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Panoptic segmentation with highly imbalanced semantic labels

3 March 2022
J. L. Rumberger
Elias Baumann
Peter Hirsch
Andrew Janowczyk
Inti Zlobec
Dagmar Kainmueller
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Abstract

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.

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