dc.contributor.author | Finsberg, Henrik Nicolay | |
dc.contributor.author | Balaban, Gabriel | |
dc.contributor.author | Ross, Stian Balnagown | |
dc.contributor.author | Håland, Trine Synnøve Fink | |
dc.contributor.author | Odland, Hans Henrik | |
dc.contributor.author | Sundnes, Joakim | |
dc.contributor.author | Wall, Samuel Thomas | |
dc.date.accessioned | 2018-07-18T11:35:56Z | |
dc.date.available | 2018-07-18T11:35:56Z | |
dc.date.created | 2018-01-29T15:23:28Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Journal of Computational Science. 2017, 24 85-90. | nb_NO |
dc.identifier.issn | 1877-7503 | |
dc.identifier.uri | http://hdl.handle.net/11250/2506005 | |
dc.description.abstract | Cardiac computational models, individually personalized, can provide clinicians with useful diagnostic information and aid in treatment planning. A major bottleneck in this process can be determining model parameters to fit created models to individual patient data. However, adjoint-based data assimilation techniques can now rapidly estimate high dimensional parameter sets. This method is used on a cohort of heart failure patients, capturing cardiac mechanical information and comparing it with a healthy control group. Excellent fit (R2 ≥ 0.95) to systolic strains is obtained, and analysis shows a significant difference in estimated contractility between the two groups. Keywords Cardiac mechanics; Adjoint method; Data assimilation; PDE-constrained optimization; Contractility | nb_NO |
dc.description.abstract | Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model | nb_NO |
dc.language.iso | eng | nb_NO |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model | nb_NO |
dc.title.alternative | Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.source.pagenumber | 85-90 | nb_NO |
dc.source.volume | 24 | nb_NO |
dc.source.journal | Journal of Computational Science | nb_NO |
dc.identifier.doi | 10.1016/j.jocs.2017.07.013 | |
dc.identifier.cristin | 1555043 | |
cristin.unitcode | 192,15,0,0 | |
cristin.unitname | Realfag og teknologi | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |