【摘要】 精确估计眼底图像中的血管中心线和血管宽度是眼底血管疾病量化和可视化诊断的先决条件。在深入研究眼底图像和视网膜血管特征的基础上,提出一种基于中心线提取的视网膜血管分割算法,该算法以离散高斯核函数的偏微分为模板卷积图像,利用血管的微分几何特征定位血管中心线,并测量血管宽度。本方法的血管分割精度达到亚像素级,解决了传统方法无法直接计算血管宽度的问题,且在速度方面有较大提高。应用本算法对各类眼底图像进行了血管分割的实验,结果表明,该算法可以快速、准确地进行眼底血管分割和中心线提取。更多还原

【Abstract】 The precise estimation of blood vessel centerline and width is a prerequisite condition for the quantitative and visualized diagnosis of blood vessel disease in fundus images.In this paper,a retinal blood vessel segmentation algorithm based on centerline extraction is proposed.According to the characteristics of the fundus image and retinal blood vessels,the image is convoluted with the masks of discrete Gaussian partial derivative kernels.The centerline is determined by differential geometric properties of the blood vessels and the width is also calculated.The precision of our method can reach sub-pixel level with a fast computation speed.The experiments on several kinds of fundus images showed that the method worked quickly and accurately.更多还原