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

  • Authors:
  • Alessandro Becciu;Hans Assen;Luc Florack;Sebastian Kozerke;Vivian Roode;Bart M. Haar Romeny

  • Affiliations:
  • Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands 5600 MB;Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands 5600 MB;Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands 5600 MB and Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands ...;Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology, Zurich, Switzerland;Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands 5600 MB;Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands 5600 MB

  • Venue:
  • SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
  • Year:
  • 2009

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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.