NONINVASIVE IMAGING OF 3D CARDIAC ELECTROPHYSIOLOGY
Noninvasive imaging of cardiac electrophysiology has been an active area with increasing clinical significance. Instead of equivalent-source-based approaches, however, noninvasive 3D cardiac transmembrane potentials (TMP) mapping remains a formidable goal due to the remote and integrative nature of body surface potential recordings. We recognized the incorporation of a priori physiological knowledge as one desired paradigm and presented a model-based general Bayesian framework for 3D TMP mapping from body surface potential maps (BSPMs), based on optimal integration of a priori physiological models and patient-specific observations within their respective uncertainties. An alternative being the use of additional observations for volumetric cardiac electrophysiological information, we also worked on recovering cardiac electrical excitation pattern from tomographic medical image sequences. Furthermore, aiming for a model-based data fusion framework wherein information from BSPMs and medical image sequences are integrated, we presented the dynamic image guided mapping of 3D cardiac electrophysiology.