| Application of L1-norm regularization to epicardial potential reconstruction based on gradient projection. | |
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MedLine Citation:
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PMID: 21896965 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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The epicardial potential (EP)-targeted inverse problem of electrocardiography (ECG) has been widely investigated as it is demonstrated that EPs reflect underlying myocardial activity. It is a well-known ill-posed problem as small noises in input data may yield a highly unstable solution. Traditionally, L2-norm regularization methods have been proposed to solve this ill-posed problem. But the L2-norm penalty function inherently leads to considerable smoothing of the solution, which reduces the accuracy of distinguishing abnormalities and locating diseased regions. Directly using the L1-norm penalty function, however, may greatly increase computational complexity due to its non-differentiability. We propose an L1-norm regularization method in order to reduce the computational complexity and make rapid convergence possible. Variable splitting is employed to make the L1-norm penalty function differentiable based on the observation that both positive and negative potentials exist on the epicardial surface. Then, the inverse problem of ECG is further formulated as a bound-constrained quadratic problem, which can be efficiently solved by gradient projection in an iterative manner. Extensive experiments conducted on both synthetic data and real data demonstrate that the proposed method can handle both measurement noise and geometry noise and obtain more accurate results than previous L2- and L1-norm regularization methods, especially when the noises are large. |
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Authors:
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Liansheng Wang; Jing Qin; Tien Tsin Wong; Pheng Ann Heng |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-9-06 |
Journal Detail:
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Title: Physics in medicine and biology Volume: 56 ISSN: 1361-6560 ISO Abbreviation: - Publication Date: 2011 Sep |
Date Detail:
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Created Date: 2011-9-7 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0401220 Medline TA: Phys Med Biol Country: - |
Other Details:
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Languages: ENG Pagination: 6291-6310 Citation Subset: - |
Affiliation:
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Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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