Estimation of Cardiac Electrical Propagation from Medical Image Sequence

  • Heye Zhang
  • Chun Lok Wong
  • Pengcheng Shi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)


A novel strategy is presented to recover cardiac electrical excitation pattern from tomographic medical image sequences. The geometrical/physical representation of the heart and the dense motion field of the myocardium are first derived from imaging data through segmentation and motion recovery. The myocardial active forces are then calculated through the law of force equilibrium from the motion field, realized with a stochastic multiframe algorithm. Since tissue active forces are physiologically driven by electrical excitations, we can readily relate the pattern of active forces to the pattern of electrical propagation in myocardium, where spatial regularization is enforced. Experiments are conducted on three-dimensional synthetic data and canine magnetic resonance image sequence with favorable results.


Active Force Tikhonov Regularization Force Equilibrium Move Less Square Essential Boundary Condition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Heye Zhang
    • 1
  • Chun Lok Wong
    • 1
  • Pengcheng Shi
    • 1
    • 2
  1. 1.Medical Image Computing GroupHong Kong University of Science & TechnologyHong Kong
  2. 2.School of Biomedical EngineeringSouthern Medical UniversityGuangzhouChina

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