ISIC
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Medical Image Segmentation | ISIC 2018 | Dice Score93.02 | 187 | |
| Skin Lesion Segmentation | ISIC 2018 (test) | Dice Score92.3 | 143 | |
| Skin Lesion Segmentation | ISIC 2017 (test) | Dice Score91.4 | 134 | |
| Medical Image Segmentation | ISIC 2017 | Dice Score98.7 | 102 | |
| Skin Lesion Segmentation | ISIC 2018 | Dice Coefficient95.47 | 94 | |
| Medical Image Segmentation | ISIC | DICE94.8 | 79 | |
| OOD detection | ISIC Ink Artefacts (Similar) | AUROC85.68 | 70 | |
| Medical Image Segmentation | ISIC 2018 (test) | Dice Score95.11 | 66 | |
| 2D skin lesion segmentation | ISIC 2017 | mIoU85.55 | 60 | |
| Semantic Segmentation | ISIC (test) | mIoU2,341 | 59 | |
| Mislabeled data detection | ISIC | F1 Score83.93 | 55 | |
| Medical Image Segmentation | ISIC (test) | IoU0.865 | 55 | |
| Image Classification | ISIC | Accuracy84.93 | 52 | |
| Few-Shot Segmentation | ISIC 2018 | mIoU73.6 | 51 | |
| 5-way classification | ISIC BSCD-FSL | Average Accuracy62.27 | 45 | |
| Medical Image Classification | ISIC | Accuracy79.76 | 43 | |
| Image Classification | ISIC 2019 (test) | Macro F144.7 | 43 | |
| Medical Image Segmentation | ISIC 2017 (test) | Dice90.07 | 41 | |
| Skin Lesion Segmentation | ISIC 2016 | Dice Score (D)96.28 | 40 | |
| OOD detection | ISIC Colour Chart Artefacts, Synth Dissimilar | AUROC94.48 | 40 | |
| OOD detection | ISIC Colour Chart Artefacts, Similar | AUROC97 | 40 | |
| OOD detection | ISIC Colour Chart Artefacts Synth Similar | AUROC0.9748 | 40 | |
| OOD detection | ISIC Colour Chart Artefacts (Dissimilar) | AUROC0.9552 | 40 | |
| OOD detection | ISIC Ink Artefacts (Dissimilar) | AUROC74.97 | 40 | |
| Medical Image Classification | ISIC 2018 | Accuracy92.61 | 40 |
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