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Inverse electrocardiography (IECG) estimates cardiac electrical dynamics from body surface electrocardiographic data. As a common practice, all existing IECG problems are solved on anatomically-detailed heart and torso models derived from tomographic images of individual subjects. This practice constitutes a major obstacle to clinical translation of IECG methods, imposing high demands on the quality...
Non-invasive electrocardiographic imaging (ECGI) combines body surface electrocardiographic information with anatomical data to estimate electrical dynamics of the heart on the surface or transmurally across the depth of the myocardium. As a standard practice, ECGI techniques rely on anatomically detailed heart and torso models derived from high quality tomographic data. This practice not only imposes...
To systematically couple images and physiological models according to their respective merits, state-space filtering frameworks have been proposed for cardiac deformation recovery with promising results. Nevertheless, as thousands of forward simulations are required in every filtering step, the computational complexity is too high to be practical. To reduce the computational complexity without a significant...
To noninvasively reconstruct transmembrane potential (TMP) dynamics throughout the 3D myocardium using body surface potential recordings, it is necessary to combine prior physiological models and patient's data with regard to their respective uncertainties. To fulfill model-data melding for this large-scale and high-dimensional system, data assimilation with proper computational reduction is needed...
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