Table 3.
Comparison of segmentation methods using domain adaptation.
| Methods | Drishti-GS dataset | RIM-ONE-r3 dataset | ||||
|---|---|---|---|---|---|---|
| DSC cup | DSC disc | δ | DSC cup | DSC disc | δ | |
| BEAL (Wang et al., 2019a) | 0.862 | 0.961 | - | 0.810 | 0.898 | - |
| DoFE (Wang S. et al., 2020) | 0.835 | 0.955 | - | 0.800 | 0.893 | - |
| CADA (Liu et al., 2022) | 0.840 | 0.890 | 0.111 | 0.640 | 0.766 | 0.087 |
| CFEA (Liu et al., 2019) | 0.827 | 0.887 | 0.113 | 0.635 | 0.751 | 0.095 |
| AdaptSegNet (Tsai et al., 2018) | 0.826 | 0.881 | 0.118 | 0.627 | 0.737 | 0.102 |
| DAE (Karani et al., 2021) | 0.831 | 0.940 | - | 0.790 | 0.891 | - |
| SRDA (Bateson et al., 2020) | 0.807 | 0.962 | - | 0.776 | 0.894 | - |
| Ours | 0.857 | 0.962 | 0.083 | 0.791 | 0.898 | 0.082 |
The best result of the column is shown in bold.