Synthetic Echocardiographic Image Sequences for Cardiac Inverse Electro-Kinematic Learning

Adityo Prakosa; Maxime Sermesant; Hervé Delingette; Eric Saloux; Pascal Allain; Pascal Cathier; Patrick Etyngier; Nicolas Villain; Nicholas Ayache

inria-00616214, version 1

Synthetic Echocardiographic Image Sequences for Cardiac Inverse Electro-Kinematic Learning

Adityo Prakosa ¹, Maxime Sermesant ( Author to contact preferably ) ¹, Hervé Delingette () ¹, Eric Saloux ^2, 3, Pascal Allain () ⁴, Pascal Cathier ^4, 5, 6, Patrick Etyngier () ⁴, Nicolas Villain ^7, 8, Nicholas Ayache () ¹

Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI) (2011) 8p

Abstract: In this paper, we propose to create a rich database of syn- thetic time series of 3D echocardiography (US) images using simulations of a cardiac electromechanical model, in order to study the relationship between electrical disorders and kinematic patterns visible in medical images. From a real 4D sequence, a software pipeline is applied to create several synthetic sequences by combining various steps including motion tracking and segmentation. We use here this synthetic database to train a machine learning algorithm which estimates the depolarization times of each cardiac segment from invariant kinematic descriptors such as local displacements or strains. First experiments on the inverse electro- kinematic learning are demonstrated on the synthetic 3D US database and are evaluated on clinical 3D US sequences from two patients with Left Bundle Branch Block.

1: ASCLEPIOS (INRIA Sophia Antipolis)
INRIA
2: CHU Caen
CHU Caen – Université de Caen Basse-Normandie
3: Département de Radiologie - CHU de Caen
CHU Caen
4: MedisysResearch Lab (Medisys)
Philips Research
5: Service NEUROSPIN (NEUROSPIN)
CEA : DSV/I2BM
6: IFR de Neuroimagerie Fonctionnelle (IFR 49)
CEA
7: Neuropsychologie cognitive et neuroanatomie fonctionnelle de la mémoire humaine
INSERM : E0218 – Université de Caen Basse-Normandie – Ecole Pratique des Hautes Etudes
8: Neuropsychologie cognitive et neuroanatomie fonctionnelles de la mémoire
INSERM : U923 – CHU Caen – Université de Caen Basse-Normandie – Ecole Pratique des Hautes Etudes

inria-00616214, version 1
http://hal.inria.fr/inria-00616214
oai:hal.inria.fr:inria-00616214
From: Project-Team Asclepios <>
Submitted for: Gregoire MALANDAIN <>
Submitted on: Friday, 19 August 2011 19:57:18
Updated on: Friday, 13 April 2012 17:37:45

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%% inria-00616214, version 1
%% http://hal.inria.fr/inria-00616214
@inproceedings{prakosa:inria-00616214,
    hal_id = {inria-00616214},
    url = {http://hal.inria.fr/inria-00616214},
    title = {{Synthetic Echocardiographic Image Sequences for Cardiac Inverse Electro-Kinematic Learning}},
    author = {Prakosa, Adityo and Sermesant, Maxime and Delingette, Herv{\'e} and Saloux, Eric and Allain, Pascal and Cathier, Pascal and Etyngier, Patrick and Villain, Nicolas and Ayache, Nicholas},
    abstract = {{In this paper, we propose to create a rich database of syn- thetic time series of 3D echocardiography (US) images using simulations of a cardiac electromechanical model, in order to study the relationship between electrical disorders and kinematic patterns visible in medical images. From a real 4D sequence, a software pipeline is applied to create several synthetic sequences by combining various steps including motion tracking and segmentation. We use here this synthetic database to train a machine learning algorithm which estimates the depolarization times of each cardiac segment from invariant kinematic descriptors such as local displacements or strains. First experiments on the inverse electro- kinematic learning are demonstrated on the synthetic 3D US database and are evaluated on clinical 3D US sequences from two patients with Left Bundle Branch Block.}},
    language = {English},
    affiliation = {ASCLEPIOS - INRIA Sophia Antipolis , CHU Caen , D{\'e}partement de Radiologie - CHU de Caen , MedisysResearch Lab - Medisys , Service NEUROSPIN - NEUROSPIN , IFR de Neuroimagerie Fonctionnelle - IFR 49 , Neuropsychologie cognitive et neuroanatomie fonctionnelle de la m{\'e}moire humaine , Neuropsychologie cognitive et neuroanatomie fonctionnelles de la m{\'e}moire},
    booktitle = {{Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI)}},
    publisher = {Springer, Heidelberg},
    pages = {8p},
    address = {Toronto, Canada, Canada},
    series = {LNCS },
    audience = {international },
    year = {2011},
}

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