基于数学形态学的视网膜血管提取算法

Retinal blood vessel extraction algorithm based on mathematical morphology

目的影像中血管的分割与特征提取,对疾病的早期诊断具有重要意义。针对很多视网膜血管提取算法分割精度不高的问题,提出了运用数学形态学中的高帽变换的方法对其进行检测。方法首先,选取结构元素为"圆盘形"的形态学对图像进行高帽变换,经过高帽变换后的图像平滑了图像的背景,同时增强了血管在图像中的对比度。其次,对变换后的图像利用Otsu's自动分割法对图像进行阈值分割得到血管的二值图像。再次,根据血管在图像中的结构信息和几何信息,利用基于连通域度量的方法,设置连通域的"面积"和"长宽比"两个阈值,去除虚假目标。最后,为保持血管的连续性,对图像进行一次膨胀运算,可将断裂的血管连接起来,减小了实验的误差。结果通过上述步骤实现了对血管的提取。结论结果表明,本文算法能有效提取视网膜眼底图像的血管网络,有较强的分割精度。

Objective Retinal blood vessel extraction is of great importance for the early diagnosis.Aiming at the issues that the segmentation accuracy is not high in the majority of retinal blood vessel extraction algorithms,a new method is introduced.Methods Firstly,the vessel information is extracted by using top-hat transformation.The morphological ‘top-hat transformation’ operation is conducted by using the ‘disc’ structuring element to smooth the image background and highlight the blood vessels.Secondly,Otsu＇ s segmentation is used to get its binary image.Thirdly,according to the structural information and Geometric features of retinal blood vessel,the false blood vessels are removed by measuring the connected domain.Finally,in order to maintain the continuity of blood vessels,we use morphological dilation for blood vessels to connect broken blood vessels and reduce the experimental error.Results Through the above steps,the automatic identification of vessel is realized.Conclusions The experimental results indicate that the proposed algorithm can effectively detect the blood vessels of fundus image with high segmentation accuracy.