Abstract
Tagged Magnetic Resonance Imaging (MRI) is currently the reference MR modality for myocardial motion and strain analysis. NMI-based non rigid registration has proven to be an accurate method to retrieve cardiac deformation fields. The use of αMI permits higher dimensional features to be implemented in myocardial deformation estimation through image registration. This paper demonstrates that this is feasible with a set of Haar wavelet features of high dimension. While we do not demonstrate performance improvement for this set of features, there is no significant degradation as compared to implementing the registration method with the traditional NMI metric. We use Entropic Spanning Graphs (ESGs) to estimate the αMI of the wavelet feature vectors WFVs since this is not possible with histograms. To the best of our knowledge, this is the first time that ESGs are used for non rigid registration.
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Oubel, E., Tobon-Gomez, C., Hero, A.O., Frangi, A.F. (2005). Myocardial Motion Estimation in Tagged MR Sequences by Using αMI-Based Non Rigid Registration. In: Duncan, J.S., Gerig, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005. MICCAI 2005. Lecture Notes in Computer Science, vol 3750. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11566489_34
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DOI: https://doi.org/10.1007/11566489_34
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