Cardiac Motion and Deformation Estimation from Tagged MRI Sequences Using a Temporal Coherent Image Registration Framework
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Non-rigid image registration has been proposed to extract myocardial motion and deformation from tagged Magnetic Resonance Imaging (t-MRI). Initial efforts focused on finding a set of pairwise registrations, while more recent methods proposed to perform a joint image alignment to exploit temporal information. However, the latter methods usually measure image similarity with respect to the first phase, which may not be optimal due to tag fading. In the present study, we therefore propose a sequential 2D+t registration method exploiting temporal information based on a frame-by-frame image similarity. The method was first tested on synthetic data to fine-tune its parameters, and its applicability was illustrated in human patient data. Furthermore, the sequential 2D+t method was able to detect dysfunctional regions corresponding to delayed-enhanced MRI areas in a database consisting of 8 pig datasets. While differences with respect to traditional 2D methods are limited in terms of end-systolic strain accuracy, including temporal information lead to both smoother trajectories and smoother strain curves.
KeywordsNon-rigid registration motion deformation tagged MRI
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- 2.Smal, I., Carranza-Herrezuelo, N., Klein, S., Niessen, W., Meijering, E.: Quantitative comparison of tracking methods for motion analysis in tagged MRI. In: IEEE Int. Symposium on Biomedical Imaging (2011)Google Scholar
- 6.Chandrashekara, R., Mohiaddin, R., Rueckert, D.: Cardiac motion tracking in tagged MR images using a 4D B-spline motion model and nonrigid image registration. In: IEEE Int. Symposium on Biomedical Imaging, pp. 468–471 (2004)Google Scholar
- 9.Tobon-Gomez, C., De Craene, M., Dahl, A., Kapetanakis, S., Carr-White, G., Lutz, A., Rasche, V., Etyngier, P., Kozerke, S., Schaeffter, T., et al.: A multimodal database for the 1st cardiac motion analysis challenge. Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges, 33–44 (2012)Google Scholar