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Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

  • Fabian IsenseeEmail author
  • Jens Petersen
  • Andre Klein
  • David Zimmerer
  • Paul F. Jaeger
  • Simon Kohl
  • Jakob Wasserthal
  • Gregor Koehler
  • Tobias Norajitra
  • Sebastian Wirkert
  • Klaus H. Maier-Hein
Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Zusammenfassung

The U-Net was presented in 2015. With its straight-forward and successful architecture it quickly evolved to a commonly used benchmark in medical image segmentation. The adaptation of the U-Net to novel problems, however, comprises several degrees of freedom regarding the exact architecture, preprocessing, training and inference.

Literatur

  1. 1.
    Isensee F, Petersen J, Klein A, et al. nnU-Net: self-adapting framework for U-Netbased medical image segmentation. arXiv:180910486. 2018;.

Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  • Fabian Isensee
    • 1
    Email author
  • Jens Petersen
    • 1
  • Andre Klein
    • 1
  • David Zimmerer
    • 1
  • Paul F. Jaeger
    • 1
  • Simon Kohl
    • 1
  • Jakob Wasserthal
    • 1
  • Gregor Koehler
    • 1
  • Tobias Norajitra
    • 1
  • Sebastian Wirkert
    • 1
  • Klaus H. Maier-Hein
    • 1
  1. 1.Department of Medical Image ComputingGerman Cancer Research CenterHeidelbergDeutschland

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