DocumentCode :
1826826
Title :
A new singular perturbation approach for image segmentation tracking
Author :
Schaerer, Joel ; Pousin, Jerome ; Clarysse, Patrick
Author_Institution :
CREATIS-LRMN, CNRS, Lyon
fYear :
2008
fDate :
14-17 May 2008
Firstpage :
1445
Lastpage :
1448
Abstract :
Deformable model based segmentation usually relies on a force field extracted from the image data through the computation of image gradient or gradient vector flow. At convergence, the work of the forces at the interface location should annihilate. This condition is not met in classical deformable formulations. In order to insure this condition, we previously introduced a constrained problem and a nonlinear approach in the framework of a deformable elastic template. From a computational point of view, theses two approaches can be very time consuming. Therefore, we propose in this paper a new simpler formulation using a singular perturbation technique. The nice behavior of the proposed model is demonstrated in the context of the segmentation and tracking of the heart contours in 2D cardiac MRI sequences.
Keywords :
biomedical MRI; cardiology; image segmentation; image sequences; medical image processing; perturbation techniques; 2D cardiac MRI sequences; deformable elastic template; deformable model based segmentation; force field extraction; gradient vector flow; heart contour tracking; image gradient; image segmentation tracking; singular perturbation approach; Capacitive sensors; Context modeling; Convergence; Data mining; Deformable models; Image segmentation; Image sequences; Perturbation methods; Solid modeling; Tensile stress; Deformable model; cardiac image sequences; segmentation tracking; singular perturbation method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-2002-5
Electronic_ISBN :
978-1-4244-2003-2
Type :
conf
DOI :
10.1109/ISBI.2008.4541279
Filename :
4541279
Link To Document :
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