Acta Optica Sinica, Volume. 40, Issue 2, 0210002(2020)
Retinal Vessel Segmentation Based on Super-Pixel Affinity Propagation Clustering
Figures & Tables(10)
Fig. 2. Image pre-processing. (a) Color fundus image; (b) green channel fundus image; (c) CLAHE fundus enhanced image
Fig. 3. B-COSFIRE filter configuration. (a) B-COSFIRE schematic; (b) symmetric B-COSFIRE; (c) asymmetric B-COSFIRE
Fig. 4. Response mapfor each feature. (a) Hessian maximum eigenvalue; (b) Gabor wavelet transform; (c) B-COSFIRE filter
Fig. 5. Pixel point classification diagram. (a) Initial nearest neighbor classification; (b) KNN reclassification
Fig. 6. Segmentation diagrams of ASLICAP method in two databases. (a) DRIVE database; (b) STARE database
Fig. 7. Segmentation diagrams of three clustering methods under the same conditions. (a) Original picture; (b) gold standard; (c) ASLICAP; (d) K-means; (e) FCM
Table 1. ASLICAP segmentation performance indicators
View tableTable 1. ASLICAP segmentation performance indicators
Difference DRIVE database (K=2500) STARE database (K=4750) Acc Se Sp Acc Se Sp Average 0.9463 0.7879 0.9725 0.9430 0.7930 0.9581 Worst 0.9358 0.7352 0.9722 0.9203 0.6577 0.9413 Best 0.9593 0.8929 0.9711 0.9506 0.9174 0.9551
Table 2. Comparison of performance parameters of ALISCAP method, K-means, and FCM algorithm
View tableTable 2. Comparison of performance parameters of ALISCAP method, K-means, and FCM algorithm
Algorithm DRIVE database STARE database Acc Se Sp Acc Se Sp K-means 0.9467 0.7515 0.9785 0.9331 0.8184 0.9447 FCM 0.9457 0.6973 0.9852 0.9424 0.7619 0.9609 ASLICAP 0.9463 0.7879 0.9725 0.9430 0.7930 0.9581
Table 3. Comparison of segmentation results of different algorithms
View tableTable 3. Comparison of segmentation results of different algorithms
Num Method DRIVE database STARE database Acc Se Sp Acc Se Sp 1 Ref. [7] 0.938 0.781 0.966 0.887 0.767 0.939 2 Ref. [13] 0.944 0.740 0.978 0.950 0.772 0.970 3 Ref.[17] 0.934 0.725 0.966 0.941 0.751 0.957 4 Ref. [18] 0.937 0.703 0.971 0.932 0.758 0.950 5 Ref. [19] 0.933 0.739 0.955 0.920 0.825 0.944 6 Ref. [20] 0.938 0.569 0.993 0.946 0.638 0.982 7 Ref. [21] 0.947 0.780 0.972 0.945 0.769 0.938 8 Ref. [22] 0.940 0.725 0.979 0.933 0.854 0.984 9 Proposed method 0.946 0.788 0.973 0.943 0.793 0.958
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Yanbing Xu, Yang Zhou, Canbiao Li, Chujun Zheng, Rungu Zhang, Wenbin Wang. Retinal Vessel Segmentation Based on Super-Pixel Affinity Propagation Clustering[J]. Acta Optica Sinica, 2020, 40(2): 0210002
Paper Information
Category: Image Processing
Received: Aug. 1, 2019
Accepted: Sep. 19, 2019
Published Online: Jan. 2, 2020
The Author Email: Zheng Chujun (cjzheng@scnu.edu.cn)
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