Xinhui Jiang, Zhe Li. Skin Lesion Segmentation Based on U-Shaped Structure Context Encoding and Decoding Network[J]. Laser & Optoelectronics Progress, 2021, 58(12): 1210006
- Laser & Optoelectronics Progress
- Vol. 58, Issue 12, 1210006 (2021)
Fig. 1. Network structure of our algorithm
Fig. 2. ResNet50_32×4d residual structure
Fig. 3. Efficient dual-channel attention mechanism module
Fig. 4. Atrous spatial pyramid pooling module
Fig. 5. Feature decoding block
Fig. 6. ISIC 2017 dermoscopy image dataset
Fig. 7. Data preprocessing
Fig. 8. Test results of each algorithm segmentation index on the ISIC 2017 dataset. (a) Accuracy curve of verification set; (b) loss curve of verification set; (c) Dice_Coefficient curve of test set; (d) Jaccard_Index curve of test set
Fig. 9. Test results of the speed and stability of each algorithm on the ISIC 2017 dataset. (a) Speed test results; (b) stability test results
Fig. 10. Comparison of the segmentation results of each algorithm on the ISIC 2017 dataset and the real label, in which the smooth curves represent the real labels, and the zigzag curves represent the segmentation results
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Table 1. Test results of each algorithm segmentation index on the ISIC 2017 dataset
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Table 2. Comparison with other advanced methods on the ISIC 2017 dataset
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Table 3. Test results of our algorithm and its ablation module on ISIC 2017 dataset
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