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Multi Tissue Nucleus Segmentation On Consep
Metrics
Dice
Jaccard Index
PQ
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||||
|---|---|---|---|---|---|
| GC-MHVN | 0.855 | 0.576 | 0.559 | MRL: Learning to Mix with Attention and Convolutions | - |
| HoVer-Net | 0.853 | 0.571 | 0.547 | HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images | |
| SONNET | 0.844 | 0.586 | 0.540 | SONNET: A Self-Guided Ordinal Regression Neural Network for Segmentation and Classification of Nuclei in Large-Scale Multi-Tissue Histology Images | - |
| PointNu-Net | 0.822 | 0.56 | 0.545 | PointNu-Net: Keypoint-assisted Convolutional Neural Network for Simultaneous Multi-tissue Histology Nuclei Segmentation and Classification |
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