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  4. Cell-based dual snake model: a new approach to extracting highly winding boundaries in the ultrasound images
 
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Cell-based dual snake model: a new approach to extracting highly winding boundaries in the ultrasound images

Resource
Ultrasound in Medicine & Biology 28 (8): 1061-1073
Journal
Ultrasound in Medicine & Biology
Journal Volume
28
Journal Issue
8
Pages
1061-1073
Date Issued
2002
Date
2002
Author(s)
Chen, Chung-Ming  
Lu, Henry Horng-Shing
Huang, Yueng-Shiang
DOI
10.1016/S0301-5629(02)00531-8
URI
http://ntur.lib.ntu.edu.tw//handle/246246/132701
Abstract
Two common deficiencies of most conventional deformable models are the need to place the initial contour very close to the desired boundary and the incapability of capturing a highly winding boundary for sonographic boundary extraction. To remedy these two deficiencies, a new deformable model (namely, the cell-based dual snake model) is proposed in this paper. The basic idea is to apply the dual snake model in the cell-based deformation manner. While the dual snake model provides an effective mechanism allowing a distant initial contour, the cell-based deformation makes it possible to catch the winding characteristics of the desired boundary. The performance of the proposed cell-based dual snake model has been evaluated on synthetic images with simulated speckles and on the clinical ultrasound (US) images. The experimental results show that the mean distances from the derived to the desired boundary points are 0.9 ± 0.42 pixels and 1.29 ± 0.39 pixels for the synthetic and the clinical US images, respectively. ? 2002 World Federation for Ultrasound in Medicine & Biology.
Subjects
Boundary extraction; Cell-based deformation; Deformable model; Dual snake model; Multiscale Gaussian filters; Ultrasound images; Watershed transform
SDGs

[SDGs]SDG3

Other Subjects
Boundary conditions; Deformation; Imaging techniques; Speckle; Dual snake models; Ultrasonics; algorithm; article; imaging; model; priority journal; simulation; ultrasound; Algorithms; Breast Neoplasms; Computer Simulation; Female; Humans; Image Processing, Computer-Assisted; Liver Diseases; Models, Theoretical; Ultrasonography
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