Segmentation of MRI data by means of nonlinear diffusion

Radomír Chabiniok; Radek Máca; Michal Beneš; Jaroslav Tintěra

Kybernetika (2013)

  • Volume: 49, Issue: 2, page 301-318
  • ISSN: 0023-5954

Abstract

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The article focuses on the application of the segmentation algorithm based on the numerical solution of the Allen-Cahn non-linear diffusion partial differential equation. This equation is related to the motion of curves by mean curvature. It exhibits several suitable mathematical properties including stable solution profile. This allows the user to follow accurately the position of the segmentation curve by bringing it quickly to the vicinity of the segmented object and by approaching the details of the segmentation curve. The purpose of the article is to indicate how the algorithm parameters are set up and to show how the algorithm behaves when applied to the particular class of medical data. In detail we describe the algorithm parameters influencing the segmentation procedure. The left ventricle volume estimated by the segmentation of scanned slices is evaluated through the cardiac cycle. Consequently, the ejection fraction is evaluated. The described approach allows the user to process cardiac cine MR images in an automated way and represents, therefore, an alternative to other commonly used methods. Based on the physical and mathematical background, the presented algorithm exhibits the stable behavior in the segmentation of MRI test data, it is computationally efficient and allows the user to perform various implementation improvements.

How to cite

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Chabiniok, Radomír, et al. "Segmentation of MRI data by means of nonlinear diffusion." Kybernetika 49.2 (2013): 301-318. <http://eudml.org/doc/260731>.

@article{Chabiniok2013,
abstract = {The article focuses on the application of the segmentation algorithm based on the numerical solution of the Allen-Cahn non-linear diffusion partial differential equation. This equation is related to the motion of curves by mean curvature. It exhibits several suitable mathematical properties including stable solution profile. This allows the user to follow accurately the position of the segmentation curve by bringing it quickly to the vicinity of the segmented object and by approaching the details of the segmentation curve. The purpose of the article is to indicate how the algorithm parameters are set up and to show how the algorithm behaves when applied to the particular class of medical data. In detail we describe the algorithm parameters influencing the segmentation procedure. The left ventricle volume estimated by the segmentation of scanned slices is evaluated through the cardiac cycle. Consequently, the ejection fraction is evaluated. The described approach allows the user to process cardiac cine MR images in an automated way and represents, therefore, an alternative to other commonly used methods. Based on the physical and mathematical background, the presented algorithm exhibits the stable behavior in the segmentation of MRI test data, it is computationally efficient and allows the user to perform various implementation improvements.},
author = {Chabiniok, Radomír, Máca, Radek, Beneš, Michal, Tintěra, Jaroslav},
journal = {Kybernetika},
keywords = {degenerate diffusion; Allen–Cahn equation; image segmentation; magnetic resonance imaging; degenerate diffusion; Allen-Cahn equation; image segmentation; magnetic resonance imaging},
language = {eng},
number = {2},
pages = {301-318},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Segmentation of MRI data by means of nonlinear diffusion},
url = {http://eudml.org/doc/260731},
volume = {49},
year = {2013},
}

TY - JOUR
AU - Chabiniok, Radomír
AU - Máca, Radek
AU - Beneš, Michal
AU - Tintěra, Jaroslav
TI - Segmentation of MRI data by means of nonlinear diffusion
JO - Kybernetika
PY - 2013
PB - Institute of Information Theory and Automation AS CR
VL - 49
IS - 2
SP - 301
EP - 318
AB - The article focuses on the application of the segmentation algorithm based on the numerical solution of the Allen-Cahn non-linear diffusion partial differential equation. This equation is related to the motion of curves by mean curvature. It exhibits several suitable mathematical properties including stable solution profile. This allows the user to follow accurately the position of the segmentation curve by bringing it quickly to the vicinity of the segmented object and by approaching the details of the segmentation curve. The purpose of the article is to indicate how the algorithm parameters are set up and to show how the algorithm behaves when applied to the particular class of medical data. In detail we describe the algorithm parameters influencing the segmentation procedure. The left ventricle volume estimated by the segmentation of scanned slices is evaluated through the cardiac cycle. Consequently, the ejection fraction is evaluated. The described approach allows the user to process cardiac cine MR images in an automated way and represents, therefore, an alternative to other commonly used methods. Based on the physical and mathematical background, the presented algorithm exhibits the stable behavior in the segmentation of MRI test data, it is computationally efficient and allows the user to perform various implementation improvements.
LA - eng
KW - degenerate diffusion; Allen–Cahn equation; image segmentation; magnetic resonance imaging; degenerate diffusion; Allen-Cahn equation; image segmentation; magnetic resonance imaging
UR - http://eudml.org/doc/260731
ER -

References

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