Document Detail


Finite-element-based discretization and regularization strategies for 3-D inverse electrocardiography.
MedLine Citation:
PMID:  21382763     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We consider the inverse electrocardiographic problem of computing epicardial potentials from a body-surface potential map. We study how to improve numerical approximation of the inverse problem when the finite-element method is used. Being ill-posed, the inverse problem requires different discretization strategies from its corresponding forward problem. We propose refinement guidelines that specifically address the ill-posedness of the problem. The resulting guidelines necessitate the use of hybrid finite elements composed of tetrahedra and prism elements. Also, in order to maintain consistent numerical quality when the inverse problem is discretized into different scales, we propose a new family of regularizers using the variational principle underlying finite-element methods. These variational-formed regularizers serve as an alternative to the traditional Tikhonov regularizers, but preserves the L(2) norm and thereby achieves consistent regularization in multiscale simulations. The variational formulation also enables a simple construction of the discrete gradient operator over irregular meshes, which is difficult to define in traditional discretization schemes. We validated our hybrid element technique and the variational regularizers by simulations on a realistic 3-D torso/heart model with empirical heart data. Results show that discretization based on our proposed strategies mitigates the ill-conditioning and improves the inverse solution, and that the variational formulation may benefit a broader range of potential-based bioelectric problems.
Authors:
Dafang Wang; Robert M Kirby; Chris R Johnson
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2011-03-03
Journal Detail:
Title:  IEEE transactions on bio-medical engineering     Volume:  58     ISSN:  1558-2531     ISO Abbreviation:  IEEE Trans Biomed Eng     Publication Date:  2011 Jun 
Date Detail:
Created Date:  2011-05-19     Completed Date:  2011-09-15     Revised Date:  2012-04-13    
Medline Journal Info:
Nlm Unique ID:  0012737     Medline TA:  IEEE Trans Biomed Eng     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1827-38     Citation Subset:  IM    
Affiliation:
Scientific Computing and Imaging (SCI) Institute and the School of Computing, University of Utah, Salt Lake City, UT 84112, USA. dfwang@sci.utah.edu
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Animals
Body Surface Potential Mapping / methods*
Computer Simulation
Dogs
Finite Element Analysis*
Heart / physiology
Humans
Models, Cardiovascular*
Phantoms, Imaging
Signal Processing, Computer-Assisted*
Grant Support
ID/Acronym/Agency:
5P41RR012553-12/RR/NCRR NIH HHS; P41 GM103545-14/GM/NIGMS NIH HHS; P41 RR012553-11/RR/NCRR NIH HHS
Comments/Corrections

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