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Cardiac Motion Extraction from Images by Filtering Estimation Based on a Biomechanical Model

  • Philippe Moireau
  • Dominique Chapelle
  • Mariette Yvinec
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5528)

Abstract

Starting from the presentation of a unified perspective of segmentation with deformable models and data assimilation with images, we propose a data assimilation procedure designed to dynamically estimate 3D positions and velocities of the myocardium along the heart cycle, using data consisting of contours extracted from image sequences. We assess this procedure with a test problem based on a realistic computational heart model, and with synthetic data produced from reference simulations by creating binary images of the myocardium. The automatic meshing library CGAL is then employed to create contour meshes for each snapshot, and these meshes are directly used in the model-measurement comparisons. This approach gives very satisfactory qualitative and quantitative results.

Keywords

Data Assimilation Deformable Model Heart Model Reference Simulation Automatic Mesh Generation 
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 2009

Authors and Affiliations

  • Philippe Moireau
    • 1
  • Dominique Chapelle
    • 1
  • Mariette Yvinec
    • 2
  1. 1.INRIA, Macs Project-TeamLe Chesnay cedexFrance
  2. 2.INRIA, Geometrica Project-TeamSophia Antipolis cedexFrance

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