Magnetic resonance tagging technique measures the deformation of the heart wall by overlying darker tag lines onto the brighter myocardium and tracking their motion during the heart cycle. In this paper, we propose a new spline-based methodology for constructing a dense cardiac displacement map based on the tag tracking result. In this new approach, the deformed tags are tracked using a Gabor filter-based technique and smoothed using implicit splines. Then we measure the displacement in the myocardium of both ventricles using a new spline interpolation model. This model uses rough segmentation results to set up break points along tag tracking spline so that the local myocardium deformation will not be influenced by the tag information in the blood or the deformation in other parts of the myocardium. The displacements in x- and y- directions are calculated separately and are combined later to form the final displacement map. This method accepts either a tag grid or separate horizontal and vertical tag lines as its input by adjusting the offsets of images taken at different breath hold. The method can compute dense displacement maps of the myocardium for time phases during systole and diastole. The approach has been quantatively validated on phantom images and been tested on more than 20 sets of in-vivo heart data. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Axel, L., Chen, T., & Manglik, T. (2005). Dense myocardium deformation estimation for 2D tagged MRI. In Lecture Notes in Computer Science (Vol. 3504, pp. 446–456). Springer Verlag. https://doi.org/10.1007/11494621_44
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