Active Contour Based on Local Statistic Information and an Attractive Force for Ultrasound Image Segmentation
Jianjun Yuan, Jianjun Wang
Available Online March 2017.
- 10.2991/msam-17.2017.23How to use a DOI?
- image segmentation; local statistic; level set; regularization
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.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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 - Proceedings of the 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 - 10.2991/msam-17.2017.23 ID - Yuan2017/03 ER -