A Variation Level Set Formulation Local Based C-V Model for Medical Images Segmentation
- 10.2991/iccia.2012.130How to use a DOI?
- GACM, mediccal image segmentation, intensity imhomogeneity, C-V model.
Local image information is crucial for accurate segmentation of images with intensity inhomogeneity which usually occurs in medical images. However, image information in local region is not incorporated in popular region-based active contour models, such as piecewise constant models and piecewise smooth models. In this paper, a method which is able to use local information is proposed. The main point is the introduction of the local fitting information expressed by a kernel function which is crucial for segmentation. Our method is based on piecewise constant Chan-Vese model, and compare with different methods for several synthetic images and medical images.
- © 2013, 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 - Yan Yu AU - Chaobing Huang AU - Ling Li PY - 2014/05 DA - 2014/05 TI - A Variation Level Set Formulation Local Based C-V Model for Medical Images Segmentation BT - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) PB - Atlantis Press SP - 539 EP - 542 SN - 1951-6851 UR - https://doi.org/10.2991/iccia.2012.130 DO - 10.2991/iccia.2012.130 ID - Yu2014/05 ER -