A Statistical Local Binary Fitting Model for Blood Vessel Segmentation

被引：0

作者：

Zhao, Shifeng ^{[1
]}

Zhou, Mingquan ^{[1
]}

Wang, Kang ^{[1
]}

机构：

[1] Beijing Normal Univ, Coll Informat Sci & Technol, Beijing, Peoples R China

来源：

PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION APPLICATIONS (ICCIA 2012) | 2012年

关键词：

segmentation; blood vessel; intensity inhomogeneity; VASCULAR SEGMENTATION; LEVEL;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：1650 / 1653

页数：4

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