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Myocardial stiffness estimation: A novel cost function for unique parameter identification

Research output: Chapter in Book/Report/Conference proceedingChapter

Anastasia Nasopoulou, Bojan Blazevic, Andrew Crozier, Wenzhe Shi, Anoop Shetty, C. Aldo Rinaldi, Pablo Lamata, Steven Niederer

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer-Verlag Berlin Heidelberg
Pages355-363
Number of pages9
Volume9126
ISBN (Print)9783319203089, 9783319203089
DOIs
StatePublished - 21 Jun 2015
Event8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015 - Maastricht, Netherlands
Duration: 25 Jun 201527 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9126
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015
CountryNetherlands
CityMaastricht
Period25/06/201527/06/2015

King's Authors

Abstract

Myocardial stiffness is a clinical biomarker used to diagnose and stratify diseases such as heart failure. This biomechanical property can be inferred from the personalisation of computational cardiac models to clinical measures. Nevertheless, previous attempts have been unable to determine a unique set of material constitutive parameters. In this study we address this shortcoming by proposing a new cost function that allows us to uncouple key parameters and uniquely describe passive material properties in patients from available clinical data.

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