DocumentCode :
2589432
Title :
A shape-based segmentation approach: an improved technique using level sets
Author :
Abd El Munim, Hossam E. ; Farag, Aly A.
Author_Institution :
CVIP Lab, Louisville Univ., KY
Volume :
2
fYear :
2005
fDate :
17-21 Oct. 2005
Firstpage :
930
Abstract :
We propose a novel approach for shape-based segmentation based on a specially designed level set function format. This format permits us to better control the process of object registration which is an important part in the shape-based segmentation framework. The method depends on a set of training shapes used to build a parametric shape model. The color is taken into consideration besides the shape prior information. The shape model is fitted to the image volume by registration through an energy minimization problem. The approach overcomes the conventional methods problems like point correspondences and weighing coefficients tuning of the partial differential equations (PDE´s). Also it is suitable for multidimensional data and computationally efficient. Results of extracting the 2D star fish and the brain ventricles in 3D demonstrate the efficiency of the approach
Keywords :
computational geometry; image colour analysis; image registration; image segmentation; partial differential equations; 2D star fish; brain ventricles; level set function; object registration; parametric shape model; partial differential equations; shape-based segmentation; Anatomical structure; Biomedical imaging; Data mining; Deformable models; Image segmentation; Level set; Marine animals; Partial differential equations; Process control; Shape control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
Conference_Location :
Beijing
ISSN :
1550-5499
Print_ISBN :
0-7695-2334-X
Type :
conf
DOI :
10.1109/ICCV.2005.19
Filename :
1544821
Link To Document :
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