基于图像像素状态平衡的血管提取算法  

Vessel Extraction Algorithm Based on State Balance of Image Pixels

作　　者：洪伟[1] 牟轩沁[1] 蔡元龙[1] 

机构地区：[1]西安交通大学电子与信息工程学院,西安710049

出　　处：《中国图象图形学报（A辑）》2004年第2期225-229,共5页Journal of Image and Graphics

基　　金：国家自然科学基金项目 ( 3 0 0 70 2 2 5 )

摘　　要：为了消除血管减影图像中的噪声 ,从复杂背景中提取血管 ,提出了一种基于图像像素状态平衡的血管提取方法。将图像看成一个由目标区域与背景区域构成的平衡系统 ,目标区域与背景区域由于某种作用力处于一个内在平衡状态 ,但噪声的引入破坏了这种平衡 ,该方法通过恢复平衡状态来消除噪声 ,分离目标与背景区域。在此基础上发展出一种新的灰度图像二值化算法 ,并将其应用在脑部血管 DSA图像的血管提取上 ,该算法能从背景噪声很强的 DSA剪影图像中分离出完整的血管网络 。The model of state balance of image pixels from the view of pixels' correlative degree is proposed to extract vascular network from DSA images. The image is regarded as a balanced system that consists of object and background areas. Under some certain force, there is an inner balanced state between these two kinds of areas. But the introduction of noise breaks the balance, this disturbance will make the boundary of vascular and background indistinct. In the circumstances, extracting vascular network directly is very difficulty. If the balanced state can be gained, the segmentation becomes easy and accurate relatively. Therefore it's possible to remove the noise and separate the object and background areas by resuming such balanced state. Based on this theory, a new binarization algorithm for gray images can be developed and used in the vessel extraction from the DSA images of cerebral vessels. An overlap algorithm is presented to resumes the balance state in this paper. Then using this algorithm, the vascular network can be segmented from background perfectly. It can extract the whole vascular network from the DSA subtraction images with high level noises and the experimental results are very satisfying.

关 键 词：状态平衡 血管提取 二值化 分割 图像噪声 灰度图像 图像处理 

分 类 号：TN911.73[电子电信—通信与信息系统]