TV Regularized Low-Rank Framework for Localizing Premature Ventricular Contraction Origin

Fang, Lin; Qi, Zhuang; Mao, Wei; Chen, Yunmei; Liu, Huafeng

doi:10.1109/access.2019.2899696

Cited by 4 publications

(4 citation statements)

References 42 publications

(52 reference statements)

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“…The marginal likelihood of the MCG data p(B | α, β) is obtained by integrating over the sources s, From Eqs. ( 9) and ( 12), the evidence function is written in the form where (10) www.nature.com/scientificreports/…”

Section: Methodsmentioning

confidence: 99%

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Localization of magnetocardiographic sources for myocardial infarction cases using deterministic and Bayesian approaches

Bhat

Pal

Anitha

et al. 2022

Sci Rep

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In this paper, the inverse problems of cardiac sources using analytical and probabilistic methods are solved and discussed. The standard Tikhonov regularization technique is solved initially to estimate the under-determined heart surface potentials from Magnetocardiographic (MCG) signals. The results of the deterministic method subjected to noise in the measurements are discussed and compared with the probabilistic models. Hierarchical Bayesian modeling with fixed Gaussian prior is employed to quantify the uncertainties in source reconstructions. A novel application of Variational Bayesian inference approach has been presented to estimate the heart sources. The reconstruction results of Variational Bayesian model with non-stationary priors are compared with solutions of simplistic Bayesian approach; and the performances are evaluated using Root Mean Square Error (RMSE) and correlation co-efficient metrics. The Bayesian solutions in the study are also extended to localize the MCG sources for two types of Myocardial infarction cases.

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Section: Methodsmentioning

confidence: 99%

“…Fang et al 10 proposed a novel framework to solve the ill posed inverse problems of spatiotemporal ECG using sparse decomposition and total variation method.…”

Section: Related Workmentioning

confidence: 99%

Localization of magnetocardiographic sources for myocardial infarction cases using deterministic and Bayesian approaches

Bhat

Pal

Anitha

et al. 2022

Sci Rep

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“…The torso model was created by matching the 64-electrode positions to a standard torso template with 235 triangles of Delaunay triangulation. 15 The mathematical method of the ECGI procedure was also described in our previous study. 15 Briefly, a novel framework based on low-rank and sparse decomposition (LSD) + total variation (TV) was proposed to reconstruct the cardiac electrical activity of PVCs/VT based on the surface potential data and geometrical information.…”

Section: Methodsmentioning

confidence: 99%

“…15 The mathematical method of the ECGI procedure was also described in our previous study. 15 Briefly, a novel framework based on low-rank and sparse decomposition (LSD) + total variation (TV) was proposed to reconstruct the cardiac electrical activity of PVCs/VT based on the surface potential data and geometrical information. The origin of the PVCs/VT was then prospectively localized via the reconstructed cardiac potential maps.…”

Section: Methodsmentioning

confidence: 99%

Comparative analysis of electrocardiographic imaging and ECG in predicting the origin of outflow tract ventricular arrhythmias

et al. 2020

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The aim of this study was to investigate the accuracy of electrocardiographic imaging (ECGI) in localizing the origin of outflow tract ventricular arrhythmias (OTVAs) and compare its performance with that of seven published 12-lead electrocardiography (ECG) algorithms. Methods: Patients with OTVAs who were undergoing catheter ablation were prospectively investigated. The OVTA origins were localized using both ECGI and seven 12-lead ECG algorithms, with the successful ablation site set as the gold standard. The performance of the ECGI and 12-lead ECG algorithms were compared. Results: Twenty-seven patients were enrolled into the study. The ECGI system correctly identified the chamber of OTVA origin in 27/27 (100%) patients and the sublocalization within the right ventricular outflow tract (RVOT) in 21/22 (95.5%) patients. However, the ECG algorithms correctly diagnosed the chamber and sublocalization in only 21/27 (77.8%) patients and 13/22 (59.1%) patients, respectively, which was significantly lower compared with the ECGI system. Conclusions: Non-invasive ECGI can accurately predict the origin of OTVAs in a manner that is superior to that of conventional 12-lead ECGs in differentiating the RVOT from the left ventricular outflow tract (LVOT) and septum from free wall in the RVOT. This provides a useful tool to guide catheter ablation. This trial has been registered in the Chinese Clinical Trial Registry (Registration number: ChiCTR1900025527).

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Noninvasive Epicardial and Endocardial Extracellular Potentials Imaging with Low-Rank and Non-local Total Variation Regularization

Liu

2019

Lecture Notes in Computer Science

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TV Regularized Low-Rank Framework for Localizing Premature Ventricular Contraction Origin

Cited by 4 publications

References 42 publications

Localization of magnetocardiographic sources for myocardial infarction cases using deterministic and Bayesian approaches

Localization of magnetocardiographic sources for myocardial infarction cases using deterministic and Bayesian approaches

Comparative analysis of electrocardiographic imaging and ECG in predicting the origin of outflow tract ventricular arrhythmias

Noninvasive Epicardial and Endocardial Extracellular Potentials Imaging with Low-Rank and Non-local Total Variation Regularization

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