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Joint Myocardial Motion and Contraction Phase Estimation from Cine MRI Using Variational Data Assimilation

  • Viateur Tuyisenge
  • Laurent Sarry
  • Thomas Corpetti
  • Elisabeth Innorta-Coupez
  • Lemlih Ouchchane
  • Lucie Cassagnes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8896)

Abstract

We present a cardiac motion estimation method with variational data assimilation that combines image observations and a dynamic evolution model. The novelty of the model is that it embeds new parameters modeling heart contraction and relaxation. It was applied to a synthetic dataset with known ground truth motion and to 10 cine-MRI sequences of patients with normal or dyskinetic myocardial zones. It was compared to the inTag tagging tracking software for computing the radial motion component, and to the diagnosis for dyskinesia. We found that the new dynamic model performed better than the standard transport model, and the contraction parameters are promising features for diagnosing dyskinesia.

Keywords

Data Assimilation Synthetic Dataset Cardiac Motion Variational Data Assimilation Myocardial Motion 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Viateur Tuyisenge
    • 1
  • Laurent Sarry
    • 1
  • Thomas Corpetti
    • 3
  • Elisabeth Innorta-Coupez
    • 2
  • Lemlih Ouchchane
    • 1
  • Lucie Cassagnes
    • 1
    • 2
  1. 1.Clermont Université, Université d’ Auvergne, ISIT UMR 6284 UdA-CNRSClermont-ferrandFrance
  2. 2.Pôle de Radiologie et d’ Imagerie Médicale, CHU Gabriel MontpiedClermont-ferrandFrance
  3. 3.COSTEL-LETG UMR 6554 CNRS-Université de Rennes 2RennesFrance

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