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Bersvendsen J, Orderud F, Lie Ø, et al. Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces. J Med Imaging (Bellingham). 2017;4(2):024005doi: 10.1117/1.JMI.4.2.024005.
Bersvendsen, J., Orderud, F., Lie, �. �., Massey, R. J., Fosså, K., Estépar, R. S. J., Urheim, S., & Samset, E. (2017). Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces. Journal of medical imaging (Bellingham, Wash.), 4(2), 024005. https://doi.org/10.1117/1.JMI.4.2.024005
Bersvendsen, Jørn, et al. "Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces." Journal of medical imaging (Bellingham, Wash.) vol. 4,2 (2017): 024005. doi: https://doi.org/10.1117/1.JMI.4.2.024005
Bersvendsen J, Orderud F, Lie Ø, Massey RJ, Fosså K, Estépar RSJ, Urheim S, Samset E. Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces. J Med Imaging (Bellingham). 2017 Apr;4(2):024005. doi: 10.1117/1.JMI.4.2.024005. Epub 2017 May 24. PMID: 28560243; PMCID: PMC5443355.
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J Med Imaging (Bellingham). 2017 Apr;4(2):024005. doi: 10.1117/1.JMI.4.2.024005. Epub 2017 May 24.

Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces.

Journal of medical imaging (Bellingham, Wash.)

Jørn Bersvendsen, Fredrik Orderud, Øyvind Lie, Richard John Massey, Kristian Fosså, Raúl San José Estépar, Stig Urheim, Eigil Samset

Affiliations

  1. GE Vingmed Ultrasound AS, Horten, Norway.
  2. University of Oslo, Department of Informatics, Oslo, Norway.
  3. Center for Cardiological Innovation, Oslo, Norway.
  4. Oslo University Hospital, Department of Cardiology, Oslo, Norway.
  5. Oslo University Hospital, Department of Radiology and Nuclear Medicine, Oslo, Norway.
  6. Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States.
  7. Oslo University Hospital, Institute for Surgical Research, Oslo, Norway.

PMID: 28560243 PMCID: PMC5443355 DOI: 10.1117/1.JMI.4.2.024005

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 [Formula: see text], [Formula: see text], and [Formula: see text] 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 [Formula: see text].

Keywords: image segmentation; medical imaging; surface representation; three-dimensional echocardiography

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