Panoptic segmentation with highly imbalanced semantic labels
About
We describe here the panoptic segmentation method we devised for our participation in the CoNIC: Colon Nuclei Identification and Counting Challenge at ISBI 2022. Key features of our method are a weighted loss specifically engineered for semantic segmentation of highly imbalanced cell types, and a state-of-the art nuclei instance segmentation model, which we combine in a Hovernet-like architecture.
Josef Lorenz Rumberger, Elias Baumann, Peter Hirsch, Andrew Janowczyk, Inti Zlobec, Dagmar Kainmueller• 2022
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Nuclei Detection and Classification | CoNIC (test) | Neu Score38 | 6 |
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