title: Estimation of cardiac electrical propagation from medical image sequence.
abstract: A novel strategy is presented to recover cardiac electrical excitation pattern from tomographic medical image sequences. The geometrical/physical representation of the heart and the dense motion field of the myocardium are first derived from imaging data through segmentation and motion recovery. The myocardial active forces are then calculated through the law of force equilibrium from the motion field, realized with a stochastic multiframe algorithm. Since tissue active forces are physiologically driven by electrical excitations, we can readily relate the pattern of active forces to the pattern of electrical propagation in myocardium, where spatial regularization is enforced. Experiments are conducted on three-dimensional synthetic data and canine magnetic resonance image sequence with favorable results.
authors.affiliation: Medical Image Computing Group, Hong Kong University of Science & Technology, Hong Kong, China. eezhy@ust.hk
authors.forename: Heye
authors.initials: H
authors.lastname: Zhang
authors.forename: Chun Lok
authors.initials: CL
authors.lastname: Wong
authors.forename: Pengcheng
authors.initials: P
authors.lastname: Shi
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000465:Algorithms; D001185:Artificial Intelligence; D018780:Body Surface Potential Mapping / Q000379:methods*; D003198:Computer Simulation; D006329:Heart Conduction System / Q000033:anatomy & histology* / Q000502:physiology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique