2009 IEEE Conference on Computer Vision and Pattern Recognition (2009)
Miami, FL, USA
June 20, 2009 to June 25, 2009
Linwei Wang , Computational Biomedicine Laboratory, Rochester, NY, USA
Heye Zhang , Bioengineering Instiute, University of Auckland, Australia
Ken C.L. Wong , Computational Biomedicine Laboratory, Rochester, NY, USA
Huafeng Liu , State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, China
Pengcheng Shi , Computational Biomedicine Laboratory, Rochester, NY, USA
Volumetric details of cardiac electrophysiology, such as transmembrane potential dynamics and tissue excitability of the myocardium, are of fundamental importance for understanding normal and pathological cardiac mechanisms, and for aiding the diagnosis and treatment of cardiac arrhythmia. Noninvasive observations, however, are made on body surface as an integration-projection of the volumetric phenomena inside patient's heart. We present a physiological-model-constrained statistical framework where prior knowledge of general myocardial electrical activity is used to guide the reconstruction of patient-specific volumetric cardiac electrophysiological details from body surface potential data. Sequential data assimilation with proper computational reduction is developed to estimate transmembrane potential and myocardial excitability inside the heart, which are then utilized to depict arrhythmogenic substrates. Effectiveness and validity of the framework is demonstrated through its application to evaluate the location and extent of myocardial infract using real patient data.
cardiology, electromyography, image reconstruction, medical image processing, statistical analysis
L. Wang, H. Zhang, K. C. Wong, H. Liu and P. Shi, "Noninvasive volumetric imaging of cardiac electrophysiology," 2009 IEEE Conference on Computer Vision and Pattern Recognition(CVPR), Miami, FL, USA, 2018, pp. 2176-2183.