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We have recently developed an automated technique using noise-based level-set methods and non-rigid registration for endocardial and epicardial border detection as a basis for perfusion quantification from cardiac magnetic resonance (CMR) images. The goal of the present work was to validate this technique against conventional manual analysis both directly and using quantitative coronary angiography...
We developed a method for automated quantification of myocardial perfusion from cardiac magnetic resonance (CMR) images. Our approach uses region-based and edge-based level set techniques for endocardial and epicardial border detection combined with non-rigid registration achieved by a 2D multi-scale cross-correlation and contour adaptation. This method was tested on 66 short-axis image sequences...
The aim of this study was to gain a wide perspective of the arrhythmogenic right ventricular dysplasia (ARVD) by developing algorithms for Cardiac Magnetic Resonance Imaging. We developed a semi-automatic procedure to assess the Right Ventricle (RV) volumes and to quantify RV wall motion; moreover, with the increased visible details in a single MR image, a manual method to evaluate the trabeculae...
We developed a technique for automated identification of 3D myocardial ROI suitable for translation-free quantification of myocardial videointensity over time, MVI(t), from RT3DE images. Our software was tested on 12 ECG-triggered RT3DE datasets obtained in pigs during transient contrast inflow. Analysis included: (1) semi-automated detection of endo- and epicardial surfaces using level-set techniques...
Evaluation of aorta morphology and function in presence of aneurysms or dissection is crucial for a correct treatment choice between surgical resection and percutaneous stent-graft deployment. We developed and tested a new method for automated dynamic aorta segmentation from computed tomography (CT) images from which static and dynamic parameters of aortic morphology and function can be automatically...
Assessment of left ventricular (LV) size and function from cardiac magnetic resonance (CMR) images requires manual tracing of LV borders on multiple 2D slices, which is subjective, experience dependent, tedious and time-consuming. We tested a new method for automated dynamic segmentation of CMR images based on a modified region-based model, in which a level set function minimizes a functional containing...
Off-line 3D color-encoding was applied to the left ventricular (LV) endocardial surfaces obtained from real-time 3D echocardiographic images. Systolic regional wall motion abnormalities (RWMA) were automatically detected and the accuracy of this method was tested against expert visual interpretation of 2D echocardiographic (2DE) images (apical 2-, 3- and 4- chamber). 20 subjects with normal wall motion...
Quantification of left ventricular (LV) function from the analysis of real-time 3D echocardiographic (RT3DE) data does not fully exploit the dynamic volumetric information contained in these data. Accordingly, we developed a volumetric analysis technique aimed at quantification of global and regional LV function. RT3DE images were analyzed using custom software to extract global and partial volumes...
This study presents a geometric model and a computational algorithm for segmentation of ultrasound images. A partial differential equation (PDE)-based flow is designed in order to achieve a maximum likelihood segmentation of the target in the scene. The flow is derived as the steepest descent of an energy functional taking into account the density probability distribution of the gray levels of the...
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