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Contribution to a conference proceedings/Contribution to a book DKFZ-2026-02467
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Efficient Pan-Cancer Lesion Segmentation from Partially Labeled Data with nnU-Net

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2026
Springer Nature Switzerland Cham
ISBN: 978-3-031-96201-1 (print), 978-3-031-96202-8 (electronic)

Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation / Ma, Jun (Editor) [https://orcid.org/0000-0002-9739-0855] ; Cham : Springer Nature Switzerland, 2026, Chapter 5 ; ISSN: 0302-9743=1611-3349 ; ISBN: 978-3-031-96201-1=978-3-031-96202-8 ; doi:10.1007/978-3-031-96202-8
4th International challenge on Fast, Low-resource, Accurate Robust organ and pan-cancer segmentation, FLARE 2024, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, MarrakeshMarrakesh, Morocco, 6 Oct 2024 - 6 Oct 20242024-10-062024-10-06 Cham : Springer Nature Switzerland, Lecture Notes in Computer Science 15717, 43 - 53 () [10.1007/978-3-031-96202-8_5]  GO


Note: #EA:E230#LA:E230# / SCOPUS / ISSN 03029743
Contributing Institute(s):
  1. Medizinische Bildverarbeitung (E230)
Research Program(s):
  1. 315 - Bildgebung und Radioonkologie (POF4-315) (POF4-315)

Appears in the scientific report 2026
Database coverage:
NationallizenzNationallizenz ; SCOPUS
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Document types > Books > Contribution to a book
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 Record created 2026-10-07, last modified 2026-10-08
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