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Additional info for Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges: Second International Workshop, STACOM 2011, Held in Conjunction with MICCAI 2011, Toronto, ON, Canada, September 22, 2011, Revised Selected Papers
Fig 5(c & d) shows good matching of the LV endocardial isochrones, as well as epicardial isochrones with Fig 5(a & b) and data (Fig 3(a & b)). Thus epicardial mapping could be suﬃcient enough to reproduce the true wave propagation dynamics, as compared to endocardial mapping data. This is conﬁrmed by the low prediction errors on the endocardial surface, as shown in Fig 7(b).
11. : Coupled personalization of cardiac electrophysiology models for prediction of ischaemic ventricular tachycardia. Interface Focus 1(3), 396 (2011) 12. : A two-current model for the dynamics of cardiac membrane. Bulletin of Mathematical Biology 65(5), 767–793 (2003) 13. : Vortex dynamics in three-dimensional continuous myocardium with ﬁber rotation: ﬁlament instability and ﬁbrillation. Chaos 8(1), 20–47 (1998) 14. : Quantitative comparison of two cardiac electrophysiology models using personalisation to optical and mr data.
The phantom actuator was synchronized with the MR scanner and echocardiography system by sending a 10mV pp electrocardiography (ECG) waveform to the optically decoupled standard ECG monitoring unit. The datasets were acquired at the Department of Internal Medicine II Cardiology, University of Ulm, Germany. – The volunteers: ﬁfteen healthy volunteers without clinical history of cardiac disease were recruited (3 female, aged 28 ± 5 years). Demographics and body surface area measurements are summarized in Table 1.