<title>Virtual MR tagging on three-dimensional deformable models</title>

Abstract

Magnetic Resonance (MR) tagging techniques have recently received much attention for the generation of suitable data sets for cardiac motion analysis. Several different techniques have been developed for the analysis of 3D cardiac wall motion from such data sets. Unfortunately, due to the lack of gold standard test data sets, most of the techniques are not fully evaluated. We have developed a virtual MR tagging system for evaluation of such 3D motion estimation techniques. It generates virtual tagging images, in particular SPAMM images, of the deformable model that undergoes a predetermined motion sequence in a virtual environment. The input to the system is a set of vertices that characterizes the shape of the volumetric model at each time phase. After the user interactively specifies the imaging and tagging parameters, the system automatically marks the intersections between the image and tagging planes within the model tissue to track its motion, computing the deformed tagging lines over the time sequence. The output is the set of tomographic images of the virtual object with SPAMM grid patterns reflecting the known 3D deformation field, and it can be used to evaluate an arbitrary cardiac motion estimation technique.