Wenhan Yang, Miao Liao. Fusion of Attention Mechanism and Deformable Residual Convolution for Liver Tumor Segmentation[J]. Laser & Optoelectronics Progress, 2023, 60(12): 1210001
- Laser & Optoelectronics Progress
- Vol. 60, Issue 12, 1210001 (2023)
Fig. 1. Structure of improved U-Net model
Fig. 2. Structure of residual convolution module
Fig. 3. Structure of RBE module
Fig. 4. Schematic of deformable convolution. (a) Traditional convolution kernel; (b) deformable convolution kernel
Fig. 5. Dual attentional structure model
Fig. 6. Structure of channel attention
Fig. 7. Partial images of LITS dataset
Fig. 8. Data pre-processing. (a) Original CT image; (b) segmentation result of ribs and spine; (c) cropping diagram; (d) pre-processed image
Fig. 9. Visual comparison of probability graphs of different methods
Fig. 10. Segmentation results of different networks
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Table 1. Comparison results of ablation experiments
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Table 2. Performance comparison of different methods on LITS test set
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Table 3. Performance comparison with other methods on LITS dataset
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