Paper Info
Title
Propagation of Myocardial Fibre Architecture Uncertainty on Electromechanical Model Parameter Estimation: A Case Study.
Abstract
Computer models of the heart are of increasing interest for clinical applications due to their discriminative and predictive power. However the personalisation step to go from a generic model to a patient-specific one is still a scientific challenge. In particular it is still difficult to quantify the uncertainty on the estimated parameters and predicted values. In this manuscript we present a new pipeline to evaluate the impact of fibre uncertainty on the personalisation of an electromechanical model of the heart from ECG and medical images. We detail how we estimated the variability of the fibre architecture among a given population and how the uncertainty generated by this variability impacts the following personalisation. We first show the variability of the personalised simulations, with respect to the principal variations of the fibres. Then discussed how the variations in this (small) healthy population of fibres impact the parameters of the personalised simulations.
Year
DOI
Venue
2015
10.1007/978-3-319-20309-6_51
Lecture Notes in Computer Science
Field
DocType
Volume
Data mining,Population,Architecture,Predictive power,Simulation,Computer science,Unscented transform,Discriminative model,Model parameter
Conference
9126
ISSN
Citations 
PageRank 
0302-9743
4
0.62
References 
Authors
9
13
Name
Order
Citations
PageRank
Roch Molléro172.70
Dominik Neumann2839.40
Marc-Michel Rohé3724.59
Manasi Datar4635.71
Herve Lombaert539229.98
Nicholas Ayache6108041654.36
Dorin Comaniciu78389601.83
Olivier Ecabert834626.28
Marcello Chinali940.96
Gabriele Rinelli1040.96
Xavier Pennec115021357.08
Maxime Sermesant121111122.97
Tommaso Mansi1345445.94