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We developed an automated technique for non-rigid image registration as a basis for tracking the heart in contrast-enhanced cardiac magnetic resonance (CMR) image sequences. The goal of the present work was to validate this technique against conventional manual analysis. Our approach is based on a multi-scale extension of the normalized 2D cross-correlation algorithm in combination with level-set...
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...
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...
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