Proceedings of the 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)

Active Contour Based on Local Statistic Information and an Attractive Force for Ultrasound Image Segmentation

Authors
Jianjun Yuan, Jianjun Wang
Corresponding Author
Jianjun Yuan
Available Online March 2017.
DOI
https://doi.org/10.2991/msam-17.2017.23How to use a DOI?
Keywords
image segmentation; local statistic; level set; regularization
Abstract
This paper presents a new active contour model with local intensities through level set method for ultrasound images segmentation. The method is not affected by the limitation of Gaussian distribution. The model is designed by local intensities, alignment term with a sharpening edge coefficient and regularization. Local intensities have the capability of denoising, and local means and variances are considered. The alignment term with a sharpening edge coefficient can sharpen edge and increase the convergence speed. The numerical schedule is implemented by level set method. Experimental results show that proposed method succeed to segment edges for ultrasound images.
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Proceedings
2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2017
ISBN
978-94-6252-324-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/msam-17.2017.23How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jianjun Yuan
AU  - Jianjun Wang
PY  - 2017/03
DA  - 2017/03
TI  - Active Contour Based on Local Statistic Information and an Attractive Force for Ultrasound Image Segmentation
BT  - 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
PB  - Atlantis Press
SP  - 99
EP  - 103
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-17.2017.23
DO  - https://doi.org/10.2991/msam-17.2017.23
ID  - Yuan2017/03
ER  -