Medical Image Segmentation On Isic 2018 1
Metrics
DSC
mIoU
Results
Performance results of various models on this benchmark
Model Name | DSC | mIoU | Paper Title | Repository |
|---|---|---|---|---|
| ProMISe | 92.10 | 85.00 | ProMISe: Promptable Medical Image Segmentation using SAM | |
| UNeXt | 89.70 | - | UNeXt: MLP-based Rapid Medical Image Segmentation Network | |
| PVT-GCASCADE | 91.51 | 86.53 | G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation | |
| EMCAD | 90.96 | - | EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation | |
| FANet | 87.31 | - | FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation |
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