24 May 2017 Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces
Jørn Bersvendsen, Fredrik Orderud, Øyvind Lie, Richard John Massey, Kristian Fosså, Raúl San José Estépar, Stig Urheim, Eigil Samset
Author Affiliations +
Abstract
With the advancement of three-dimensional (3-D) real-time echocardiography in recent years, automatic creation of patient specific geometric models is becoming feasible and important in clinical decision making. However, the vast majority of echocardiographic segmentation methods presented in the literature focus on the left ventricle (LV) endocardial border, leaving segmentation of the right ventricle (RV) a largely unexplored problem, despite the increasing recognition of the RV’s role in cardiovascular disease. We present a method for coupled segmentation of the endo- and epicardial borders of both the LV and RV in 3-D ultrasound images. To solve the segmentation problem, we propose an extension of a successful state-estimation segmentation framework with a geometrical representation of coupled surfaces, as well as the introduction of myocardial incompressibility to regularize the segmentation. The method was validated against manual measurements and segmentations in images of 16 patients. Mean absolute distances of 2.8±0.4  mm, 3.2±0.7  mm, and 3.1±0.5  mm between the proposed and reference segmentations were observed for the LV endocardium, RV endocardium, and LV epicardium surfaces, respectively. The method was computationally efficient, with a computation time of 2.1±0.4  s.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2017/$25.00 © 2017 SPIE
Jørn Bersvendsen, Fredrik Orderud, Øyvind Lie, Richard John Massey, Kristian Fosså, Raúl San José Estépar, Stig Urheim, and Eigil Samset "Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces," Journal of Medical Imaging 4(2), 024005 (24 May 2017). https://doi.org/10.1117/1.JMI.4.2.024005
Received: 27 January 2016; Accepted: 1 May 2017; Published: 24 May 2017
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Image segmentation

Echocardiography

3D modeling

3D image processing

Ultrasonography

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