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Images as drivers of progress in cardiac computational modelling

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Images as drivers of progress in cardiac computational modelling. / Lamata de la Orden, Pablo; Casero, Ramón; Carapella, Valentina; Niederer, Steve A; Bishop, Martin J; Schneider, Jürgen E; Kohl, Peter; Grau, Vicente.

In: Progress in Biophysics and Molecular Biology, Vol. 115, No. 2-3, 08.2014, p. 198-212.

Research output: Contribution to journalArticle

Harvard

Lamata de la Orden, P, Casero, R, Carapella, V, Niederer, SA, Bishop, MJ, Schneider, JE, Kohl, P & Grau, V 2014, 'Images as drivers of progress in cardiac computational modelling' Progress in Biophysics and Molecular Biology, vol. 115, no. 2-3, pp. 198-212. DOI: 10.1016/j.pbiomolbio.2014.08.005

APA

Lamata de la Orden, P., Casero, R., Carapella, V., Niederer, S. A., Bishop, M. J., Schneider, J. E., ... Grau, V. (2014). Images as drivers of progress in cardiac computational modelling. DOI: 10.1016/j.pbiomolbio.2014.08.005

Vancouver

Lamata de la Orden P, Casero R, Carapella V, Niederer SA, Bishop MJ, Schneider JE et al. Images as drivers of progress in cardiac computational modelling. Progress in Biophysics and Molecular Biology. 2014 Aug;115(2-3):198-212. Available from, DOI: 10.1016/j.pbiomolbio.2014.08.005

Author

Lamata de la Orden, Pablo ; Casero, Ramón ; Carapella, Valentina ; Niederer, Steve A ; Bishop, Martin J ; Schneider, Jürgen E ; Kohl, Peter ; Grau, Vicente. / Images as drivers of progress in cardiac computational modelling. In: Progress in Biophysics and Molecular Biology. 2014 ; Vol. 115, No. 2-3. pp. 198-212

Bibtex Download

@article{94b2e015fde3469ca12bf6c16f814071,
title = "Images as drivers of progress in cardiac computational modelling",
abstract = "Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved.",
author = "{Lamata de la Orden}, Pablo and Ram{\'o}n Casero and Valentina Carapella and Niederer, {Steve A} and Bishop, {Martin J} and Schneider, {J{\"u}rgen E} and Peter Kohl and Vicente Grau",
year = "2014",
month = "8",
doi = "10.1016/j.pbiomolbio.2014.08.005",
language = "English",
volume = "115",
pages = "198--212",
journal = "Progress in Biophysics and Molecular Biology",
issn = "0079-6107",
publisher = "Elsevier Limited",
number = "2-3",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Images as drivers of progress in cardiac computational modelling

AU - Lamata de la Orden,Pablo

AU - Casero,Ramón

AU - Carapella,Valentina

AU - Niederer,Steve A

AU - Bishop,Martin J

AU - Schneider,Jürgen E

AU - Kohl,Peter

AU - Grau,Vicente

PY - 2014/8

Y1 - 2014/8

N2 - Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved.

AB - Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved.

U2 - 10.1016/j.pbiomolbio.2014.08.005

DO - 10.1016/j.pbiomolbio.2014.08.005

M3 - Article

VL - 115

SP - 198

EP - 212

JO - Progress in Biophysics and Molecular Biology

T2 - Progress in Biophysics and Molecular Biology

JF - Progress in Biophysics and Molecular Biology

SN - 0079-6107

IS - 2-3

ER -

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