CoNSeP
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Nuclear Instance Segmentation | CoNSeP | AJI58.2 | 32 | |
| Nuclei Instance Segmentation | CoNSeP | mPQ52.25 | 28 | |
| Nuclei Segmentation | CoNSeP T2 | IoU46.69 | 26 | |
| Nuclei Segmentation | CoNSeP T1 | IoU64.73 | 26 | |
| Nuclei Instance Segmentation | CoNSeP (test) | PQ0.597 | 26 | |
| Cell Detection | CoNSeP (test) | mAP25.7 | 14 | |
| Segmentation | Consep | Dice Score64.5 | 11 | |
| Nuclei Classification | CoNSeP | Accuracy87.3 | 10 | |
| Nuclei Segmentation | CoNSeP | Dice (All Nuclei)76.81 | 9 | |
| Nuclei Detection and Classification | CoNSeP | F1 (Inflammatory)62.3 | 8 | |
| Nuclear Instance Segmentation | CoNSeP All | DICE68.1 | 8 | |
| Interactive Multi-class Image Segmentation | CoNSeP (val) | User Interaction Time (min)6 | 6 | |
| Cell Counting | CoNSeP | MAE (Inflamm)26.35 | 5 | |
| Nuclear Classification | CoNSeP | Fd0.748 | 5 | |
| Nuclei Instance Segmentation and Classification | CoNSeP (test) | mPQ0.536 | 5 | |
| Medical Image Segmentation | CoNSeP-T2 (test) | IoU40.88 | 3 | |
| Medical Image Segmentation | CoNSeP-T1 (test) | IoU59 | 3 | |
| Cell Detection | CoNSeP | Precision63.2 | 3 |
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