基于多尺度小波变换融合的视网膜血管分割

Retinal Blood Vessel Segmentation Based on Multi-Scale Wavelet Transform Fusion

针对眼底视网膜血管细小、轮廓模糊导致血管分割精度低的问题,提出一种多尺度框架下采用小波变换融合血管轮廓特征和细节特征的视网膜血管分割方法。通过预处理增强血管与背景的对比度,在多尺度框架下提取血管轮廓特征和细节特征,并进行图像后处理;采用小波变换融合两幅特征图像,通过计算各尺度对应像素的最大值,得到血管检测图像,最后采用Otsu法进行分割。通过在DRIVE数据集上进行测试实验,得到平均准确率、灵敏度和特异度分别为0.9582,0.7086,0.9806。所提方法能够在准确分割血管轮廓的同时保留较多细小血管分支,准确率较高。

Aiming at the problem of low accuracy of blood vessel segmentation caused by the small and blurred outline of fundus retinal blood vessels,a retinal blood vessel segmentation method using wavelet transform to fuse the contour feature and detailed feature of the blood vessel under a multi-scale framework is proposed.The contrast between the blood vessel and the background is enhanced by preprocessing,the contour feature and detail feature of the blood vessel are extracted in a multi-scale framework,and image post-processing is performed.The wavelet transform is used to fuse the two feature images,the maximum value of the corresponding pixel of each scale is calculated to obtain the blood vessel detection image,and finally the Otsu method is used for segmentation.Through the test experiment of the DRIVE data set,the average accuracy,sensitivity,and specificity are 0.9582,0.7086,and 0.9806,respectively.The method in this paper can accurately segment the contour of the blood vessel while retaining more branches of small blood vessels,and the accuracy is high.