To improve the accuracy of retinal blood vessel segmentation,an improved RAIterNet cascaded retinal blood vessel segmentation and tracking algorithm was proposed,and the image enhancement and accuracy improvement were performed re-spectively in the preprocessing and segmentation network model stages.The adaptive fractional differential was used to enhance the data set to be segmented to improve the quality of the blood vessel image and the contrast between the blood vessel and the background of the image to be segmented.The improved RAIterNet model was used to segment the retina.The end capillaries of the weak structure were tracked based on the continuous tracking method,which effectively segmented the tiny blood vessels in the retina that were difficult to segment.The algorithm was tested on the data set DRIVE.Experimental results show that the Acc can reach 0.9650,the F1 score is 0.9006,and the area under the AU-ROC curve of 0.9807 is obtained.The subjective and objective results verify the effectiveness of the algorithm.
关键词
视网膜血管提取/卷积神经网络/递归残差卷积/注意力机制/分数阶微分/自适应分数阶增强/血管追踪
Key words
retinal vessels extraction/convolution neural network/recursive residual convolution/attention mechanism/frac-tional order derivative/adaptive fractional order enhancement/vascular tracking
维普
万方数据