Medical Image Re-identification on MIMIC-CXR
96.89CMC-R1MaMI
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| MaMIArchitecture=ViT-Base, All-in-One=true2025.03 | 96.89 | — | — | |
| Med-UniCArchitecture=ViT-Base, Fine-tuned=true2025.03 | 92.9 | — | — | |
| Packhäuser et al.Architecture=ViT-Base, Modality-specialized=X-ray2025.03 | 92.42 | — | — | |
| CLIPArchitecture=ViT-Base, Fine-tuned=true2025.03 | 92.3 | — | — | |
| MAEArchitecture=ViT-Base, Fine-tuned=true2025.03 | 88.2 | — | — | |
| TransReIDArchitecture=ViT-Base, Fine-tuned=true2025.03 | 86.8 | — | — | |
| MoCoV3Architecture=ViT-Base, Fine-tuned=true2025.03 | 84.2 | — | — | |
| RetFoundArchitecture=ViT-Base, Fine-tuned=true2025.03 | 54.8 | — | — | |
| Med-UniCArchitecture=ViT-Base, Fine-tuned=false2025.03 | 48.7 | — | — | |
| MoCoV3Architecture=ViT-Base, Fine-tuned=false2025.03 | 45.1 | — | — | |
| DINOv2Architecture=ViT-Base, Fine-tuned=false2025.03 | 36.4 | — | — | |
| CAEArchitecture=ViT-Base, Fine-tuned=false2025.03 | 36.2 | — | — | |
| BEITv2Architecture=ViT-Base, Fine-tuned=false2025.03 | 35.1 | — | — | |
| ImageNet-SupArchitecture=ViT-Base, Fine-tuned=false2025.03 | 34.1 | — | — | |
| CLIPArchitecture=ViT-Base, Fine-tuned=false2025.03 | 33.1 | — | — | |
| TransReIDArchitecture=ViT-Base, Fine-tuned=false2025.03 | 29.3 | — | — | |
| BioMedClipArchitecture=ViT-Base, Fine-tuned=false2025.03 | 25.2 | — | — | |
| MAEArchitecture=ViT-Base, Fine-tuned=false2025.03 | 23.8 | — | — | |
| BioMedClipArchitecture=ViT-Base, Fine-tuned=true2025.03 | 20.1 | — | — | |
| CT-CLIPArchitecture=ViT-Base, Fine-tuned=true2025.03 | 19.7 | — | — | |
| RetFoundArchitecture=ViT-Base, Fine-tuned=false2025.03 | 12.1 | — | — | |
| Ganz et al.Architecture=ViT-Base, Modality-specialized=CT2025.03 | 11.4 | — | — | |
| MaskFeatArchitecture=ViT-Base, Fine-tuned=false2025.03 | 9.2 | — | — | |
| CT-CLIPArchitecture=ViT-Base, Fine-tuned=false2025.03 | 3.8 | — | — | |
| BLIPArchitecture=ViT-Base, Fine-tuned=false2025.03 | 3.1 | — | — | |
| AlignArchitecture=ViT-Base, Fine-tuned=false2025.03 | 0.4 | — | — | |
| BYOLMethod Category=Foundation Models, Sensitivity=0.992025.12 | — | 72.1 | 0.7 | |
| CLIPMethod Category=Foundation Models, Sensitivity=0.992025.12 | — | 63.5 | 1.5 | |
| ConvNeXtMethod Category=Foundation Models, Sensitivity=0.992025.12 | — | 73 | 2.2 | |
| data2vecMethod Category=Foundation Models, Sensitivity=0.992025.12 | — | 58.7 | 1.8 | |
| DINOv2Method Category=Foundation Models, Sensitivity=0.992025.12 | — | 72.8 | 1.8 | |
| DINOv3Method Category=Foundation Models, Sensitivity=0.992025.12 | — | 81.9 | 3.8 | |
| InceptionMethod Category=Foundation Models, Sensitivity=0.992025.12 | — | 67.6 | 2.7 | |
| LCMemMethod Category=Task-specific, Sensitivity=0.99, Training Protocol=Jointly trained2025.12 | — | 99.6 | 93.3 | |
| LCMem Single StageMethod Category=Task-specific, Sensitivity=0.99, Training Protocol=Jointly trained2025.12 | — | 99.4 | 89.1 | |
| MAEMethod Category=Foundation Models, Sensitivity=0.992025.12 | — | 74.1 | 2 | |
| MSEMethod Category=Pixel-wise, Sensitivity=0.992025.12 | — | 66.1 | 1.5 | |
| NCCMethod Category=Pixel-wise, Sensitivity=0.992025.12 | — | 67.2 | 1.7 | |
| RandomMethod Category=Unsupervised, Sensitivity=0.992025.12 | — | 57.2 | 2.2 | |
| SiameseMethod Category=Task-specific, Sensitivity=0.99, Training Protocol=Jointly trained2025.12 | — | 71.2 | 1 | |
| Siamese + NT-XentMethod Category=Unsupervised, Sensitivity=0.992025.12 | — | 80.6 | 6.2 | |
| Siamese + NT-XentMethod Category=Task-specific, Sensitivity=0.99, Training Protocol=Jointly trained2025.12 | — | 77.9 | 3.9 | |
| SSIMMethod Category=Pixel-wise, Sensitivity=0.992025.12 | — | 62 | 1.2 | |
| SwAVMethod Category=Foundation Models, Sensitivity=0.992025.12 | — | 79.2 | 3.1 |