Literature DB >> 12217442

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

Chung-Ming Chen1, Henry Horng-Shing Lu, Yueng-Shiang Huang.   

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.

Mesh:

Year:  2002        PMID: 12217442     DOI: 10.1016/s0301-5629(02)00531-8

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  3 in total

1.  Endocardial boundary extraction in left ventricular echocardiographic images using fast and adaptive B-spline snake algorithm.

Authors:  Mahdi Marsousi; Armin Eftekhari; Armen Kocharian; Javad Alirezaie
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-03-16       Impact factor: 2.924

2.  Segmentation in echocardiographic sequences using shape-based snake model combined with generalized Hough transformation.

Authors:  Chen Sheng; Yang Xin; Yao Liping; Sun Kun
Journal:  Int J Cardiovasc Imaging       Date:  2005-12-20       Impact factor: 2.357

3.  BGM-Net: Boundary-Guided Multiscale Network for Breast Lesion Segmentation in Ultrasound.

Authors:  Yunzhu Wu; Ruoxin Zhang; Lei Zhu; Weiming Wang; Shengwen Wang; Haoran Xie; Gary Cheng; Fu Lee Wang; Xingxiang He; Hai Zhang
Journal:  Front Mol Biosci       Date:  2021-07-19
  3 in total

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