Medical Image Segmentation on GlaS (test)
93.94Dice ScoreU-KABS
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| U-KABSParams(M)=9.54, FLOPS(G)=6.922026.02 | 93.94 | 88.59 | 0.82 | — | — | |
| ResU-KANParams(M)=20.06, FLOPS(G)=8.572026.02 | 93.61 | 87.99 | 1.01 | — | — | |
| S2M-NetLoss=MASL2026.01 | 93.54 | — | — | — | — | |
| U-KANParams(M)=9.38, FLOPS(G)=6.892026.02 | 93.37 | 87.64 | 0.98 | — | — | |
| U-Net++Params(M)=9.16, FLOPS(G)=34.902026.02 | 92.96 | 87.07 | 0.81 | — | — | |
| Att-UNetParams(M)=50.27, FLOPS(G)=60.062026.02 | 92.89 | 86.84 | 0.82 | — | — | |
| U-NetParams(M)=7.76, FLOPS(G)=13.782026.02 | 92.79 | 86.66 | 0.83 | — | — | |
| Rolling-UnetParams(M)=25.32, FLOPS(G)=28.322026.02 | 92.63 | 86.42 | 1 | — | — | |
| Med-DisSeg2026.05 | 92.2 | 85.7 | — | 93.7 | 91.4 | |
| SelfReg-UNetbackbone=SwinUnet, resolution=224x224, pre-trained=ImageNet2024.06 | 91.62 | 85.29 | — | — | — | |
| ConDSeg (AAAI 2025)2026.05 | 91.6 | 85.1 | — | 93.5 | 90.5 | |
| TPFIANet2026.02 | 91.32 | 84.88 | — | — | — | |
| UNeXtParams(M)=1.47, FLOPS(G)=4.582026.02 | 91.22 | 83.95 | 1.04 | — | — | |
| SelfReg-UNetbackbone=U-Net, resolution=224x2242024.06 | 90.93 | 84.08 | — | — | — | |
| UMambaLoss=MASL2026.01 | 90.45 | — | — | — | — | |
| S2M-NetLoss=standard Dice loss2026.01 | 90.33 | — | — | — | — | |
| UCTransNetresolution=224x2242024.06 | 90.18 | 82.96 | — | — | — | |
| DuckNetLoss=MASL2026.01 | 89.78 | — | — | — | — | |
| SwinUNetLoss=MASL2026.01 | 89.67 | — | — | — | — | |
| SwinUnetresolution=224x224, pre-trained=ImageNet2024.06 | 89.58 | 82.06 | — | — | — | |
| TransUNetLoss=MASL2026.01 | 89.23 | — | — | — | — | |
| U-Net++Loss=MASL2026.01 | 88.92 | — | — | — | — | |
| UMambaLoss=standard Dice loss2026.01 | 88.91 | — | — | — | — | |
| AttUnetresolution=224x2242024.06 | 88.8 | 80.69 | — | — | — | |
| MRUnetresolution=224x2242024.06 | 88.73 | 80.89 | — | — | — | |
| ACC-UNetparams=16.8M, FLOPS=38G2023.08 | 88.61 | — | — | — | — | |
| Trans Unetresolution=224x2242024.06 | 88.4 | 80.4 | — | — | — | |
| MultiResUNetparams=7.3M, FLOPS=1.1G2023.08 | 88.34 | — | — | — | — | |
| RAPUNetLoss=MASL2026.01 | 88.34 | — | — | — | — | |
| DuckNetLoss=standard Dice loss2026.01 | 88.34 | — | — | — | — | |
| SwinUNetLoss=standard Dice loss2026.01 | 88.23 | — | — | — | — | |
| UNetparams=14M, FLOPS=37G2023.08 | 87.99 | — | — | — | — | |
| DTAN (KBS 2024)2026.05 | 87.9 | 78.5 | — | 88.5 | 90.2 | |
| PraNetLoss=MASL2026.01 | 87.78 | — | — | — | — | |
| TransUNetLoss=standard Dice loss2026.01 | 87.78 | — | — | — | — | |
| U-NetLoss=MASL2026.01 | 87.65 | — | — | — | — | |
| Unet++resolution=224x2242024.06 | 87.56 | 79.13 | — | — | — | |
| CASF-Net (Comput. Biol. Med. 2023)2026.05 | 87.2 | 78.4 | — | 91.3 | 85.9 | |
| UCTransnetparams=66.4M, FLOPS=38.8G2023.08 | 87.17 | — | — | — | — | |
| U-Net++ (MICCAI 2018)2026.05 | 86.9 | 77.6 | — | 89.6 | 85.5 | |
| U-Net++Loss=standard Dice loss2026.01 | 86.67 | — | — | — | — | |
| DCSAU-Net (Comput. Biol. Med. 2023)2026.05 | 86.5 | 77.6 | — | 93 | 82.5 | |
| Swin-Unetparams=27.2M, FLOPS=6.2G2023.08 | 86.45 | — | — | — | — | |
| RAPUNetLoss=standard Dice loss2026.01 | 86.12 | — | — | — | — | |
| MedTresolution=224x2242024.06 | 85.92 | 75.47 | — | — | — | |
| MedTParams(M)=1.60, FLOPS(G)=21.242026.02 | 85.92 | 75.47 | 1.04 | — | — | |
| Attn U-Net (MIDL 2018)2026.05 | 85.9 | 76.6 | — | 91.8 | 82.2 | |
| DoubleAANet (Information Fusion 2025)2026.05 | 85.6 | 83.2 | — | 88.1 | 90.1 | |
| PraNetLoss=standard Dice loss2026.01 | 85.56 | — | — | — | — | |
| U-Net (MICCAI 2015)2026.05 | 85.5 | 75.8 | — | 90.3 | 82.8 | |
| U-Nettrained_from_scratch=true, resolution=224x2242024.06 | 85.45 | 74.78 | — | — | — | |
| U-NetLoss=standard Dice loss2026.01 | 85.43 | — | — | — | — | |
| XBFormer (TMI 2023)2026.05 | 84.3 | 73.7 | — | 84 | 85.7 | |
| SMESwin-Unetparams=169.8M, FLOPS=6.4G2023.08 | 83.72 | — | — | — | — | |
| PraNet (MICCAI 2020)2026.05 | 83 | 71.8 | — | 90.9 | 78 | |
| TGANet (MICCAI 2022)2026.05 | 81.8 | 77.1 | — | 84.7 | 80.2 |