Personalization of cardiac fiber orientations from image data using the unscented Kalman filter

Andreas Nagler, Cristóbal Bertoglio, Michael Gee, Wolfgang Wall

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

23 Scopus citations

Abstract

In this work, we propose to estimate rule-based myocardial fiber model (RBM) parameters from measured image data, with the goal of personalizing the fiber architecture for cardiac simulations. We first describe the RBM, which is based on a space-dependent angle distribution on the heart surface and then extended to the whole domain through an harmonic lifting of the fiber vectors. We then present a static Unscented Kalman Filter which we use for estimating the degrees of freedom of the fiber model. We illustrate the methodology using noisy synthetic data on a real heart geometry, as well as real DT-MRI-derived fiber data. We also show the impact of different fiber distributions on cardiac contraction simulations.

Original languageEnglish
Title of host publicationFunctional Imaging and Modeling of the Heart - 7th International Conference, FIMH 2013, Proceedings
Pages132-140
Number of pages9
DOIs
StatePublished - 2013
Event7th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2013 - London, United Kingdom
Duration: 20 Jun 201322 Jun 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7945 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2013
Country/TerritoryUnited Kingdom
CityLondon
Period20/06/1322/06/13

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