DocumentCode :
2083865
Title :
Cellular Automata based Level Set Method for Image Segmentation
Author :
Chen, Yu ; Yan, Zhuangzhi ; Chu, Yungao
Author_Institution :
Shanghai Univ., Shanghai
fYear :
2007
fDate :
23-27 May 2007
Firstpage :
171
Lastpage :
174
Abstract :
Level set equation can be substituted by the convection-diffusion equation. But the two equations are very difficult to solve. When both of the equations become non-differentiable for certain initial data, appropriate weak solutions must be built. This may undermine the quality of the segmentation. In recent years the Cellular Automata (CA), for example the lattice Boltzmann method (LBM), has attracted much attention as an alternative approach for solving partial differential equations. CA is an inherent discrete system and do not require the differentiability of the initial condition. For this reason, CA is very appropriate for the numerical solution of the partial differential equation. In this paper, the LBM is used to solve the convection-diffusion equation. The experiments show that the LBM can solve the advection equation accurately and stably, and the segmentation is good.
Keywords :
cellular automata; image segmentation; lattice Boltzmann methods; medical image processing; partial differential equations; advection equation; cellular automata; convection-diffusion equation; inherent discrete system; lattice Boltzmann method; level set equation; medical image segmentation; partial differential equation; Biomedical engineering; Biomedical imaging; Entropy; Fluid flow; Image segmentation; Lattice Boltzmann methods; Level set; Microscopy; Partial differential equations; Viscosity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Complex Medical Engineering, 2007. CME 2007. IEEE/ICME International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1077-4
Electronic_ISBN :
978-1-4244-1078-1
Type :
conf
DOI :
10.1109/ICCME.2007.4381715
Filename :
4381715
Link To Document :
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