| AI-SAM: Automatic and Interactive Segment Anything Model | ✓ Link | 90.66 | | Interactive AI-SAM gt box | 2023-12-05 |
| Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation | ✓ Link | 89.80 | | Medical SAM Adapter | 2023-04-25 |
| MedSegDiff-V2: Diffusion based Medical Image Segmentation with Transformer | ✓ Link | 89.50 | | MedSegDiff-v2 | 2023-01-19 |
| nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation | ✓ Link | 88.80 | 10.78 | nnUNet | 2018-09-27 |
| MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation | ✓ Link | 88.76 | | MedNeXt-L (5x5x5) | 2023-03-17 |
| MIST: Medical Image Segmentation Transformer with Convolutional Attention Mixing (CAM) Decoder | ✓ Link | 86.92 | 11.07 | MIST | 2023-10-30 |
| nnFormer: Interleaved Transformer for Volumetric Segmentation | ✓ Link | 86.57 | 10.63 | nnFormer | 2021-09-07 |
| AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation | ✓ Link | 86.11 | 12.88 | AgileFormer | 2024-03-29 |
| Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation | ✓ Link | 84.90 | 13.22 | MERIT | 2023-03-29 |
| AI-SAM: Automatic and Interactive Segment Anything Model | ✓ Link | 84.21 | | Automatic AI-SAM | 2023-12-05 |
| ParaTransCNN: Parallelized TransCNN Encoder for Medical Image Segmentation | ✓ Link | 83.86 | 15.86 | ParaTransCNN | 2024-01-27 |
| EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation | ✓ Link | 83.63 | 15.68 | EMCAD | 2024-05-11 |
| Rethinking Attention Gated with Hybrid Dual Pyramid Transformer-CNN for Generalized Segmentation in Medical Imaging | ✓ Link | 83.43 | 15.82 | PAG-TransYnet | 2024-04-28 |
| SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation | ✓ Link | 82.15 | | SegFormer3D | 2024-04-15 |
| MISSFormer: An Effective Medical Image Segmentation Transformer | ✓ Link | 81.96 | 18.20 | MISSFormer | 2021-09-15 |
| S2S2: Semantic Stacking for Robust Semantic Segmentation in Medical Imaging | ✓ Link | 81.19 | | TransUNet | 2024-12-17 |
| SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation | ✓ Link | 80.54 | | SelfReg-UNet: SwinUNet | 2024-06-21 |
| SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation | ✓ Link | 80.34 | | SelfReg-UNet: Vanilla UNet | 2024-06-21 |
| Adaptive t-vMF Dice Loss for Multi-class Medical Image Segmentation | ✓ Link | 80.26 | | FCB Former | 2022-07-16 |
| Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers | ✓ Link | 79.60 | | SETR | 2020-12-31 |
| Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation | ✓ Link | 79.13 | 21.55 | SwinUnet | 2021-05-12 |
| UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer | ✓ Link | 78.99 | 30.29 | UCTransNet | 2021-09-09 |
| TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation | ✓ Link | 77.48 | 31.69 | TransUNet | 2021-02-08 |