Myocardial motion estimation in tagged MR sequences by using αMI-based non rigid registration

Authors:
E. Oubel;C. Tobon-Gomez;A. O. Hero;A. F. Frangi
Affiliations:
Computational Imaging Laboratory, Pompeu Fabra University, Barcelona, Spain;Computational Imaging Laboratory, Pompeu Fabra University, Barcelona, Spain;Dept. of EECS, The University of Michigan, Ann Arbor, MI;Computational Imaging Laboratory, Pompeu Fabra University, Barcelona, Spain
Venue:
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Year:
2005

Citing 2
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A Generic Framework for Non-rigid Registration Based on Non-uniform Multi-level Free-Form Deformations

MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Measuring myocardial deformations in tagged MR image sequences using informational non-rigid registration

FIMH'03 Proceedings of the 2nd international conference on Functional imaging and modeling of the heart

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Abstract

Tagged Magnetic Resonance Imaging (MRI) is currently the reference MR modality for myocardial motion and strain analysis. NMIbased non rigid registration has proven to be an accurate method to retrieve cardiac deformation fields. The use of aMI 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 aMI 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.