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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...
Extensive research in the field of magnetic resonance imaging has been done to improve diagnosis of cardiovascular diseases. Using a dynamic heart phantom (DHP) is vital to improve and validate MR imaging techniques and protocols. We have developed an innovative DHP design using a motor driven hydraulic system that delivers XYZ translational motion, rotation of the gel and internal pressure generation...
In conventional Doppler ultrasound (US) the blood velocity is only estimated along the US beam direction. The estimate is angle corrected assuming laminar flow parallel to the vessel boundaries. As the flow in the vascular system never is purely laminar, the velocities estimated with conventional Doppler US are always incorrect. Three angle independent vector velocity methods are evaluated in this...
Competing technologies have recently emerged across the spectrum of cardiovascular imaging modalities that study intra-myocardial function, probing promising new parameters such as cardiac strain, twist, and torsion. Displacement encoding with stimulated echoes (DENSE) in cardiac magnetic resonance (cMR) imaging achieves accurate spatiotemporal measurements of tissue motion, but remains expensive...
Magnetic resonance imaging (MRI) offers the potential to estimate blood pressure gradients, by solving the Navier-Stokes model relating the haemodynamic pressure to the acceleration and velocity. Here we compared results directly obtained using acceleration encoded MR sequences with those calculated from MR velocity acquisitions available on clinical systems. We found that using velocity encoded data...
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