Abstract
In this work we use a Finite Element model of the left ventricular
(LV) mechanics to assess the sensitivity of strains to geometry.
Six principal shape modes extracted from an atlas of LV geometries
using principal component analysis, have been used to model the variability
of the geometry of a population of 1991 asymptomatic volunteers.
We observed that shear strains are more sensitive than normal strains to
geometry. For all the strains, shape mode 1, related with variation in size
within the population, plays an major role, but none of the six principal
modes can be considered non influential.
(LV) mechanics to assess the sensitivity of strains to geometry.
Six principal shape modes extracted from an atlas of LV geometries
using principal component analysis, have been used to model the variability
of the geometry of a population of 1991 asymptomatic volunteers.
We observed that shear strains are more sensitive than normal strains to
geometry. For all the strains, shape mode 1, related with variation in size
within the population, plays an major role, but none of the six principal
modes can be considered non influential.
Original language | English |
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Title of host publication | Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings |
Editors | Yves Coudière, Valéry Ozenne, Edward Vigmond, Nejib Zemzemi |
Place of Publication | Cham |
Publisher | Springer Nature |
Pages | 240-248 |
Number of pages | 9 |
ISBN (Electronic) | 978-3-030-21949-9 |
ISBN (Print) | 978-3-030-21948-2 |
DOIs | |
Publication status | Published - 2019 |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | SpringerLink |
Volume | 11504 |