@article {25635,
	title = {Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model},
	journal = {Journal of Computational Science},
	volume = {24},
	year = {2017},
	pages = {85-90},
	publisher = {Elsevier},
	keywords = {Adjoint Method, Cardiac Mechanics, Contractility, Data assimilation, PDE-constrained optimization},
	issn = {1877-7503},
	doi = {10.1016/j.jocs.2017.07.013},
	url = {http://www.sciencedirect.com/science/article/pii/S1877750317308190},
	author = {Finsberg, Henrik and Balaban, Gabriel and Ross, Stian and Trine F {H{\r a}land} and Hans Henrik {Odland} and Sundnes, Joakim and Wall, Samuel}
}
@misc {25590,
	title = {Shape Optimization with Overlapping Meshes},
	howpublished = {ENUMATH 2017, Voss, Bergen},
	year = {2017},
	type = {Invited speaker to Minisymposia on PDE Software Frameworks},
	keywords = {Adjoint Method, CUTFEM, MultiMesh, Shape-optimization},
	author = {J{\o}rgen Schartum {Dokken}},
	editor = {Simon W {Funke} and Johansson, August and Schmidt, Stephan}
}
@inproceedings {24567,
	title = {Optimization of a Spatially Varying Cardiac Contraction parameter using the Adjoint Method},
	journal = {FEniCS{\textquoteright}16},
	year = {2016},
	abstract = {A cardiac computational model is constrained using clinical measurements such as pressure, volume and regional strain. The problem is formulated as a PDE-constrained optimisation problem where the objective functional represents the misfit between measured and simulated data. The control parameter for the active phase is a spatially varying contraction parameter defined at every vertex in the mesh. This makes gradient calculations using the adjoint approach computationally advantageous over standard finite difference approximations.},
	keywords = {Adjoint Method, Cardiac Mechanics, parameter estimation, PDE-constrained optimization},
	author = {Finsberg, Henrik and Balaban, Gabriel and Marie E. {Rognes} and Sundnes, Joakim and Wall, Samuel}
}
