Multi-scale polyp segmentation network employing cascaded strategy to fuse boundary features

Method	mDice↑	mIoU↑	$F_{β}^{ω}$ ↑	$S_{α}$ ↑	$E_{ϕ}^{m a x}$ ↑	MAE↓
U-Net	0.824	0.767	0.811	0.889	0.917	0.019
U-Net++	0.797	0.741	0.785	0.872	0.898	0.022
SFA	0.698	0.615	0.647	0.793	0.816	0.042
PraNet	0.902	0.858	0.896	0.935	0.958	0.009
CaraNet	0.936	0.887	0.931	0.954	0.991	0.007
MSNet	0.921	0.879	0.914	0.941	0.972	0.008
FSFM	0.934	0.884	0.931	0.953	0.982	0.010
BLE-Net	0.905	0.878	0.922	0.950	0.981	0.008
SAM-CLNet	0.853	0.783	0.845	0.897	0.953	0.014
M²SNet	0.922	0.880	0.917	0.942	0.970	0.009
Ours	0.944	0.900	0.938	0.948	0.987	0.006

Table 2. Performance comparison of each model on the Kvasir dataset

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Table 2. Performance comparison of each model on the Kvasir dataset

Method	mDice↑	mIoU↑	$F_{β}^{ω}$ ↑	$S_{α}$ ↑	$E_{ϕ}^{m a x}$ ↑	MAE↓
U-Net	0.821	0.756	0.794	0.858	0.901	0.055
U-Net++	0.824	0.753	0.808	0.862	0.907	0.048
SFA	0.725	0.619	0.670	0.782	0.828	0.075
PraNet	0.901	0.848	0.885	0.915	0.943	0.030
CaraNet	0.918	0.865	0.909	0.929	0.968	0.023
FSFM	0.913	0.861	0.906	0.922	0.952	0.027
BLE-Net	0.905	0.854	0.897	0.919	0.955	0.025
SAM-CLNet	0.857	0.788	0.854	0.882	0.929	0.042
MSNet	0.907	0.862	0.893	0.922	0.944	0.028
M²SNet	0.912	0.861	0.901	0.922	0.953	0.025
Ours	0.920	0.869	0.910	0.924	0.961	0.022

Table 3. Comparison of segmentation results of different algorithms on the CVC-ColonDB dataset

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Table 3. Comparison of segmentation results of different algorithms on the CVC-ColonDB dataset

Method	mDice↑	mIoU↑	$F_{β}^{ω}$ ↑	$S_{α}$ ↑	$E_{ϕ}^{m a x}$ ↑	MAE↓
U-Net	0.519	0.449	0.498	0.711	0.763	0.061
U-Net++	0.490	0.413	0.467	0.691	0.762	0.064
SFA	0.467	0.351	0.379	0.634	0.648	0.094
PraNet	0.716	0.645	0.699	0.820	0.847	0.043
CaraNet	0.773	0.689	0.729	0.853	0.902	0.042
FSFM	0.781	0.709	0.775	0.852	0.898	0.032
BLE-Net	0.731	0.658	0.710	0.832	0.859	0.044
SAM-CLNet	0.711	0.627	0.694	0815	0.862	0.040
MSNet	0.755	0.678	0.737	0.836	0.883	0.041
M²SNet	0.758	0.685	0.737	0.842	0.869	0.038
Ours	0.782	0.714	0.765	0.855	0.893	0.034

Table 4. Comparison of segmentation results of different algorithms on the CVC-300 dataset

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Table 4. Comparison of segmentation results of different algorithms on the CVC-300 dataset

Method	mDice↑	mIoU↑	$F_{β}^{ω}$ ↑	$S_{α}$ ↑	$E_{ϕ}^{m a x}$ ↑	MAE↓
U-Net	0.717	0.639	0.684	0.842	0.867	0.022
U-Net++	0.714	0.636	0.687	0.838	0.884	0.018
SFA	0.465	0.332	0.341	0.640	0.604	0.065
PraNet	0.873	0.804	0.843	0.924	0.938	0.010
CaraNet	0.903	0.838	0.887	0.940	0.989	0.007
FSFM	0.910	0.846	0.893	0.942	0.978	0.006
BLE-Net	0.879	0.805	0.850	0.928	0.973	0.009
SAM-CLNet	0.876	0.800	0.851	0.922	0.975	0.008
MSNet	0.869	0.807	0.849	0.925	0.943	0.010
M²SNet	0.903	0.842	0.881	0.939	0.965	0.009
Ours	0.915	0.852	0.896	0.938	0.979	0.006

Table 5. Comparison of segmentation results of different algorithms on the ETIS-LaribPolypDB dataset

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Table 5. Comparison of segmentation results of different algorithms on the ETIS-LaribPolypDB dataset

Method	mDice↑	mIoU↑	$F_{β}^{ω}$ ↑	$S_{α}$ ↑	$E_{ϕ}^{m a x}$ ↑	MAE↓
U-Net	0.406	0.343	0.366	0.682	0.645	0.036
U-Net++	0.413	0.342	0.390	0.681	0.704	0.035
SFA	0.297	0.219	0.231	0.557	0.515	0.109
PraNet	0.630	0.576	0.600	0.791	0.792	0.031
CaraNet	0.747	0.672	0.709	0.868	0.894	0.017
FSFM	0.775	0.702	0.733	0.850	0.883	0.013
BLE-Net	0.673	0.594	0.622	0.810	0.837	0.032
SAM-CLNet	0.665	0.586	0.635	0.810	0.859	0.019
MSNet	0.719	0.664	0.678	0.840	0.830	0.020
M²SNet	0.749	0.678	0.712	0.846	0.872	0.017
Ours	0.776	0.694	0.737	0.850	0.887	0.019

Table 6. Ablation experimental results on the CVC-ClinicDB dataset
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Table 6. Ablation experimental results on the CVC-ClinicDB dataset
Method mDice↑ mIoU↑ $F_{β}^{ω}$ ↑ $S_{α}$ ↑ $E_{ϕ}^{m a x}$ ↑ MAE↓
Method1 0.922 0.880 0.917 0.942 0.970 0.009
Method2 0.934 0.887 0.926 0.944 0.979 0.006
Method3 0.935 0.892 0.929 0.946 0.979 0.006
Method4 0.944 0.900 0.938 0.948 0.987 0.006

Table 7. Ablation experimental results on the Kvasir dataset
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Table 7. Ablation experimental results on the Kvasir dataset
Method mDice↑ mIoU↑ $F_{β}^{ω}$ ↑ $S_{α}$ ↑ $E_{ϕ}^{m a x}$ ↑ MAE↓
Method1 0.912 0.861 0.901 0.922 0.953 0.025
Method2 0.914 0.867 0.906 0.920 0.952 0.024
Method3 0.917 0.867 0.908 0.921 0.956 0.022
Method4 0.920 0.869 0.910 0.924 0.961 0.022

Table 8. Ablation experimental results on the CVC-300 dataset
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Table 8. Ablation experimental results on the CVC-300 dataset
Method mDice↑ mIoU↑ $F_{β}^{ω}$ ↑ $S_{α}$ ↑ $E_{ϕ}^{m a x}$ ↑ MAE↓
Method1 0.903 0.842 0.881 0.939 0.965 0.009
Method2 0.903 0.844 0.882 0.943 0.960 0.006
Method3 0.908 0.848 0.890 0.937 0.968 0.007
Method4 0.915 0.852 0.896 0.938 0.979 0.006

Table 9. Ablation experimental results on the ETIS-LaribPolypDB dataset
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Table 9. Ablation experimental results on the ETIS-LaribPolypDB dataset
Method mDice↑ mIoU↑ $F_{β}^{ω}$ ↑ $S_{α}$ ↑ $E_{ϕ}^{m a x}$ ↑ MAE↓
Method1 0.749 0.678 0.712 0.846 0.872 0.017
Method2 0.752 0.678 0.714 0.844 0.873 0.018
Method3 0.761 0.692 0.726 0.851 0.865 0.015
Method4 0.776 0.694 0.737 0.850 0.887 0.019

Table 10. Ablation experimental results on the CVC-ColonDB dataset
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Table 10. Ablation experimental results on the CVC-ColonDB dataset
Method mDice↑ mIoU↑ $F_{β}^{ω}$ ↑ $S_{α}$ ↑ $E_{ϕ}^{m a x}$ ↑ MAE↓
Method1 0.758 0.685 0.737 0.842 0.869 0.038
Method2 0.765 0.690 0.748 0.842 0.891 0.035
Method3 0.776 0.697 0.762 0.843 0.886 0.033
Method4 0.782 0.714 0.765 0.855 0.893 0.034

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Jianbing YI, Jianhui WAN, Feng CAO, Jun LI, Xin CHEN. Multi-scale polyp segmentation network employing cascaded strategy to fuse boundary features[J]. Optics and Precision Engineering, 2024, 32(18): 2846

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Paper Information

Category:

Received: Apr. 21, 2024

Accepted: --

Published Online: Nov. 18, 2024

The Author Email: Jianbing YI (yijianbing8@jxust.edu.cn)

DOI:10.37188/OPE.20243218.2846

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Performance comparison of each model on the CVC-ClinicDB dataset

Table 1. Performance comparison of each model on the CVC-ClinicDB dataset

Table 2. Performance comparison of each model on the Kvasir dataset

Table 2. Performance comparison of each model on the Kvasir dataset

Table 3. Comparison of segmentation results of different algorithms on the CVC-ColonDB dataset

Table 3. Comparison of segmentation results of different algorithms on the CVC-ColonDB dataset

Table 4. Comparison of segmentation results of different algorithms on the CVC-300 dataset

Table 4. Comparison of segmentation results of different algorithms on the CVC-300 dataset

Table 5. Comparison of segmentation results of different algorithms on the ETIS-LaribPolypDB dataset

Table 5. Comparison of segmentation results of different algorithms on the ETIS-LaribPolypDB dataset

Table 6. Ablation experimental results on the CVC-ClinicDB dataset

Table 6. Ablation experimental results on the CVC-ClinicDB dataset

Table 7. Ablation experimental results on the Kvasir dataset

Table 7. Ablation experimental results on the Kvasir dataset

Table 8. Ablation experimental results on the CVC-300 dataset

Table 8. Ablation experimental results on the CVC-300 dataset

Table 9. Ablation experimental results on the ETIS-LaribPolypDB dataset

Table 9. Ablation experimental results on the ETIS-LaribPolypDB dataset

Table 10. Ablation experimental results on the CVC-ColonDB dataset

Table 10. Ablation experimental results on the CVC-ColonDB dataset