2017

chapter in monograph

english

EN The paper aims to build a reduced order model (ROM) of the left and right ventricle of a human heart. The input heart model is build from 3D sets of registered, flexible surface meshes for the left and right ventricle, resulting from the MRI data. Spatial and temporal variables are separated using Proper Orthogonal Decomposition. It enables data reduction and works as a data-driven filter, separating similar and alternative properties of the left and right ventricle movement, which is diagnostically essential in cardiology studies. Each mode can be correlated with a corresponding heart movement. The temporal coefficients reflect the functioning of the heart, and comparing them may reveal and distinguish pathologies. We have proven that complex heart motion can be modeled with relatively small number of degrees of freedom. The model spanned on a few POD modes allows the analysis of the crucial movement data and better identification of possible failures.

57 - 69

10.1007/978-3-319-54481-6_5

https://link.springer.com/chapter/10.1007/978-3-319-54481-6_5

Computational Biomechanics for Medicine. From Algorithms to Models and Applications

20