Vessel Segmentation on CHASE DB1
0.8908clDicennU-Net
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| nnU-NetType=FULL2026.04 | 0.8908 | 0.8601 | — | |
| UniVGType=DE2026.04 | 0.8885 | 0.8539 | — | |
| MedSAMType=PFM2026.04 | 0.8776 | 0.844 | — | |
| MOCOType=PFM2026.04 | 0.875 | 0.8396 | — | |
| SimSiamType=PFM-V2026.04 | 0.873 | 0.8377 | — | |
| nnU-NetType=FIVE2026.04 | 0.8705 | 0.8426 | — | |
| SAMType=PFM2026.04 | 0.8692 | 0.8354 | — | |
| SimSiamType=PFM2026.04 | 0.8603 | 0.8325 | — | |
| PEPA SAM2026.06 | 0.855 | — | 0.708 | |
| UNetType=FULL2026.04 | 0.8452 | 0.8055 | — | |
| CPSType=WSL2026.04 | 0.8393 | 0.8042 | — | |
| AGMMType=WSL2026.04 | 0.8382 | 0.709 | — | |
| SimCLRType=PFM2026.04 | 0.8374 | 0.802 | — | |
| YoloCurvSegType=DE2026.04 | 0.8345 | 0.8089 | — | |
| FPBE SAM2026.06 | 0.832 | — | 0.703 | |
| iBOTType=PFM-V2026.04 | 0.8273 | 0.813 | — | |
| Vessel-captchaType=WSL2026.04 | 0.8188 | 0.7998 | — | |
| HM-Mamba2026.06 | 0.815 | — | 0.689 | |
| MedSAM2026.01 | 0.811 | 0.179 | 0.098 | |
| iBOTType=PFM2026.04 | 0.8053 | 0.7881 | — | |
| GCC-UNet2026.06 | 0.805 | — | 0.683 | |
| DBDMType=WSL2026.04 | 0.7992 | 0.6718 | — | |
| CCTType=WSL2026.04 | 0.7949 | 0.7738 | — | |
| Mid-Net2026.06 | 0.788 | — | 0.661 | |
| nnU-Net2026.06 | 0.787 | — | 0.676 | |
| FSG-NetType=FIVE2026.04 | 0.7851 | 0.7703 | — | |
| TVS-Net2026.06 | 0.78 | — | 0.665 | |
| CrossDiff2026.06 | 0.76 | — | 0.634 | |
| DBCNet2026.06 | 0.758 | — | 0.642 | |
| MASSLType=WSL2026.04 | 0.7525 | 0.7382 | — | |
| UNetType=FIVE2026.04 | 0.7353 | 0.7262 | — | |
| Retina-UnetType=FIVE2026.04 | 0.7347 | 0.7092 | — | |
| MAEType=PFM2026.04 | 0.7123 | 0.7264 | — | |
| PVAType=WSL2026.04 | 0.6028 | 0.5791 | — | |
| RetSAMEvaluation Protocol=Finetune2026.01 | 0.266 | 0.815 | 0.655 | |
| RetFound2026.01 | 0.261 | 0.665 | 0.498 | |
| RetSAMEvaluation Protocol=Linear2026.01 | 0.259 | 0.804 | 0.674 | |
| MedSAM22026.01 | 0.228 | 0.744 | 0.594 | |
| SAM22026.01 | 0.221 | 0.772 | 0.629 | |
| Med-SAM-Adapter2026.01 | 0.217 | 0.715 | 0.557 | |
| SAM32026.01 | 0.206 | 0.784 | 0.638 | |
| SAM2-UNet2026.01 | 0.199 | 0.793 | 0.657 | |
| Our (UniVG)number of training images=52026.04 | — | 0.8539 | — | |
| SOTA (Bhati et al., 2025)number of training images=202026.04 | — | 0.8401 | — |