Fig. 1. Dilated convolution

Fig. 2. Parallel multi-branch structure

Fig. 3. Attention residual block

Fig. 4. Spatial pyramid pooling module

Fig. 5. Detailed design of segmentation head in booster

Fig. 6. Multi-scale attention analytic network

Fig. 7. Training samples and labels. (a) Training samples; (b) labels

Fig. 8. Image preprocessing. (a) Original image; (b) preprocessed image

Fig. 9. Retinal vessel segmentation results of different algorithms. (a) Original images; (b) labels; (c) results of proposed algorithm; (d) results in Ref. [30]; (e) results in Ref. [17]; (f) results in Ref. [16]; (g) results in Ref. [31]

Fig. 10. Detail comparison of segmentation results. (a) Original images; (b) details of original images; (c) details of labels; (d) segmentation details of proposed algorithm; (e) segmentation details of algorithm in Ref. [30]; (f) segmentation details of proposed algorithm in Ref. [17]

Fig. 11. ROC curves of segmentation results of different algorithms. (a) ROC curves; (b) curves in box of Fig. 11(a)

Fig. 12. PR curves of segmentation results of different algorithms. (a) PR curves; (b) curves in rectangular of Fig. 12(a)

Fig. 13. Changes in various evaluation indicators. (a) F₁ value; (b) accuracy; (c) sensitivity; (d) specificity; (e) AUC (ROC); (f) AUC (PR)