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Nuclei Segmentation on MoNuSeg

84.17Dice CoefficientUN-SAM
12.586831.170949.75568.3391Jul 25, 2024Nov 14, 2024Mar 7, 2025Jun 27, 2025Oct 18, 2025Feb 7, 2026May 31, 2026

Evaluation results

MethodLinks
UN-SAMManual prompt=No, Fine-tuned=Yes2025.0884.1772.9384.27———————
ReN-UNet2025.0484.1273.06—81.4687.30.03292.24220.1583——
LKCell-LModel size=L2024.0783.96—82.99———————
CellViT-SAM-H2024.0783.08—86.8———————
SACManual prompt=No, Fine-tuned=Yes2025.0882.8969.2282.98———————
PromptNucSegManual prompt=No, Fine-tuned=Yes2025.0882.6269.8779.11———————
Med-SAManual prompt=Point, Fine-tuned=Yes2025.0882.4770.2482.57———————
CellSAMManual prompt=No, Fine-tuned=Yes2025.0882.2869.9682.4———————
SAMedManual prompt=Point, Fine-tuned=Yes2025.0882.2669.9482.43———————
ConvNeXt-FD2026.0582.23—————————
H-SAMManual prompt=No, Fine-tuned=Yes2025.0882.1369.7582.27———————
Pixel-wise annotation2026.0581.94—————————
UNet++2025.0481.8369.34—75.3190.290.04222.79010.6458——
SAMPOManual prompt=Point, Fine-tuned=No2025.0881.8369.2582.72———————
U2-Net2025.0481.3368.89—77.286.880.044413.4453.0647——
Hover-net + Lou et al.2026.0581.29—————————
SNSeg2026.0581.21—————————
FFEDNet2026.0581.2—————————
nnU-NetManual prompt=No, Fine-tuned=Yes2025.0881.0968.2881.24———————
Universal-model2026.0581—————————
nnUNet2025.0480.4267.6—81.6380.880.05553.33570.6852——
Huang et al.2026.0580.27—————————
TSCA-Net2026.0580.23—————————
TransUNet2025.0480.2267.89—81.5879.170.0613.56020.7379——
He et al.2026.0579.86—————————
UCTransNet2025.0479.265.56—75.8382.880.056118.3664.2——
Swin-Unet2025.0479.0165.38—72.3887.880.04033.78710.7893——
UCTransNet2026.0578.39—————————
All-in-SAMManual prompt=No, Fine-tuned=Yes2025.0878.3865.9479.21———————
Swin-Unet2026.0578.25—————————
Hover-Net2025.0477.2662.9—77.6777.540.06893.86870.8114——
Attention-UNetManual prompt=No, Fine-tuned=Yes2025.0876.8962.9277.45———————
Unet++Manual prompt=No, Fine-tuned=Yes2025.0876.7862.9778.31———————
TransUNetManual prompt=No, Fine-tuned=Yes2025.0875.0861.4176.55———————
U-NetManual prompt=No, Fine-tuned=Yes2025.0874.0660.2575.57———————
U-Net2025.0473.4259.62—74.8773.040.07663.66090.8109——
IAU-NetSupervision=Weakly supervised2026.0472.9958.35————————
MaxViT-UNet2024.0772.08—83.78———————
U-Net++2024.0766.17—79.49———————
Med Transformer2024.0766.17—79.55———————
U-Net2024.0765.99—79.43———————
SAMedManual prompt=No, Fine-tuned=Yes2025.0865.7651.8265.96———————
U-NetParams=31.0M, Pre-trained ImageNet Backbone=false, Zero-shot (without retraining)=true2026.0565.1—65.1———————
AMNParams=66.5M, Pre-trained ImageNet Backbone=true, Zero-shot (without retraining)=true2026.0565.1—65.1———————
Med-SAManual prompt=No, Fine-tuned=Yes2025.0864.9151.0265.06———————
SegNetParams=16.5M, Pre-trained ImageNet Backbone=false, Zero-shot (without retraining)=true2026.0564.88—64.88———————
HmsU-NetParams=68.2M, Pre-trained ImageNet Backbone=true, Zero-shot (without retraining)=true2026.0564.83—64.83———————
Swin-unet2024.0764.71—79.56———————
ResU-NetParams=32.4M, Pre-trained ImageNet Backbone=false, Zero-shot (without retraining)=true2026.0564.7—64.7———————
Scribble2LabelSupervision=Weakly supervised2026.0464.0858.11————————
ConvFormer-UNetParams=18.4M, Pre-trained ImageNet Backbone=false, Zero-shot (without retraining)=true2026.0563.63—63.63———————
rLossSupervision=Weakly supervised2026.0463.3757.89————————
pCE OnlySupervision=Weakly supervised2026.0463.1957.66————————
Pseudo-LabelSupervision=Weakly supervised2026.0461.1356.07————————
BEFUnetParams=33.2M, Pre-trained ImageNet Backbone=true, Zero-shot (without retraining)=true2026.0557.57—57.57———————
DeepLabV3+Params=44.5M, Pre-trained ImageNet Backbone=true, Zero-shot (without retraining)=true2026.0556.21—56.21———————
ViT-SmallParams=22.2M, Pre-trained ImageNet Backbone=true, Zero-shot (without retraining)=true2026.0547.67—47.67———————
SAM2Manual prompt=Point, Fine-tuned=No2025.0844.5129.8144.85———————
Original SAMManual prompt=Point, Fine-tuned=Yes2025.0837.5422.4746.33———————
SAM3Manual prompt=Text, Fine-tuned=No2025.0831.5645.7531.47———————
Original SAMManual prompt=No, Fine-tuned=Yes2025.0820.2812.6225.25———————
GrabCutSupervision=Weakly supervised2026.0415.347.03————————
Axial Attention U-NetType=Fully Attention Baseline2021.02—62.4976.83———————
FCNType=Convolutional Baselines2021.02—28.7128.84———————
Gated Axial Attn.Type=Proposed2021.02—62.0176.44———————
LoGoType=Proposed2021.02—66.1779.56———————
MedTType=Proposed2021.02—66.1779.55———————
Res-UNetType=Convolutional Baselines2021.02—66.0779.49———————
U-NetType=Convolutional Baselines2021.02—65.9979.43———————
U-NetArchitecture=Original2026.04—74.46——————87.3661.55
U-Net + oursArchitecture=U-Net with proposed method2026.04—76.99——————89.7164.28
U-Net++Type=Convolutional Baselines2021.02—66.0479.49———————
UCTransNetArchitecture=Original2026.04—74.36——————87.7960.93
UCTransNet + oursArchitecture=UCTransNet with proposed method2026.04—77.36——————90.1564.58