sequence of fundus fluorescein angiography images. Automated segmentation and identification of the CNV lesion types (either occult or classic) is required to reduce the inter-and intra-...
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...
The current 3D XCAT phantom allows users to manually define the regional myocardial perfusion defect (MPD) as a simple pie-shaped wedge region with reduced activity level in the myocardium of left ventricle. To more accurately and realistically model the MPD, we have developed a new regional MPD model for the 3D XCAT phantom for myocardial perfusion SPECT (MP-SPECT) studies based on the location and...
Conventional kinetic parameter estimation based on compartmental models requires an accurate estimation of arterial blood input function. To avoid invasive blood sampling, an image-derived input function can be obtained by manually defining a Region of Interest. Here we propose a new and simple, iterative method for automatic segmentation and input function calculation of PET cardiac studies using...
Segmented cross sectional MRI images were used to construct 3D virtual models of the carotid bifurcation in 5 healthy volunteers. Geometric features such as bifurcation angle, planarity angle, asymmetry angle tortuosity and curvature were calculated for the normal head posture and were compared to the equivalent values acquired with the head rotated clockwise by up to 80 degrees. The results obtained...
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used for the detection and assessment of coronary artery disease. While myocardial ischemia may be detected visually from the MR images by trained cardiologists or radiologists, it is likely that semi-quantitative or quantitative analysis of the dynamic images can improve the accuracy of diagnoses. Such analyses have yet to be standardized...
In this article, a system for automatic analysis of intraoperative B-Mode ultrasound images of the liver is presented. The system is part of an assistance system for open liver surgery. It supports 3D-ultrasound imaging and automatic segmentation of vessel structures in the intraoperative ultrasound images. With this segmentation results, an ultrasound based 3D-model of the vascular structure is extracted...
Unsupervised methods for automatic vessel segmentation from retinal images are attractive when only small datasets, with associated ground truth markings, are available. We present an unsupervised, curvature-based method for segmenting the complete vessel tree from colour retinal images. The vessels are modeled as trenches and the medial lines of the trenches are extracted using the curvature information...
This paper presents two methods to measure aneurysms and stenosis, and introduces a method for visualizing models of tube- and Y-stents virtually placed into preoperative CT-data. The measurement algorithms obtain characteristic dimensions of a vessel disease used to select a proper stent. A physical simulation of the forces interacting between stent and vessel walls allows the prediction of the stent...
An approach for the 3D segmentation and reconstruction of human left coronary arteries using angio-CT images is presented in This work. Each voxel in the 3D dataset is assumed to belong to one of the three homogeneous regions: blood, myocardium, and lung. A priori knowledge of the regions is introduced via Bayes' rule. Posterior probabilities obtained using Bayes' rule are anisotropically smoothed,...
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