Literature DB >> 16916080

Building maps of local apparent conductivity of the epicardium with a 2-D electrophysiological model of the heart.

Valérie Moreau-Villéger1, Hervé Delingette, Maxime Sermesant, Hiroshi Ashikaga, Elliot McVeigh, Nicholas Ayache.   

Abstract

In this paper, we address the problem of estimating the parameters of an electrophysiological model of the heart from a set of electrical recordings. The chosen model is the reaction-diffusion model on the transmembrane potential proposed by Aliev and Panfilov. For this model of the transmembrane, we estimate a local apparent two-dimensional conductivity from a measured depolarization time distribution. First, we perform an initial adjustment including the choice of initial conditions and of a set of global parameters. We then propose a local estimation by minimizing the quadratic error between the depolarization time computed by the model and the measures. As a first step we address the problem on the epicardial surface in the case of an isotropic version of the Aliev and Panfilov model. The minimization is performed using Brent method without computing the derivative of the error. The feasibility of the approach is demonstrated on synthetic electrophysiological measurements. A proof of concept is obtained on real electrophysiological measures of normal and infarcted canine hearts.

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Year:  2006        PMID: 16916080     DOI: 10.1109/TBME.2006.877794

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  3 in total

1.  Reconstructing parameters of the FitzHugh-Nagumo system from boundary potential measurements.

Authors:  Yuan He; David E Keyes
Journal:  J Comput Neurosci       Date:  2007-05-10       Impact factor: 1.621

2.  Quantifying the uncertainty in model parameters using Gaussian process-based Markov chain Monte Carlo in cardiac electrophysiology.

Authors:  Jwala Dhamala; Hermenegild J Arevalo; John Sapp; B Milan Horácek; Katherine C Wu; Natalia A Trayanova; Linwei Wang
Journal:  Med Image Anal       Date:  2018-05-17       Impact factor: 8.545

3.  Fundamental principles of data assimilation underlying the Verdandi library: applications to biophysical model personalization within euHeart.

Authors:  D Chapelle; M Fragu; V Mallet; P Moireau
Journal:  Med Biol Eng Comput       Date:  2012-11-07       Impact factor: 2.602

  3 in total

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