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ResearchFormerly WizWand

Medical Image Re-identification on MIMIC-CXR

96.89CMC-R1MaMI
-3.459622.592748.64574.6973Mar 11, 2025
Updated 8mo ago

Evaluation results

MethodLinks
MaMIArchitecture=ViT-Base, All-in-One=true2025.0396.89——
Med-UniCArchitecture=ViT-Base, Fine-tuned=true2025.0392.9——
Packhäuser et al.Architecture=ViT-Base, Modality-specialized=X-ray2025.0392.42——
CLIPArchitecture=ViT-Base, Fine-tuned=true2025.0392.3——
MAEArchitecture=ViT-Base, Fine-tuned=true2025.0388.2——
TransReIDArchitecture=ViT-Base, Fine-tuned=true2025.0386.8——
MoCoV3Architecture=ViT-Base, Fine-tuned=true2025.0384.2——
RetFoundArchitecture=ViT-Base, Fine-tuned=true2025.0354.8——
Med-UniCArchitecture=ViT-Base, Fine-tuned=false2025.0348.7——
MoCoV3Architecture=ViT-Base, Fine-tuned=false2025.0345.1——
DINOv2Architecture=ViT-Base, Fine-tuned=false2025.0336.4——
CAEArchitecture=ViT-Base, Fine-tuned=false2025.0336.2——
BEITv2Architecture=ViT-Base, Fine-tuned=false2025.0335.1——
ImageNet-SupArchitecture=ViT-Base, Fine-tuned=false2025.0334.1——
CLIPArchitecture=ViT-Base, Fine-tuned=false2025.0333.1——
TransReIDArchitecture=ViT-Base, Fine-tuned=false2025.0329.3——
BioMedClipArchitecture=ViT-Base, Fine-tuned=false2025.0325.2——
MAEArchitecture=ViT-Base, Fine-tuned=false2025.0323.8——
BioMedClipArchitecture=ViT-Base, Fine-tuned=true2025.0320.1——
CT-CLIPArchitecture=ViT-Base, Fine-tuned=true2025.0319.7——
RetFoundArchitecture=ViT-Base, Fine-tuned=false2025.0312.1——
Ganz et al.Architecture=ViT-Base, Modality-specialized=CT2025.0311.4——
MaskFeatArchitecture=ViT-Base, Fine-tuned=false2025.039.2——
CT-CLIPArchitecture=ViT-Base, Fine-tuned=false2025.033.8——
BLIPArchitecture=ViT-Base, Fine-tuned=false2025.033.1——
AlignArchitecture=ViT-Base, Fine-tuned=false2025.030.4——
BYOLMethod Category=Foundation Models, Sensitivity=0.992025.12—72.10.7
CLIPMethod Category=Foundation Models, Sensitivity=0.992025.12—63.51.5
ConvNeXtMethod Category=Foundation Models, Sensitivity=0.992025.12—732.2
data2vecMethod Category=Foundation Models, Sensitivity=0.992025.12—58.71.8
DINOv2Method Category=Foundation Models, Sensitivity=0.992025.12—72.81.8
DINOv3Method Category=Foundation Models, Sensitivity=0.992025.12—81.93.8
InceptionMethod Category=Foundation Models, Sensitivity=0.992025.12—67.62.7
LCMemMethod Category=Task-specific, Sensitivity=0.99, Training Protocol=Jointly trained2025.12—99.693.3
LCMem Single StageMethod Category=Task-specific, Sensitivity=0.99, Training Protocol=Jointly trained2025.12—99.489.1
MAEMethod Category=Foundation Models, Sensitivity=0.992025.12—74.12
MSEMethod Category=Pixel-wise, Sensitivity=0.992025.12—66.11.5
NCCMethod Category=Pixel-wise, Sensitivity=0.992025.12—67.21.7
RandomMethod Category=Unsupervised, Sensitivity=0.992025.12—57.22.2
SiameseMethod Category=Task-specific, Sensitivity=0.99, Training Protocol=Jointly trained2025.12—71.21
Siamese + NT-XentMethod Category=Unsupervised, Sensitivity=0.992025.12—80.66.2
Siamese + NT-XentMethod Category=Task-specific, Sensitivity=0.99, Training Protocol=Jointly trained2025.12—77.93.9
SSIMMethod Category=Pixel-wise, Sensitivity=0.992025.12—621.2
SwAVMethod Category=Foundation Models, Sensitivity=0.992025.12—79.23.1