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Cardiac Motion Estimation Using Covariant Derivatives and Helmholtz Decomposition

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 7085)

Abstract

Quantification of cardiac function is important for the assessment of abnormalities and response to therapy. We present a method to reconstruct dense cardiac motion from sparse features in tagging MRI, decomposed into solenoidal and irrotational parts using multi-scale Helmholtz decomposition. Reconstruction is based on energy minimization using covariant derivatives exploiting prior knowledge about the motion field. The method is tested on cardiac motion images. Experiments on phantom data show that both covariant derivatives and multi-scale Helmholtz decomposition improve motion field reconstruction.

Keywords

  • Cardiac function
  • MRI tagging
  • multi-scale
  • Helmholtz decomposition
  • covariant derivatives

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Becciu, A., Duits, R., Janssen, B.J., Florack, L.M.J., van Assen, H.C. (2012). Cardiac Motion Estimation Using Covariant Derivatives and Helmholtz Decomposition. In: Camara, O., Konukoglu, E., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2011. Lecture Notes in Computer Science, vol 7085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28326-0_27

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  • DOI: https://doi.org/10.1007/978-3-642-28326-0_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28325-3

  • Online ISBN: 978-3-642-28326-0

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