Panoptic segmentation with highly imbalanced semantic labels

Rumberger, Josef Lorenz; Baumann, Elias; Hirsch, Peter; Janowczyk, Andrew; Zlobec, Inti; Kainmueller, Dagmar (28 March 2022). Panoptic segmentation with highly imbalanced semantic labels. In: 2022 IEEE International Symposium on Biomedical Imaging Challenges (ISBIC). 10.1109/ISBIC56247.2022.9854551

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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.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

04 Faculty of Medicine > Service Sector > Institute of Pathology

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Baumann, Elias, Zlobec, Inti

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

Language:

English

Submitter:

Elias Baumann

Date Deposited:

07 Dec 2023 12:40

Last Modified:

07 Dec 2023 12:40

Publisher DOI:

10.1109/ISBIC56247.2022.9854551

BORIS DOI:

10.48350/189909

URI:

https://boris.unibe.ch/id/eprint/189909

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