A Statistical Local Binary Fitting Model for Blood Vessel Segmentation
- 10.2991/iccia.2012.411How to use a DOI?
- segmentation, blood vessel, intensity inhomogeneity
Network structure such as blood vessels in medical images are important features for computer-aided diagnosis and follow-up of many diseases. In this study, a new model-based segmentation method is proposed to detect blood vessels in medical images. The Local Binary Fitting(LBF) model with statistical distribution function is used for this purpose. The brain tissues and cerebral vessels in the image are modeled by Gaussian distribution and uniform distribution respectively. The region distribution combined with the LBF model is used in curve evolution. And the level set method is developed to implement the curve evolution to assure high efficiency of the cerebrovascular segmentation. Comparisons with the LBF method show that our model can achieve better results.
- © 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 - Shifeng Zhao AU - Mingquan Zhou AU - Kang Wang PY - 2014/05 DA - 2014/05 TI - A Statistical Local Binary Fitting Model for Blood Vessel Segmentation BT - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) PB - Atlantis Press SP - 1650 EP - 1653 SN - 1951-6851 UR - https://doi.org/10.2991/iccia.2012.411 DO - 10.2991/iccia.2012.411 ID - Zhao2014/05 ER -