Total Variation Regularization in Electrocardiographs Mapping
Electrocardiographic mapping (ECGM) is to estimate the cardiac activities from the measured body surface potentials (BSPs), in which the epicar-dial potentials (EPs) is often reconstructed. One of the challenges in ECGM problem is its ill-posedness, and regularization techniques are needed to obtain the clinically reasonable solutions. The total variation (TV) method has been validated in keeping the sharp edges and has found some preliminary applications in ECG inverse problem. In this study, we applied and compared two algorithms: lagged diffusivity (LD) fixed point iteration and primal dual-interior point method (PD-IPM), to implement TV regularization method in ECGM problem. With a realistic heart-lungtorso model, the TV methods are tested and compared to the L2-norm regularization methods in zero-and first-order. The simulation results demonstrate that the TV method can generate better EPs compared to the zero-order Tikhonov method. Compared to the firstorder Tik-honov method, the TVs results are much sharper. For the two algorithms in TV method, the LD algorithm seems more robust than the PD-IPM in ECGM problem, though the PD-IPM converges faster.
Guofa Shou Ling Xia Mingfeng Jiang
Department of Biomedical Engineering, Zhejiang University, Hangzhou, P.R.China, 310027 The College of Electronics and Informatics, Zhejiang Sci-Tech University,Hangzhou, 310018, P.R.China
国际会议
无锡
英文
51-59
2010-09-17（万方平台首次上网日期，不代表论文的发表时间）