Title: A Pipeline for the Generation of Realistic 3D Synthetic Echocardiographic Sequences: Methodology and Open-access Database
Authors: Alessandrini, Martino ×
De Craene, Mathieu
Bernard, Olivier
Giffard-Roisin, Sophie
Allain, Pascal
Waechter-Stehle, Irina
Weese, Juergen
Saloux, Eric
Delingette, Hervé
Sermesant, Maxime
D'hooge, Jan #
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers
Series Title: IEEE Transactions on Medical Imaging vol:34 issue:7 pages:1436-1451
Abstract: Quantification of cardiac deformation and strain
with 3D ultrasound takes considerable research efforts. Nevertheless,
a widespread use of these techniques in clinical practice
is still held back due to the lack of a solid verification process
to quantify and compare performance. In this context, the use
of fully synthetic sequences has become an established tool for
initial in silico evaluation. Nevertheless, the realism of existing
simulation techniques is still too limited to represent reliable
benchmarking data. Moreover, the fact that different centers
typically make use of in-house developed simulation pipelines
makes a fair comparison difficult.
In this context, this paper introduces a novel pipeline for the
generation of synthetic 3D cardiac ultrasound image sequences.
State-of-the art solutions in the fields of electromechanical modeling
and ultrasound simulation are combined within an original
framework that exploits a real ultrasound recording to learn
and simulate realistic speckle textures. The simulated images
show typical artifacts that make motion tracking in ultrasound
challenging. The ground-truth displacement field is available voxelwise
and is fully controlled by the electromechanical model. By
progressively modifying mechanical and ultrasound parameters,
the sensitivity of 3D strain algorithms to pathology and image
properties can be evaluated.
The proposed pipeline is used to generate an initial library of
8 sequences including healthy and pathological cases, which is
made freely accessible to the research community via our project
ISSN: 0278-0062
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Cardiovascular Imaging and Dynamics
× corresponding author
# (joint) last author

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