PanNuke
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Instance Segmentation | PanNuke 19 tissue types (three-fold cross-validation) | mPQ59.9 | 120 | |
| Nuclei Detection | PanNuke averaged across three dataset splits | Precision0.88 | 40 | |
| Nuclei Instance Segmentation | PanNuke | Neoplastic Score84.22 | 39 | |
| Pathology Image Classification | PanNuke (test) | Top-1 Accuracy89.62 | 37 | |
| Nuclei Classification | PanNuke | Neoplastic F1 Score73 | 31 | |
| Nuclei Segmentation | PanNuke T2 | IoU69.3 | 28 | |
| Nuclei Segmentation | PanNuke T1 | mIoU70.36 | 28 | |
| Nuclei Classification | PanNuke (official three-fold splits) | Precision (Neo)75 | 18 | |
| Binary Nuclei Detection | PanNuke | Precision84 | 17 | |
| Nuclei Instance Segmentation | PanNuke (target) | Dice82.97 | 14 | |
| Panoptic Segmentation | PanNuke (three-fold cross-validation) | Neoplastic58.4 | 12 | |
| classification | PanNuke | AUC91.5 | 11 | |
| Nuclei Segmentation | PanNuke | Dice (All Nuclei)79.42 | 11 | |
| Instance Segmentation | PanNuke | Dice Coefficient82.24 | 10 | |
| Medical Image Segmentation | PanNuke | mIoU85.14 | 10 | |
| Histopathology Image Classification | PanNuke | Accuracy71.52 | 10 | |
| Nuclei Segmentation | PanNuKe | mPQ58.61 | 10 | |
| Instance Segmentation | PanNuke | MACs (G)89.5 | 8 | |
| Nuclei Panoptic Segmentation | PanNuke (three-fold cross-val) | mPQ50.8 | 8 | |
| Mask-to-Image Consistency Alignment | PanNuke | FS1 Score82.32 | 7 | |
| Image Quality Assessment | PanNuke | FID7.7772 | 7 | |
| Cell-type classification | PanNuke Cls.-Eval (test) | Macro F10.3569 | 7 | |
| Nuclei instance segmentation | PanNuke Average over all tissues | bPQ69.55 | 7 | |
| Nuclei instance segmentation | PanNuke Uterus | Boundary PQ67.54 | 7 | |
| Nuclei instance segmentation | PanNuke Thyroid | bPQ72.93 | 7 |
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