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.
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Isensee F, Petersen J, Klein A, et al. nnU-Net: self-adapting framework for U-Netbased medical image segmentation. arXiv:180910486. 2018;.
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© 2019 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
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Isensee, F. et al. (2019). Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation. In: Handels, H., Deserno, T., Maier, A., Maier-Hein, K., Palm, C., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2019. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-25326-4_7
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DOI: https://doi.org/10.1007/978-3-658-25326-4_7
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