Novosibirsk State University Journal of Information Technologies
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ISSN 2410-0420 (Online), ISSN 1818-7900 (Print)

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All Issues >> Contents: Volume 15, Issue No 4 (2017)

Automated Segmentation of the Lateral Ventricles from MRI Image
Evgeniy Aleksandrovich Zuenko, Angelika Arsentievna Shulunova

University of Innsbruck
Siberian State Aerospace University

DOI: DOI 10.25205/1818-7900-2017-15-4-22-31
UDC code: 004.932.1:616.831.38

Abstract
The aim of this work was to create a fully-automated segmentation algorithm for the lateral brain ventricles from 3-D MRI T1-weighted scans. The algorithm is based on atlas-based definition of a region of interest, followed by iterative filling, provided on a the distance map.

Key Words
automated segmentation, brain imaging, neuroimaging, atlas-based segmentation, MRI, lateral ventricles

How to cite:
Zuenko E. A., Shulunova A. A. Automated Segmentation of the Lateral Ventricles from MRI Image // Vestnik NSU Series: Information Technologies. - 2017. - Volume 15, Issue No 4. - P. 22-31. - DOI 10.25205/1818-7900-2017-15-4-22-31. - ISSN 1818-7900. (in Russian).

Full Text in Russian

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References
1. Samaille T. et al. Contrast-based fully automatic segmentation of white matter hyperintensities: method and validation // PloS one. 2012. Vol. 7, № 11. Р. e48953.
2. Babalola K. O. et al. Comparison and evaluation of segmentation techniques for subcortical structures in brain MRI // International Conference on Medical Image Computing and ComputerAssisted Intervention. Springer, Berlin, Heidelberg, 2008. Р. 409–416.
3. Schnack H. G. et al. Automatic segmentation of the ventricular system from MR images of the human brain // Neuroimage. 2001. Vol. 14, № 1. Р. 95–104.
4. Schönmeyer R. et al. Automated segmentation of lateral ventricles from human and primate magnetic resonance images using cognition network technology // Magnetic resonance imaging. 2006. Vol. 24, № 10. P. 1377–1387.
5. Xia Y. et al. A knowledge-driven algorithm for a rapid and automatic extraction of the human cerebral ventricular system from MR neuroimages // NeuroImage. 2004. Vol. 21, №. 1. P. 269–282.
6. The MNI brain and the Talairach atlas / Washington University School of Medicine. URL: http://www.nil.wustl.edu/labs/kevin/man/answers/mnispace.html
7. Distance transform on binary image // bwdist Matlab function documentation. URL: https://de.mathworks.com/help/images/ref/bwdist.html?requestedDomain=www.mathworks.com
8. Vellas B. et al. MAPT study: a multidomain approach for preventing Alzheimer’s disease: design and baseline data // The journal of prevention of Alzheimer's disease. 2014. Vol. 1, № 1. P. 13.

Publication information
Main title Vestnik NSU Series: Information Technologies, Volume 15, Issue No 4 (2017).
Parallel title: Novosibirsk State University Journal of Information Technologies Volume 15, Issue No 4 (2017).

Key title: Vestnik Novosibirskogo gosudarstvennogo universiteta. Seriâ: Informacionnye tehnologii
Abbreviated key title: Vestn. Novosib. Gos. Univ., Ser.: Inf. Tehnol.
Variant title: Vestnik NGU. Seriâ: Informacionnye tehnologii

Year of Publication: 2017
ISSN: 1818-7900 (Print), ISSN 2410-0420 (Online)
Publisher: Novosibirsk State University Press
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