PanNuke
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Instance Segmentation | PanNuke 19 tissue types (three-fold cross-validation) | mPQ59.9 | 120 | |
| Nuclei Instance Segmentation | PanNuke | Neoplastic Score84.22 | 39 | |
| Nuclei Detection | PanNuke averaged across three dataset splits | Precision0.88 | 31 | |
| Nuclei Classification | PanNuke | Neoplastic Precision74 | 15 | |
| Nuclei Instance Segmentation | PanNuke (target) | Dice82.97 | 14 | |
| Panoptic Segmentation | PanNuke (three-fold cross-validation) | Neoplastic58.4 | 12 | |
| Histopathology Image Classification | PanNuke | Accuracy71.52 | 10 | |
| Nuclei Segmentation | PanNuKe | mPQ58.61 | 10 | |
| Binary Nuclei Detection | PanNuke | Precision84 | 10 | |
| Nuclei Classification | PanNuke (official three-fold splits) | Precision (Neo)72 | 9 | |
| Nuclei Panoptic Segmentation | PanNuke (three-fold cross-val) | mPQ50.8 | 8 | |
| Patch-level Histopathology Classification | PanNuke (5-fold CV) | Macro F195.76 | 7 | |
| Nuclei Classification | PanNuke (test) | Fd80 | 6 | |
| Nuclei Segmentation | PanNuke (test) | Dice82.2 | 6 | |
| Label Synthesis | PanNuke | FSD4.31 | 6 | |
| Nuclei Segmentation and Classification | PanNuke v1 (test) | mPQ (Adrenal Gland)0.5115 | 6 | |
| Nuclei Detection | PanNuke (three-fold cross-validation) | Neoplastic F1 Score75 | 4 | |
| Image Generation | PanNuke | FID50.29 | 4 | |
| Patch-Level Classification | PanNuke | Accuracy98.13 | 3 |
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