NDLI: Evaluation of approaches to solving electrocardiographic imaging problem

Content Provider	IEEE Xplore Digital Library
Author	Milanic, M. Jazbinsek, V. Wang, D.F. Sinstra, J. MacLeod, R.S. Brooks, D.H. Hren, R.
Copyright Year	2009
Description	Author affiliation: Jozef Stefan Institute, Ljubljana, Slovenia (Milanic, M.) \|\| Institute of Mathematics, Physics, and Mechanics, University of Ljubljana, Slovenia (Jazbinsek, V.; Hren, R.) \|\| Dept of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA (Brooks, D.H.) \|\| Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, USA (Wang, D.F.; Sinstra, J.; MacLeod, R.S.)
Abstract	Electrocardiographic imaging (ECGI) is a widely used method of computing potentials on the epicardium from measured or simulated potentials on the torso surface. The main challenge of the electrocardiographic imaging problem lies in its intrinsic ill-posedness, and many regularization techniques have been developed to smooth out the solution. It is still an ongoing research subject to choose proper regularization methods and to determine their proper amount for obtaining clinically acceptable solutions. This study systematically compares various regularization techniques for the ECGI problem under a unified simulation framework. The framework consists of an electrolytic human torso tank containing a live canine heart, with the cardiac source being modeled by potentials measured on a cylindrical cage placed around the heart. We tested 14 different regularization techniques to solve the inverse problem of recovering epicardial potentials, and found that non-quadratic methods (total variation algorithms) were the most robust and resulted in the lowest reconstruction errors.
Starting Page	177
Ending Page	180
File Size	261704
Page Count	4
File Format	PDF
ISBN	9781424472819
ISSN	02766547
e-ISBN	9781424472826
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Computers in Cardiology(CinC)
Subject Keyword	Torso Heart Computational modeling Humans Testing Inverse problems Robustness Image reconstruction
Content Type	Text
Resource Type	Article

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