基于Level Set模型的彩色脑血管图像骨架提取算法

Color Cerebrovascular Image Skeleton Extraction Algorithm Based on Level Set Model

骨架提取是计算机视觉理论与应用中极具挑战性的课题,具有重要的应用价值。在分析医学彩色脑血管图像特性的基础上,引入一种基于颜色梯度信息和贝叶斯分类的水平集速度函数,提出了HSV空间高速模型,并基于该模型提出了用于彩色脑血管图像的骨架提取算法。该算法使用了两个新的中间函数,它的全部参数均由分析得到,避免了人工干涉。实验证明,该算法对颜色渐变和边界噪声不敏感,具有很好的有效性和鲁棒性。

Skeleton extraction is a challenging subject of computer vision theory and applications and has an important application value. Based on the characteristics analysis of medical color images of eerebrovascular, this paper introduced a Level Set speed function using color gradient information and bayesian classification, proposed HSV space high-speed model, and put forward the skeleton extraction algorithm for color cerebrovascular image on the basis of this model. This algorithm uses two new intermediate function, whose all parameters are obtained by analysis, so avoid the artificial interference. Experiments show that this algorithm is not sensitive to gradual changing of colors and the boundary noise and has good validity and robustness.