@. Mollero, R. Pennec, X. Delingette, H. Ayache, N. Sermesant et al., Population-Based Priors in Cardiac Model Personalisation for Consistent Parameter Estimation in Heterogeneous Databases

D. Neumann, M. Rohé, . Datar, . Manasi, H. Lombaert et al., Propagation of Myocardial Fibre Architecture Uncertainty on Electromechanical Model Parameter Estimation: A Case Study, Peer-reviewed conferences with proceedings: ? 8th International Conference on Functional Imaging and Modeling of the Heart (FIMH), LNCS 9126, pp.448-456, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01241896

R. Mollero, X. Pennec, . Delingette, . Hervé, N. Ayache et al., A Multiscale Cardiac Model for Fast Personalisation and Exploitation, 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.174-182, 2016.
DOI : 10.1007/3-540-32494-1_4
URL : https://hal.archives-ouvertes.fr/hal-01360908

R. Molléro, J. Hauser, X. Pennec, . Datar, . Manasi et al., Longitudinal Parameter Estimation in 3D Electromechanical Models: Application to Cardiovascular Changes in Digestion, 9th international conference on Functional Imaging and Modeling of the Heart (FIMH), LNCS 10263, pp.432-440, 2017.
DOI : 10.1007/978-3-319-46726-9_21

R. Molléro, . Neumann, . Dominik, M. Rohé, . Datar et al., Longitudinal Analysis Using Personalised 3D Cardiac Models with Population-Based Priors: Application to Paediatric Cardiomyopathies, 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.350-358, 2017.
DOI : 10.1007/978-3-319-46726-9_21

M. Rohé, R. Molléro, . Sermesant, . Maxime, and X. Pennec, Highly reduced model of the cardiac function for fast simulation, 2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), p.12, 2016.
DOI : 10.1109/IVMSPW.2016.7528214

S. Roisin, L. Fovargue, J. Webb, R. Molléro, J. Lee et al., Estimation of Purkinje Activation from ECG: an Intermittent Left Bundle Branch Block Study, 7th International Statistical Atlases and Computational Modeling of the Heart (STACOM) Workshop, held in Conjunction with MICCAI 2016, pp.135-142, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01372924

@. Molléro, R. Pennec, X. Delingette, H. Ayache, N. Sermesant et al., Population-Based Priors in Cardiac Model Personalisation for Consistent Parameter Estimation in Heterogeneous Databases

R. Molléro, . Neumann, . Dominik, M. Rohé, . Datar et al., Propagation of Myocardial Fibre Architecture Uncertainty on Electromechanical Model Parameter Estimation: A Case Study, 8th International Conference on Functional Imaging and Modeling of the Heart (FIMH), LNCS 9126, pp.448-456, 2015.
DOI : 10.1007/978-3-319-20309-6_51

R. Molléro, X. Pennec, . Delingette, . Hervé, N. Ayache et al., A Multiscale Cardiac Model for Fast Personalisation and Exploitation, 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.174-182, 2016.
DOI : 10.1007/3-540-32494-1_4

E. Roy and . Albert, The response of the peripheral venous pressure to exercise in congestive heart failure, American heart journal, vol.43, issue.67, pp.395-400, 1952.

R. Rubin, . Aliev, V. Alexander, and . Panfilov, A simple two-variable model of cardiac excitation, Chaos, Solitons & Fractals, vol.7, issue.3, pp.293-301, 1996.

T. Arts, T. Delhaas, P. Bovendeerd, X. Verbeek, W. Frits et al., Adaptation to mechanical load determines shape and properties of heart and circulation: the CircAdapt model, American Journal of Physiology-Heart and Circulatory Physiology, vol.288, issue.4, pp.1943-1954, 2005.
DOI : 10.1016/0021-9290(95)00027-5

B. Baillargeon, N. Rebelo, D. David, . Fox, L. Robert et al., The Living Heart Project: A robust and integrative simulator for human heart function, European Journal of Mechanics - A/Solids, vol.48, pp.38-47, 2014.
DOI : 10.1016/j.euromechsol.2014.04.001

J. Bestel, F. Clément, and M. Sorine, A Biomechanical Model of Muscle Contraction, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.1159-1161, 2001.
DOI : 10.1007/3-540-45468-3_143

J. Boulakia and . Gerbeau, Parameter Identification in Cardiac Electrophysiology Using Proper Orthogonal Decomposition Method, International Conference on Functional Imaging and Modeling of the Heart, pp.315-322, 2011.
DOI : 10.1007/b96841
URL : https://hal.archives-ouvertes.fr/hal-00650606

R. Chabiniok, P. Moireau, P. Lesault, A. Rahmouni, J. Deux et al., Estimation of tissue contractility from cardiac cine-MRI using a biomechanical heart model, Biomechanics and Modeling in Mechanobiology, vol.3, issue.4, pp.609-630, 2012.
DOI : 10.1109/9.989154
URL : https://hal.archives-ouvertes.fr/hal-00654541

R. Chabiniok, V. Y. Wang, M. Hadjicharalambous, L. Asner, J. Lee et al., Multiphysics and multiscale modelling, data???model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics, Interface Focus, vol.18, issue.2, pp.2016-2033, 2016.
DOI : 10.1161/CIRCULATIONAHA.109.192278
URL : https://hal.archives-ouvertes.fr/hal-01277684

]. D. Chapelle, P. Le-tallec, P. Moireau, and M. Sorine, Energypreserving muscle tissue model: formulation and compatible discretizations, International Journal for Multiscale Computational Engineering, vol.10, issue.24, pp.2012-2038, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00678772

Z. Chen, R. Cabrera-lozoya, J. Relan, M. Sohal, A. Shetty et al., Biophysical Modeling Predicts Ventricular Tachycardia Inducibility and Circuit Morphology: A Combined Clinical Validation and Computer Modeling Approach, Journal of Cardiovascular Electrophysiology, vol.107, issue.7, pp.851-860, 2016.
DOI : 10.1016/j.pbiomolbio.2011.07.002

C. and A. Panfilov, A guide to modelling cardiac electrical activity in anatomically detailed ventricles, Progress in biophysics and molecular biology, pp.19-43, 2008.

O. Clayton, E. Bernus, H. Cherry, . Dierckx, . Fh-fenton et al., Models of cardiac tissue electrophysiology: Progress, challenges and open questions, Progress in biophysics and molecular biology, pp.22-48, 2011.
DOI : 10.1016/j.pbiomolbio.2010.05.008

D. Kevin, . Costa, W. Jeffrey, . Holmes, D. Andrew et al., Modelling cardiac mechanical properties in three dimensions, Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, vol.359, issue.1783, pp.1233-1250, 2001.

]. and A. Crozier, Personalised electromechanical modelling of cardiac resynchronisation therapy King's College London, 2015.

A. A. Cuellar, C. M. Lloyd, P. F. Nielsen, D. P. Bullivant, D. P. Nickerson et al., An Overview of CellML 1.1, a Biological Model Description Language, SIMULATION, vol.79, issue.12, pp.740-747, 2003.
DOI : 10.1098/rsta.2001.0817

H. Delingette, F. Billet, C. Ken, M. Wong, K. Sermesant et al., Personalization of Cardiac Motion and Contractility From Images Using Variational Data Assimilation, IEEE Transactions on Biomedical Engineering, vol.59, issue.1, pp.20-24, 2012.
DOI : 10.1109/TBME.2011.2160347
URL : https://hal.archives-ouvertes.fr/inria-00616183

E. Irene, R. Vignon-clementel, A. L. Figliola, and . Marsden, A Modular Numerical Method for Implicit 0D/3D Coupling in Cardiovascular Finite Element Simulations, J. Comput. Phys, vol.244, pp.63-79, 2013.

F. Alejandro, D. Frangi, J. A. Rueckert, . Schnabel, J. Wiro et al., Automatic construction of multiple-object three-dimensional statistical shape models: Application to cardiac modeling, IEEE transactions on medical imaging, vol.21, issue.9, pp.1151-1166, 2002.

A. Garny, J. Peter, and . Hunter, OpenCOR: a modular and interoperable approach to computational biology, Frontiers in Physiology, vol.5, issue.79, p.2015, 2015.
DOI : 10.1186/1752-0509-5-198

L. Giffard-roisin-2016-]-sophie-giffard-roisin, J. Fovargue, R. Webb, J. Molléro, H. Lee et al., Estimation of Purkinje Activation from ECG: An Intermittent Left Bundle Branch Block Study, 7th International Statistical Atlases and Computational Modeling of the Heart (STACOM) Workshop, Bibliography Held in Conjunction with MICCAI 2016, p.114, 2016.
DOI : 10.1007/3-540-32494-1_4

A. Richard, J. Gray, A. Jalife, . Panfilov, T. William et al., Nonstationary vortexlike reentrant activity as a mechanism of polymorphic ventricular tachycardia in the isolated rabbit heart, Circulation, vol.91, issue.9, pp.2454-2469, 1995.

J. Gray and . Jalife, Ventricular fibrillation and atrial fibrillation are two different beasts, Chaos: An Interdisciplinary Journal of Nonlinear Science, vol.31, issue.1, pp.65-78, 1998.
DOI : 10.1161/01.RES.48.1.39

M. Julius, . Guccione, D. Andrew, L. Mcculloch, and . Waldman, Passive material properties of intact ventricular myocardium determined from a cylindrical model, J Biomech Eng, vol.113, issue.1, pp.42-55, 1991.

A. Jakob and . Hauser, Comprehensive assessment of the global and regional vascular responses to food ingestion in humans using novel rapid MRI, Am. J. Physiol. Regul. Integr. Comp. Physiol, vol.310, issue.62, pp.541-545, 2016.

A. Patrick, H. Helm, L. Tseng, E. R. Younes, R. L. Mcveigh et al., Ex Vivo 3D Diffusion Tensor Imaging and Quantification of Cardiac Laminar Structure, Magnetic Resonance in Medicine, 2005.

L. Alan, . Hodgkin, F. Andrew, and . Huxley, A quantitative description of membrane current and its application to conduction and excitation in nerve, The Journal of physiology, vol.117, issue.4, pp.500-544, 1952.

A. Gerhard, . Holzapfel, C. Thomas, and . Gasser, A viscoelastic model for fiber-reinforced composites at finite strains: Continuum basis, computational aspects and applications, Computer methods in applied mechanics and engineering, vol.190, issue.34, pp.4379-4403, 2001.

T. Daphne and . Hsu, Heart Failure in Children, Circ. Heart. Fail, vol.2, issue.1, pp.63-70, 2009.

R. Humphrey, F. Strumpf, and . Yin, Determination of a constitutive relation for passive myocardium: I. A new functional form, Journal of biomechanical engineering, vol.112, issue.3, pp.333-339, 1990.

M. Jacques, . Huyghe, H. Dick, T. Van-campen, . Arts et al., The constitutive behaviour of passive heart muscle tissue: a quasilinear viscoelastic formulation, Journal of biomechanics, vol.24, issue.9, pp.841-849, 1991.

M. Jolly, C. Guetter, X. Lu, H. Xue, and J. Guehring, Automatic Segmentation of the Myocardium in Cine MR Images Using Deformable Registration, International Workshop on Statistical Atlases and Computational Models of the Heart, pp.98-108, 2011.
DOI : 10.1109/ICCV.2007.4408925

J. Simon, . Julier, K. Jeffrey, and . Uhlmann, A new extension of the Kalman filter to nonlinear systems. In Int. symp. aerospace/defense sensing, simul. and controls, pp.3-5, 1997.

E. Kayvanpour, T. Mansi, F. Sedaghat-hamedani, A. Amr, D. Neumann et al., Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart, PLOS ONE, vol.367, issue.1902, p.2015, 2015.
DOI : 10.1371/journal.pone.0134869.s006

C. Marc, A. Kennedy, and . Hagan, Predicting the output from a complex computer code when fast approximations are available, Biometrika, vol.87, issue.58, pp.1-13, 2000.

. Rcp-kerckhoffs, . Bovendeerd, . Jcs-kotte, K. Fw-prinzen, T. Smits et al., Homogeneity of Cardiac Contraction Despite Physiological Asynchrony of Depolarization: A Model Study, Annals of Biomedical Engineering, vol.31, issue.5, pp.536-547, 2003.
DOI : 10.1114/1.1566447

C. P. Roy, M. L. Kerckhoffs, Q. Neal, J. B. Gu, J. H. Bassingthwaighte et al., Coupling of a 3D Finite Element Model of Cardiac Ventricular Mechanics to Lumped Systems Models of the Systemic and Pulmonic Circulation, Annals of Biomedical Engineering, vol.35, issue.1, pp.1-18, 2007.

S. Ahmad, . Khalil, E. Brett, M. Bouma, and . Mofrad, A combined FEM/genetic algorithm for vascular soft tissue elasticity estimation, Cardiovascular Engineering, vol.6, issue.3, pp.93-102, 2006.

]. E. Konukoglu, J. Relan, U. Cilingir, B. Menze, P. Chinchapatnam et al., Efficient probabilistic model personalization integrating uncertainty on data and parameters: Application to Eikonal-Diffusion models in cardiac electrophysiology, Progress in Biophysics and Molecular Biology, vol.107, issue.1, pp.134-146, 2011.
DOI : 10.1016/j.pbiomolbio.2011.07.002
URL : https://hal.archives-ouvertes.fr/inria-00616198

]. W. Laskey, Estimation of total systemic arterial compliance in humans, Journal of Applied Physiology, vol.69, issue.1, pp.112-119, 1990.
DOI : 10.1152/jappl.1990.69.1.112

H. Laughlin, Cardiovascular response to exercise., Advances in Physiology Education, vol.277, issue.6, pp.244-259, 1999.
DOI : 10.1152/advances.1999.277.6.S244

E. Lluch, R. Doste, S. Giffard-roisin, A. This, M. Sermesant et al., Smoothed Particle Hydrodynamics for Electrophysiological Modeling: An Alternative to Finite Element Methods, International Conference on Functional Imaging and Modeling of the Heart, pp.333-343, 2017.
DOI : 10.3181/00379727-141-36927
URL : https://hal.archives-ouvertes.fr/hal-01533371

H. Lombaert, J. Peyrat, P. Croisille, S. Rapacchi, L. Fanton et al., Hervé Delingette and Nicholas Ayache. Statistical Analysis of the Human Cardiac Fiber Architecture from DT-MRI, Proceedings of FIMH Conference 2011, pp.171-179, 2011.

R. Lopez-perez-2015-]-alejandro-lopez-perez, . Sebastian, M. Jose, and . Ferrero, Three-dimensional cardiac computational modelling: methods, features and applications, Biomedical engineering online, vol.14, issue.1, pp.35-2015

S. Marchesseau, T. Heimann, S. Chatelin, R. Willinger, and H. Delingette, Multiplicative Jacobian Energy Decomposition Method for Fast Porous Visco-Hyperelastic Soft Tissue Model, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.235-242, 2010.
DOI : 10.1007/978-3-642-15705-9_29
URL : https://hal.archives-ouvertes.fr/hal-00593207

]. S. Marchesseau, H. Delingette, M. Sermesant, and N. Ayache, Fast parameter calibration of a cardiac electromechanical model from medical images based on the unscented transform, Biomechanics and Modeling in Mechanobiology, vol.4, issue.7, pp.815-831, 2013.
DOI : 10.1016/j.jmbbm.2011.03.018
URL : https://hal.archives-ouvertes.fr/hal-00813847

]. Marchesseau, H. Delingette, M. Sermesant, R. Cabrera-lozoya, C. Tobon-gomez et al., Personalization of a cardiac electromechanical model using reduced order unscented Kalman filtering from regional volumes, Medical Image Analysis, vol.17, issue.7, pp.816-829, 2013.
DOI : 10.1016/j.media.2013.04.012
URL : https://hal.archives-ouvertes.fr/hal-00819806

]. Mcleod, T. Mansi, M. Sermesant, G. Pongiglione, and X. Pennec, Statistical Shape Analysis of Surfaces in Medical Images Applied to the Tetralogy of Fallot Heart, Modeling in Computational Biology and Biomedicine, pp.165-191, 2013.
DOI : 10.1007/978-3-642-31208-3_5
URL : https://hal.archives-ouvertes.fr/hal-00813850

L. Mihalef, T. Itu, P. Mansi, and . Sharma, Lumped Parameter Whole Body Circulation Modelling In Patient-specific Hemodynamic Computations: Application to Personalized Diagnosis of Cardiovascular Pathologies, pp.111-152, 2017.

C. Colleen, . Mitchell, G. David, and . Schaeffer, A two-current model for the dynamics of cardiac membrane, Bulletin of mathematical biology, vol.65, issue.5, pp.767-793, 2003.

P. Moireau and D. Chapelle, Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems, ESAIM: Control, Optimisation and Calculus of Variations, vol.14, issue.2, pp.380-405, 2011.
DOI : 10.1002/stc.186
URL : https://hal.archives-ouvertes.fr/inria-00550104

R. Molléro, D. Neumann, M. Rohé, M. Datar, H. Lombaert et al., Propagation of Myocardial Fibre Architecture Uncertainty on Electromechanical Model Parameter Estimation: A Case Study, Functional Imaging and Modeling of the Heart 8th International Conference. Proceedings, pp.448-456, 2015.
DOI : 10.1007/978-3-319-20309-6_51

R. Mollero, X. Pennec, H. Delingette, N. Ayache, and M. Sermesant, A Multiscale Cardiac Model for Fast Personalisation and Exploitation, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.174-182, 2016.
DOI : 10.1007/3-540-32494-1_4
URL : https://hal.archives-ouvertes.fr/hal-01360908

]. Molléro, H. Delingette, M. Datar, T. Heimann, J. Hauser et al., Xavier Pennec and Maxime Sermesant. Longitudinal Analysis using Personalised 3D Cardiac Models with Population-Based Priors: Application to Paediatric Cardiomyopathies, Medical Image Computing and Computer Assisted Intervention (MICCAI), MICCAI 2017, pp.69-110, 2017.

]. Molléro, X. Pennec, H. Delingette, A. Garny, N. Ayache et al., Multifidelity-CMA: a multifidelity approach for efficient personalisation of 3D cardiac electromechanical models, Biomechanics and Modeling in Mechanobiology, vol.27, issue.5, pp.38-113, 2017.
DOI : 10.1093/bioinformatics/btq723

A. Roch, J. Molléro, X. Hauser, M. Pennec, H. Datar et al., Tobias Heimann and Maxime Sermesant. Longitudinal Parameter Estimation in 3D Electromechanical Models: Application to Cardiovascular Changes in Digestion, FIMH 2017 -9th international conference on Functional Imaging and Modeling of the Heart, pp.61-79, 2017.

P. Martyn, . Nash, J. Peter, and . Hunter, Computational mechanics of the heart, Journal of elasticity and the physical science of solids, vol.61, issue.1-3, pp.113-141, 2000.

P. Martyn, A. V. Nash, and . Panfilov, Electromechanical model of excitable tissue to study reentrant cardiac arrhythmias, Progress in biophysics and molecular biology, pp.501-522, 2004.

T. Dominik-neumann, B. Mansi, A. Georgescu, E. Kamen, A. Kayvanpour et al., Robust Image-Based Estimation of Cardiac Tissue Parameters and Their Uncertainty from Noisy Data, Medical Image Computing and Computer-Assisted Intervention?MICCAI 2014, pp.9-16, 2014.

T. Dominik-neumann, S. Mansi, I. Grbic, B. Voigt, E. Georgescu et al., Automatic image-to-model framework for patient-specific electromechanical modeling of the heart, Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on, pp.935-938, 2014.

T. Neumann, L. M. Mansi, B. Itu, E. Georgescu, F. Kayvanpour et al., A self-taught artificial agent for multi-physics computational model personalization, abs/1605.00303, pp.2016-2035, 2016.
DOI : 10.1016/j.media.2016.04.003

. Nordsletten, . Mccormick, P. Kilner, . Hunter, N. Kay et al., Fluid-solid coupling for the investigation of diastolic and systolic human left ventricular function, International Journal for Numerical Methods in Biomedical Engineering, vol.28, issue.2, pp.1017-1039, 2011.
DOI : 10.1016/j.medengphy.2005.10.004

S. Pant, C. Corsini, C. Baker, . Tain-yen, G. Hsia et al., Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation, Bibliography Selected Articles from the International Conference on CFD in Medicine and Biology, pp.2162-2173, 2015.
DOI : 10.1016/j.jbiomech.2015.11.030
URL : https://hal.archives-ouvertes.fr/hal-01240146

S. Pant, C. Corsini, C. Baker, . Tain-yen, G. Hsia et al., Inverse problems in reduced order models of cardiovascular haemodynamics: aspects of data assimilation and heart rate variability, Journal of The Royal Society Interface, vol.445, issue.126, p.2017
DOI : 10.1007/s00424-002-0931-9
URL : https://hal.archives-ouvertes.fr/hal-01413446

N. Panthee, J. Okada, T. Washio, Y. Mochizuki, R. Suzuki et al., Tailor-made heart simulation predicts the effect of cardiac resynchronization therapy in a canine model of heart failure, Medical Image Analysis, vol.31, pp.46-62, 2016.
DOI : 10.1016/j.media.2016.02.003

K. Benjamin-peherstorfer, M. Willcox, and . Gunzburger, Survey of multifidelity methods in uncertainty propagation, inference, and optimization. 2016, pp.65-73, 2016.

P. Peng, K. Lekadir, A. Gooya, L. Shao, E. Steffen et al., A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging, Magnetic Resonance Materials in Physics, Biology and Medicine, vol.29, issue.9, pp.155-195, 2016.
DOI : 10.1007/978-3-642-38899-6_21

]. E. Pernod, A multi-front eikonal model of cardiac electrophysiology for interactive simulation of radio-frequency ablation, Computers & Graphics, vol.35, issue.2, pp.431-440, 2011.
DOI : 10.1016/j.cag.2011.01.008
URL : https://hal.archives-ouvertes.fr/inria-00616180

C. Petitjean and J. Dacher, A review of segmentation methods in short axis cardiac MR images, Medical Image Analysis, vol.15, issue.2, pp.169-184, 2011.
DOI : 10.1016/j.media.2010.12.004
URL : https://hal.archives-ouvertes.fr/hal-00551034

J. Peyrat, M. Sermesant, X. Pennec, H. Delingette, C. Xu et al., A Computational Framework for the Statistical Analysis of Cardiac Diffusion Tensors: Application to a Small Database of Canine Hearts, IEEE Transactions on Medical Imaging, vol.26, issue.11, pp.1500-1514, 2007.
DOI : 10.1109/TMI.2007.907286
URL : https://hal.archives-ouvertes.fr/inria-00616023

J. Michael and . Powell, The BOBYQA algorithm for bound constrained optimization without derivatives, 2009.

J. Relan, M. Pop, H. Delingette, G. Wright, N. Ayache et al., Estimation of Reaction, Diffusion and Restitution Parameters for a 3D Myocardial Model Using Optical Mapping and MRI, MICCAI Workshop on Statistical Atlases and Computational Models of the Heart: Mapping Structure and Function (STACOM) and a Cardiac Electrophysiological Simulation Challenge (CESC'10), pp.270-280, 2010.
DOI : 10.1007/978-3-642-15835-3_28
URL : https://hal.archives-ouvertes.fr/inria-00616151

M. Rohé, R. Molléro, M. Sermesant, and X. Pennec, Highly reduced model of the cardiac function for fast simulation, 2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), p.92, 2016.
DOI : 10.1109/IVMSPW.2016.7528214

Z. Qian, P. Clarysse, D. Metaxas, L. Axel, E. Isabelle et al., Fast and automated creation of patient-specific 3D heart model from Tagged MRI, Proceedings of the MICCAI 2006 SA2PM Workshop, 2006.

H. Schmid, . Oâcallaghan, . Nash, . Lin, . Ij-legrice et al., Myocardial material parameter estimation, Biomechanics and Modeling in Mechanobiology, vol.32, issue.2, pp.161-173, 2008.
DOI : 10.1161/01.RES.32.3.314

P. Seegerer, T. Mansi, M. Jolly, D. Neumann, B. Georgescu et al., Estimation of Regional Electrical Properties of the Heart from 12-Lead ECG and Images, LNCS, vol.8896, issue.21, pp.19-29, 2015.
DOI : 10.1007/978-3-319-14678-2_21

M. Sermesant, R. Chabiniok, P. Chinchapatnam, T. Mansi, F. Billet et al., Patient-specific electromechanical models of the heart for the prediction of pacing acute effects in CRT: A preliminary clinical validation, Medical Image Analysis, vol.16, issue.1, pp.201-215, 2012.
DOI : 10.1016/j.media.2011.07.003

R. Schulze, I. Hose, P. Valverde, C. Beerbaum, M. Staicu et al., euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling, Interface Focus, vol.1, issue.3, pp.349-364, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00616189

D. Daniel and . Streeter, Gross morphology and fiber geometry of the heart. Handbook of physiology, pp.61-112, 1979.

A. Suinesiaputra, R. Brett, . Cowan, O. Ahmed, . Al-agamy et al., A collaborative resource to build consensus for automated left ventricular segmentation of cardiac MR images, Medical Image Analysis, vol.18, issue.1, pp.50-62, 2014.
DOI : 10.1016/j.media.2013.09.001
URL : https://hal.archives-ouvertes.fr/hal-00857223

D. Noble, . Noble, V. Alexander, and . Panfilov, A model for human ventricular tissue, Biomechanically-constrained 4D estimation of myocardial motion International Conference on Medical Image Computing and Computer- Assisted Intervention, pp.257-265, 2004.

D. James, . Thomas, E. Arthur, and . Weyman, Numerical modeling of ventricular filling, Annals of biomedical engineering, vol.20, issue.1, pp.19-39, 1992.

A. Natalia and . Trayanova, Whole-heart modeling Circulation research, pp.113-128, 2011.

X. Tom-vercauteren and . Pennec, Diffeomorphic demons: Efficient non-parametric image registration, NeuroImage, vol.45, issue.1, pp.61-72, 2009.
DOI : 10.1016/j.neuroimage.2008.10.040

E. Irene, A. Vignon-clementel, . Figueroa, E. Kenneth, . Jansen et al., Outflow boundary conditions for threedimensional finite element modeling of blood flow and pressure in arteries, Computer methods in applied mechanics and engineering, vol.195, issue.29, pp.3776-3796, 2006.

Y. Vicky, . Wang, . Lam, B. Daniel, . Ennis et al., Modelling passive diastolic mechanics with quantitative MRI of cardiac structure and function, Medical image analysis, vol.13, issue.5, pp.773-784, 2009.

Y. Vicky, C. Wang, A. F. Hoogendoorn, . Frangi, R. Brett et al., Automated personalised human left ventricular FE models to investigate heart failure mechanics, International Workshop on Statistical Atlases and Computational Models of the Heart, pp.307-316, 2012.

. Wang, . Georgescu, . Chen, . Wu, . Wang et al., Learning-Based Detection and Tracking in Medical Imaging: A Probabilistic Approach, LNCVB, pp.209-235, 2013.
DOI : 10.1007/978-94-007-5446-1_9

]. Wang, B. Georgescu, T. Chen, W. Wu, P. Wang et al., Razvan Ionasec, Yefeng Zheng and Dorin Comaniciu. Learning-based detection and tracking in medical imaging: a probabilistic approach, Deformation Models, pp.209-235, 2013.

]. Westerhof, F. Bosman, J. Cornelis, A. Vries, and . Noordergraaf, Analog studies of the human systemic arterial tree, Journal of Biomechanics, vol.2, issue.2, p.17, 1969.
DOI : 10.1016/0021-9290(69)90024-4

]. , Y. Larry, and A. Taber, The possible role of poroelasticity in the apparent viscoelastic behavior of passive cardiac muscle, Journal of biomechanics, vol.24, issue.7, pp.587-597, 1991.

T. Yu, C. M. Lloyd, D. P. Nickerson, M. T. Cooling, A. K. Miller et al., The Physiome Model Repository 2, Bioinformatics, vol.20, issue.13, p.743, 2011.
DOI : 10.1093/bioinformatics/bth200

O. Zettinig, T. Mansi, D. Neumann, B. Georgescu, S. Rapaka et al., Data-driven estimation of cardiac electrical diffusivity from 12-lead ECG signals, Medical Image Analysis, vol.18, issue.8, pp.1361-1376, 2014.
DOI : 10.1016/j.media.2014.04.011