Sequential state estimation for electrophysiology models with front level-set data using topological gradient derivations

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

Abstract

We propose a new sequential estimation method for making an electrophysiology model patient-specific, with data in the form of level sets of the electrical potential. Our method incorporates a novel correction term based on topological gradients, in order to track solutions of complex patterns. Our assessments demonstrate the effectiveness of this approach, including in a realistic case of atrial fibrillation.

Original languageEnglish
Title of host publicationFunctional Imaging and Modeling of the Heart - 8th International Conference, FIMH 2015, Proceedings
EditorsHans van Assen, Peter Bovendeerd, Hans van Assen, Peter Bovendeerd, Tammo Delhaas, Tammo Delhaas
PublisherSpringer Verlag
Pages402-411
Number of pages10
ISBN (Print)9783319203089, 9783319203089
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015 - Maastricht, Netherlands
Duration: 25 Jun 201527 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9126
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015
Country/TerritoryNetherlands
CityMaastricht
Period25/06/1527/06/15

Keywords

  • Bidomain equations
  • Data assimilation
  • Electrophysiology modeling
  • Estimation
  • Observer
  • Shape derivative
  • Topological gradient

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