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Propagation of Myocardial Fibre Architecture Uncertainty on Electromechanical Model Parameter Estimation: A Case Study

  • Roch Molléro
  • Dominik Neumann
  • Marc-Michel Rohé
  • Manasi Datar
  • Hervé Lombaert
  • Nicholas Ayache
  • Dorin Comaniciu
  • Olivier Ecabert
  • Marcello Chinali
  • Gabriele Rinelli
  • Xavier Pennec
  • Maxime SermesantEmail author
  • Tommaso Mansi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9126)

Abstract

Computer models of the heart are of increasing interest for clinical applications due to their discriminative and predictive power. However the personalisation step to go from a generic model to a patient-specific one is still a scientific challenge. In particular it is still difficult to quantify the uncertainty on the estimated parameters and predicted values. In this manuscript we present a new pipeline to evaluate the impact of fibre uncertainty on the personalisation of an electromechanical model of the heart from ECG and medical images. We detail how we estimated the variability of the fibre architecture among a given population and how the uncertainty generated by this variability impacts the following personalisation. We first show the variability of the personalised simulations, with respect to the principal variations of the fibres. Then discussed how the variations in this (small) healthy population of fibres impact the parameters of the personalised simulations.

Keywords

Fibre Orientation Fibre Architecture Unscented Transform Electromechanical Model Electrical Axis 
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.

Notes

Ackowledgements

This work has been partially funded by the EU FP7-funded project MD-Paedigree (Grant Agreement 600932)

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Roch Molléro
    • 1
  • Dominik Neumann
    • 3
    • 4
  • Marc-Michel Rohé
    • 1
  • Manasi Datar
    • 3
  • Hervé Lombaert
    • 1
  • Nicholas Ayache
    • 1
  • Dorin Comaniciu
    • 2
  • Olivier Ecabert
    • 3
  • Marcello Chinali
    • 5
  • Gabriele Rinelli
    • 5
  • Xavier Pennec
    • 1
  • Maxime Sermesant
    • 1
    Email author
  • Tommaso Mansi
    • 2
  1. 1.Inria, Asclepios Research ProjectSophia AntipolisFrance
  2. 2.Siemens Corporate TechnologyImaging and Computer VisionPrincetonUS
  3. 3.Siemens Corporate TechnologyImaging and Computer VisionErlangenGermany
  4. 4.Pattern Recognition LabFriedrich-Alexander-UniversitätErlangen-nürnbergGermany
  5. 5.Ospedale Pediatrico Bambino GesùRomeItaly

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