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Improved External Force Field for Snakes and Accurate Segmentation of Left Ventricle MRI


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Improved External Force Field for Snakes and Accurate Segmentation of Left Ventricle MRI
SHI Cheng-xian1 2 WANG Ping- an3 XIA De-shen1
1.School of Computer Science and Technology, NUST,Nanjing 210094, China; 2. Department of Information Science, Jiangsu Polytechnic University, Changzhou 213016, China; 3.Department of Computer Science and Engineering,The Chinese University of Hong Kong, H
parameter active contour gradient vector flow potential force field image segmentation
Parametric active contour model ( Snakes) manifests two limitations: an initial contour must be set near the feature of the image and such a model cannot deal properly with the concave regions in the image. By replacing the gradient f ield with the gradient vector flow ( GVF) , Snakes can segment concave region edges effectively and has a large capture range. GVF Snakes has poor performances at high curvature boundaries ( such as corners) due to the smoothness of the intrinsic force and the gradient vector flow. The image is smoothed by an anisotropic diffusion equation. The combination of the gradient vector force field with the potential force field is proposed for Snakes. Experiments demonstrate that the model curve is driven accurately to the object boundary by the new forces even if the init ial estimate curve is not close, the object is nonconvex or the edge has a high local curvature on the left ventricle MRI.


[ 1] Kass M,Witkin A, Terzopoulos D. Snakes: Active contour models[ J] . Int J Comput Vis, 1987, 1( 4) : 321- 331.
[ 2] Cohen L D, Cohen I. Finite- element methods for active contour models and balloons for 2-D and 3-D images[ J] . IEEE Trans Pattern Anal Mach Intell, 1993, 15 ( 11) : 1 131- 1 147.
[ 3] Xu Chenyang , Prince J L. Snakes, shapes, and gradient vector flow [ J] . IEEE Trans of Image Processing, 1998, 7( 3) : 359- 369.
[ 4] Wang Jiankang, Li Xiaobo. A conten-t guided searching a-l gorithm for balloons[ J] . Pattern Recognition, 2003, 36( 1) : 205- 215.
[ 5] Velascoa F A, L M J. Growing Snakes: Active contours for complex topologies[ J] . Pattern Recognition, 2003, 36( 2) : 475- 482.
[ 6] Aubert G, Vese L. A variational method in image recovery [ J] . SIAM J Numer Anal, 1997, 34( 5) : 1 948- 1 979.
[ 7] Weickert J, Ter Haar Romeny B, Viergever M. Efficient and reliable schemes for nonlinear diffusion filtering [ J] . IEEE Trans on Image Processing, 1998, 7( 3) : 398- 410.


Last Update: 2006-02-28