Medical Image Segmentation On Acdc
Metriken
Dice Score
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Dice Score | Paper Title | Repository |
|---|---|---|---|
| Swin UNet | 0.9 | Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation | |
| FCT | 0.9302 | The Fully Convolutional Transformer for Medical Image Segmentation | |
| AgileFormer | 0.9255 | AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation | |
| TransUNet | 0.8971 | TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation | |
| EMCAD | 0.9212 | EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation | |
| RWKV-UNet | 0.9217 | RWKV-UNet: Improving UNet with Long-Range Cooperation for Effective Medical Image Segmentation |
0 of 6 row(s) selected.