Improved Snake Model Algorithm with Application in Liver Image Segmentation

Abstract:

Snake model is one of classical active contour models, and is widely used in the image segmentation. But it has defects of sensitive to the initial contour and lack of curvature constraints. This paper presents an improved Snake model algorithm, which initializes contour by maker control watershed algorithm and adds an external force related with the curve shape into the energy function of Snake model to solve the problem about curvature constraints. Testing on the Magnetic Resonance (MR) images of the abdomen for liver image segmentation proves that the new algorithm can achieve good results.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 2643-2648
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.2643
• Online since: December 2012
• Authors: Hong Lan, Le Quan Min
• Keywords: Liver Image Segmentation, Maker Control Watershed, Snake Model, Watershed Transform

References

[1] Guopu Zhu, Image Segmentation Based on Active Contour Model(in Chinese), Doctoral Dissertation of Harbin Institute of Technology (2007).

[2] Tianqing Li ,Yi Zhang, Zhi Liu, An Overview on Snakes Models(in Chinese), Computer Engineering, 31(2005) 1-3.

[3] Hui Huang, Lutai Guan,Yongyi Gong, Directional Snake Based on Dynamic Programming(in Chinese), Computer Engineering and Applications, 42(2006): 31-32.

[4] Marsousi M, Eftekhari A, Kocharian A, Alirezaie J, Endocardial boundary extraction in left ventricular echocardiographic images using fast and adaptive B-spline Snake algorithm, International Journal of Computer Assisted Radiology and Surgery,5(2010)501-513.

DOI: 10.1007/s11548-010-0404-0

[5] Kass M, Witkin A, Terzopoulos D, Snakes: active contour models. International Journal of Computer Vision, (1987) 321-331.

DOI: 10.1007/bf00133570

[6] Vincent L, Pierre S, Watersheds in digital spaces: an efficient algorithm based on immersion simulations, IEEE Trans Pattern Analy and Mach Intel,13(1991)583-598.

DOI: 10.1109/34.87344

[7] Sollie P, .Morphological Image Analysis: and Applications,2nd ed.Springer Verlag,New York(2003).

[8] Ostu N, A threshold selection method from gray-level histogram, IEEE Trans Systems, Man and Cybernetics, 8(1978) 62-66.