@article {43160,
	title = {Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease},
	journal = {JACC: Cardiovascular Imaging},
	volume = {21222188431383612310012114772548157661151811577100346352343574},
	year = {2023},
	month = {Jan-01-2023},
	publisher = {ELSEVIER},
	issn = {1936878X},
	doi = {10.1016/j.jcmg.2022.10.020},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1936878X22006581},
	author = {Richard E. {Jones} and Hassan A. {Zaidi} and Daniel J. {Hammersley} and Hatipoglu, Suzan and Owen, Ruth and Balaban, Gabriel and de Marvao, Antonio and Simard, Fran{\c c}ois and Amrit S. {Lota} and Mahon, Ciara and Almogheer, Batool and Mach, Lukas and Musella, Francesca and Chen, Xiuyu and Gregson, John and Lazzari, Laura and Ravendren, Andrew and Leyva, Francisco and Zhao, Shihua and Vazir, Ali and Lamata, Pablo and Brian P. {Halliday} and Dudley J. {Pennell} and Martin J. {Bishop} and Sanjay K. {Prasad}}
}
@article {43161,
	title = {Machine learning analysis of complex late gadolinium enhancement patterns to improve risk prediction of major arrhythmic eventsBackgroundObjectiveMethodsResultsConclusionData_Sheet_1.PDF},
	journal = {Frontiers in Cardiovascular Medicine},
	volume = {1017164742772491571142121664485113112366167063211822},
	year = {2023},
	month = {Jul-02-2023},
	publisher = {Frontiers},
	doi = {10.3389/fcvm.2023.108277810.3389/fcvm.2023.1082778.s001},
	url = {https://www.frontiersin.org/articles/10.3389/fcvm.2023.1082778/fullhttps://www.frontiersin.org/articles/10.3389/fcvm.2023.1082778/fullhttps://www.frontiersin.org/articles/10.3389/fcvm.2023.1082778/supplementary-material/10.3389/fcvm.2023.1082778.s001},
	author = {Hassan A. {Zaidi} and Richard E. {Jones} and Daniel J. {Hammersley} and Hatipoglu, Suzan and Balaban, Gabriel and Mach, Lukas and Brian P. {Halliday} and Lamata, Pablo and Sanjay K. {Prasad} and Martin J. {Bishop}}
}
@article {27946,
	title = {Scar shape analysis and simulated electrical instabilities in a non-ischemic dilated cardiomyopathy patient cohort},
	journal = {PLOS Computational Biology},
	year = {2019},
	month = {Apr-10-2021},
	publisher = {PLOS},
	url = {https://dx.plos.org/10.1371/journal.pcbi.100742},
	author = {Balaban, Gabriel and Brian P. {Halliday} and Bai, Wenjia and Porter, Bradley and Malvuccio, Carlotta and Lamata, Pablo and Christopher A. {Rinaldi} and Plank, Gernot and Rueckert, Daniel and Sanjay K. {Prasad} and Martin J. {Bishop}},
	editor = {Andrew D. {McCulloch}}
}
@article {23371,
	title = {A computational pipeline for quantification of mouse myocardial stiffness parameters},
	journal = {Computers in Biology and Medicine},
	volume = {53},
	year = {2014},
	pages = {65{\textendash}75},
	publisher = {Comput. Biol. Med.},
	abstract = {The mouse is an important model for theoretical-experimental cardiac research, and biophysically based whole organ models of the mouse heart are now within reach. However, the passive material properties of mouse myocardium have not been much studied. We present an experimental setup and associated computational pipeline to quantify these stiffness properties. A mouse heart was excised and the left ventricle experimentally inflated from 0 to 1.44kPa in eleven steps, and the resulting deformation was estimated by echocardiography and speckle tracking. An in silico counterpart to this experiment was built using finite element methods and data on ventricular tissue microstructure from diffusion tensor {MRI}. This model assumed a hyperelastic, transversely isotropic material law to describe the force-deformation relationship, and was simulated for many parameter scenarios, covering the relevant range of parameter space. To identify well-fitting parameter scenarios, we compared experimental and simulated outcomes across the whole range of pressures, based partly on gross phenotypes (volume, elastic energy, and short- and long-axis diameter), and partly on node positions in the geometrical mesh. This identified a narrow region of experimentally compatible values of the material parameters. Estimation turned out to be more precise when based on changes in gross phenotypes, compared to the prevailing practice of using displacements of the material points. We conclude that the presented experimental setup and computational pipeline is a viable method that deserves wider application.},
	issn = {1879-0534},
	doi = {10.1016/j.compbiomed.2014.07.013},
	author = {Nordb{\o}, Oyvind and Lamata, Pablo and Land, Sander and Steven A {Niederer} and Jan M. {Aronsen} and William E. {Louch} and Sjaastad, Ivar and Martens, Harald and Arne B. {Gjuvsland} and T{\o}ndel, Kristin and Torp, Hans and Lohezic, Maelene and Jurgen E. {Schneider} and Espen W. {Remme} and Nicolas P. {Smith} and Stig W. {Omholt}}
}
