Acta Optica Sinica, Volume. 40, Issue 9, 0910001(2020)
Retinal Blood Vessel Segmentation Based on Fuzzy C-Means Clustering According to the Local Line Structural Constraints
Fig. 2. Images of the pre-processing results. (a) Color fundus image; (b) green channel; (c) morphological open operation of
Fig. 3. Multi-scale match filter response images. (a) Response image with σ=1; (b) response image with σ=2; (c) response image with all scales
Fig. 4. Schematic diagram of B-COSFIRE. (a) Principle of B-COSFIRE; (b) symmetrical B-COSFIRE structure; (c) asymmetric B-COSFIRE structure
Fig. 5. Response image of B-COSFIRE filtering. (a) Color fundus image; (b) result of B-COSFIRE filtering
Fig. 6. Schematic diagram of line detector structure. (a) Line detector schematic diagram; (b) schematic diagram of line detector matched with vessel; (c) local neighborhood information
Fig. 7. Segmentation result images of the DRIVE database. (a) The best result of images; (b) the worst result of images; (c) segmentation result of 15th images; (d) segmentation result of 18th images
Fig. 8. Segmentation results of lesion image. (a) Segmentation result of K-means; (b) segmentation result of FCM; (c) segmentation result of proposed method
Fig. 9. Results of proposed method and FCM. (a) Results of FCM; (b) results of the proposed method; (c) segmentation images manually marked by expert
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Hong Jia, Chujun Zheng, Canbiao Li, Wenbin Wang, Yanbing Xu. Retinal Blood Vessel Segmentation Based on Fuzzy C-Means Clustering According to the Local Line Structural Constraints[J]. Acta Optica Sinica, 2020, 40(9): 0910001
Category: Image Processing
Received: Nov. 29, 2019
Accepted: Jan. 19, 2020
Published Online: May. 6, 2020
The Author Email: Chujun Zheng (cjzheng@scnu.edu.cn)