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ResearchFormerly WizWand

Medical Image Segmentation on D6

97.2DSCMedNeXt-v2
88.77690.96393.1595.337Dec 19, 2025
Updated 8mo ago

Evaluation results

MethodLinks
MedNeXt-v2Pretraining Datasets=CADS-sub, Pretraining Protocol=Our Pretrained Weights, Model Configuration=Patch × 1.52025.1297.297.87
MedNeXt-v1Pretraining Datasets=-, Pretraining Protocol=Training from Scratch2025.1297.1297.74
MedNeXt-v2Pretraining Datasets=-, Pretraining Protocol=Training from Scratch2025.1297.0697.7
MedNeXt-v2Pretraining Datasets=CADS-sub, Pretraining Protocol=Our Pretrained Weights, Model Configuration=Width × 2.02025.1297.0497.68
MedNeXt-v2Pretraining Datasets=CADS-sub, Pretraining Protocol=Our Pretrained Weights, Model Configuration=Base Network2025.1297.0397.62
ResEncLPretraining Datasets=-, Pretraining Protocol=Training from Scratch2025.1296.8997.57
MedNeXt-v1Pretraining Datasets=Abd.Atlas1.0, Pretraining Protocol=Pretrained Baselines2025.1296.8197.39
CADSPretraining Datasets=CADS-Organ, Pretraining Protocol=Pretrained Baselines2025.1296.7597.36
nnUNetPretraining Datasets=-, Pretraining Protocol=Training from Scratch2025.1296.6397.22
Vista3DPretraining Datasets=Vista, Pretraining Protocol=Pretrained Baselines2025.1296.4496.95
STUNet-LPretraining Datasets=Abd.Atlas1.0, Pretraining Protocol=Pretrained Baselines2025.1296.496.94
MRSeg.Pretraining Datasets=TotalSeg-MR, Pretraining Protocol=Pretrained Baselines2025.1296.2196.72
TotalSeg.Pretraining Datasets=TotalSeg-CT, Pretraining Protocol=Pretrained Baselines2025.1296.1196.6
SegVolPretraining Datasets=SegVol, Pretraining Protocol=Pretrained Baselines2025.1289.188.56