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Predictive Modeling of Cardiac Fiber Orientation Using the Knutsson Mapping

  • Karim Lekadir
  • Babak Ghafaryasl
  • Emma Muñoz-Moreno
  • Constantine Butakoff
  • Corné Hoogendoorn
  • Alejandro F. Frangi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6892)

Abstract

The construction of realistic subject-specific models of the myocardial fiber architecture is relevant to the understanding and simulation of the electro-mechanical behavior of the heart. This paper presents a statistical approach for the prediction of fiber orientation from myocardial morphology based on the Knutsson mapping. In this space, the orientation of each fiber is represented in a continuous and distance preserving manner, thus allowing for consistent statistical analysis of the data. Furthermore, the directions in the shape space which correlate most with the myocardial fiber orientations are extracted and used for subsequent prediction. With this approach and unlike existing models, all shape information is taken into account in the analysis and the obtained latent variables are statistically optimal to predict fiber orientation in new datasets. The proposed technique is validated based on a sample of canine Diffusion Tensor Imaging (DTI) datasets and the results demonstrate marked improvement in cardiac fiber orientation modeling and prediction.

Keywords

Partial Little Square Diffusion Tensor Image Fiber Orientation Shape Information Shape Space 
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 2011

Authors and Affiliations

  • Karim Lekadir
    • 1
  • Babak Ghafaryasl
    • 1
  • Emma Muñoz-Moreno
    • 1
  • Constantine Butakoff
    • 1
  • Corné Hoogendoorn
    • 1
  • Alejandro F. Frangi
    • 1
  1. 1.Center for Computational Imaging & Simulation Technologies in BiomedicineUniversitat Pompeu Fabra and CIBER-BBNBarcelonaSpain

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