Vessel Extraction Algorithm Based on State Balance of Image Pixels
基于图像像素状态平衡的血管提取算法

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.