Two hybrid regularization frameworks for solving the electrocardiography inverse problem

Jiang, M, Xia, L, Shou, G, Liu, F. and Crozier, S. (2008) Two hybrid regularization frameworks for solving the electrocardiography inverse problem. Physics in Medicine and Biology, 53 18: 5151-5164. doi:10.1088/0031-9155/53/18/020

Author Jiang, M
Xia, L
Shou, G
Liu, F.
Crozier, S.
Title Two hybrid regularization frameworks for solving the electrocardiography inverse problem
Journal name Physics in Medicine and Biology   Check publisher's open access policy
ISSN 0031-9155
Publication date 2008-09-01
Year available 2008
Sub-type Article (original research)
DOI 10.1088/0031-9155/53/18/020
Open Access Status Not yet assessed
Volume 53
Issue 18
Start page 5151
End page 5164
Total pages 14
Editor Webb, S.
Place of publication United Kingdom
Publisher Institute of Physics Publishing
Language eng
Subject C1
970109 Expanding Knowledge in Engineering
090399 Biomedical Engineering not elsewhere classified
Abstract In this paper, two hybrid regularization frameworks, LSQR-Tik and Tik-LSQR, which integrate the properties of the direct regularization method (Tikhonov) and the iterative regularization method (LSQR), have been proposed and investigated for solving ECG inverse problems. The LSQR-Tik method is based on the Lanczos process, which yields a sequence of small bidiagonal systems to approximate the original ill-posed problem and then the Tikhonov regularization method is applied to stabilize the projected problem. The Tik-LSQR method is formulated as an iterative LSQR inverse, augmented with a Tikhonov-like prior information term. The performances of these two hybrid methods are evaluated using a realistic heart-torso model simulation protocol, in which the heart surface source method is employed to calculate the simulated epicardial potentials (EPs) from the action potentials (APs), and then the acquired EPs are used to calculate simulated body surface potentials (BSPs). The results show that the regularized solutions obtained by the LSQR-Tik method are approximate to those of the Tikhonov method, the computational cost of the LSQR-Tik method, however, is much less than that of the Tikhonov method. Moreover, the Tik-LSQR scheme can reconstruct the epcicardial potential distribution more accurately, specifically for the BSPs with large noisy cases. This investigation suggests that hybrid regularization methods may be more effective than separate regularization approaches for ECG inverse problems.
Keyword Hybrid regularization frameworks
Inverse Problem
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID 2003CB716106
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2009 Higher Education Research Data Collection
School of Information Technology and Electrical Engineering Publications
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