中文摘要：

为了进行眼底疾病辅助诊断,提出一种基于多特征融合和随机森林的视网膜血管分割方法.首先为彩色眼底图中的每个像素点提取一个23维特征向量(包括图像不变矩、灰度共生矩阵、LoG结合高斯二阶导、梯度法、相位一致性和Hessian矩阵特征);然后选取一定数量的像素点,提取其特征共同构造一个特征矩阵作为输入数据,并采用随机森林算法训练分类器;再用训练好的分类器对待分割图像中的像素点进行分类,判断其是否为血管点;最后在初步分割基础上进行基于连通区域补足血管的后处理,得到优化后的血管分割结果.在DRIVE公共数据库上进行实验的结果表明,该方法平均精确度达0.9606,平均灵敏度达0.7447,平均特异性达0.9838,比已有方法性能更优.

英文摘要：

For the ophthalmic disease computer-aided diagnosis,this paper presents a multiple feature fusionfundus retinal blood vessels segmentation algorithm based on Random Forest.For each pixel in the field ofview,a23-D feature vector is constructed(encoding information on the moment invariant,gray levelco-occurrence matrix,LoG with Gaussian second derivative,gradient of the image,phase congruency andHessian matrix).Then a matrix is constructed for pixel of the training set as the input of the Random Forest;as a result,a Random Forest classifier used for classifying the test images is obtained.Finally,thepost-processing method based on the connected area is used to make up blood vessels.The experimental resulttesting on DRIVE database demonstrates that our method performance is better than other state-of-theartmethods based on machine learning.Meanwhile,the average accuracy,sensitivity,specificity are0.9606,0.7447,0.9838,respectively.