Segment any tumour: an uncertainty-aware vision foundation model for whole-body analysis.

Peiris H, Wang S, Egan G, Harandi M, Law M, Chen Z

Open source

DOI
10.1038/s41467-026-76531-2
Published
2026 Aug 11
Container
Nature communications
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1038/s41467-026-76531-2,
  title = {Segment any tumour: an uncertainty-aware vision foundation model for whole-body analysis.},
  author = {Peiris H and Wang S and Egan G and Harandi M and Law M and Chen Z},
  year = {2026},
  journal = {Nature communications},
  doi = {10.1038/s41467-026-76531-2},
  url = {https://doi.org/10.1038/s41467-026-76531-2}
}

RIS

TY  - JOUR
TI  - Segment any tumour: an uncertainty-aware vision foundation model for whole-body analysis.
AU  - Peiris H
AU  - Wang S
AU  - Egan G
AU  - Harandi M
AU  - Law M
AU  - Chen Z
PY  - 2026
JO  - Nature communications
DO  - 10.1038/s41467-026-76531-2
UR  - https://doi.org/10.1038/s41467-026-76531-2
ER  - 

APA

H, P., S, W., G, E., M, H., M, L., & Z, C. (2026). Segment any tumour: an uncertainty-aware vision foundation model for whole-body analysis.. Nature communications. https://doi.org/10.1038/s41467-026-76531-2

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