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A Multi-scale Feature Based Optic Flow Method for 3D Cardiac Motion Estimation

  • Conference paper
Scale Space and Variational Methods in Computer Vision (SSVM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5567))

Abstract

The dynamic behavior of the cardiac muscle is strongly dependent on heart diseases. Optic flow techniques are essential tools to assess and quantify the contraction of the cardiac walls. Most of the current methods however are restricted to the analysis of 2D MR-tagging image sequences: due to the complex twisting motion combined with longitudinal shortening, a 2D approach will always suffer from through-plane motion. In this paper we investigate a new 3D aperture-problem free optic flow method to study the cardiac motion by tracking stable multi-scale features such as maxima and minima on 3D tagged MR and sine-phase image volumes. We applied harmonic filtering in the Fourier domain to measure the phase. This removes the dependency of intensity changes of the tagging pattern over time due to T1 relaxation. The regular geometry, the size-changing patterns of the MR-tags stretching and compressing along with the tissue, and the phase- and sine-phase plots represent a suitable framework to extract robustly multi-scale landmark features. Experiments were performed on real and phantom data and the results revealed the reliability of the extracted vector field. Our new 3D multi-scale optic flow method is a promising technique for analyzing true 3D cardiac motion at voxel precision, and free of through-plane artifacts present in multiple-2D data sets.

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Author information

Authors and Affiliations

  1. Biomedical Engineering, Eindhoven University of Technology, Eindhoven, 5600 MB, The Netherlands

    Alessandro Becciu, Hans van Assen, Luc Florack, Vivian Roode & Bart M. ter Haar Romeny

  2. Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, 5600 MB, The Netherlands

    Luc Florack

  3. Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology, Zurich, Switzerland

    Sebastian Kozerke

Authors
  1. Alessandro Becciu
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  2. Hans van Assen
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  3. Luc Florack
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  4. Sebastian Kozerke
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  5. Vivian Roode
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  6. Bart M. ter Haar Romeny
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Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Bergen, Johannes Brunsgate 12, 5008, Bergen, Norway

    Xue-Cheng Tai

  2. Department of Informatics and Centre of Mathematics for Applications, University of Oslo, Oslo, Norway

    Knut Mørken

  3. Simula Research Laboratory, M. Linges v 17, Fornebu, P.O.Box 134, N-1325, Lysaker, Norway

    Marius Lysaker

  4. SINTEF ICT, Oslo, Norway

    Knut-Andreas Lie

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© 2009 Springer-Verlag Berlin Heidelberg

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Becciu, A., van Assen, H., Florack, L., Kozerke, S., Roode, V., ter Haar Romeny, B.M. (2009). A Multi-scale Feature Based Optic Flow Method for 3D Cardiac Motion Estimation. In: Tai, XC., Mørken, K., Lysaker, M., Lie, KA. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2009. Lecture Notes in Computer Science, vol 5567. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02256-2_49

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  • DOI: https://doi.org/10.1007/978-3-642-02256-2_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02255-5

  • Online ISBN: 978-3-642-02256-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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