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

F. Isensee, J. Petersen, A. Klein, D. Zimmerer, P. Jaeger, S. Kohl, J. Wasserthal, G. Koehler, T. Norajitra, S. Wirkert, and K. Maier-Hein. CoRR, (2018)

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Dr. Marie Davidova University of Stuttgart

David Inkermann

David Briesenick University of Stuttgart

David Gudnason University of Stuttgart

David Stieler University of Stuttgart

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High- and Low-level image component decomposition using VAEs for improved reconstruction and anomaly detection.D. Zimmerer, J. Petersen, and K. Maier-Hein. CoRR, (2019)Robust environment perception for the Audi Autonomous Driving Cup.F. Kuhnt, M. Pfeiffer, P. Zimmer, D. Zimmerer, J. Gomer, V. Kaiser, R. Kohlhaas, and J. Zöllner. ITSC, page 1424-1431. IEEE, (2016)Spiking Convolutional Deep Belief Networks.J. Kaiser, D. Zimmerer, J. Tieck, S. Ulbrich, A. Rönnau, and R. Dillmann. ICANN (2), volume 10614 of Lecture Notes in Computer Science, page 3-11. Springer, (2017)A Case for the Score: Identifying Image Anomalies using Variational Autoencoder Gradients.D. Zimmerer, J. Petersen, S. Kohl, and K. Maier-Hein. CoRR, (2019)Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection.D. Zimmerer, S. Kohl, J. Petersen, F. Isensee, and K. Maier-Hein. CoRR, (2018)Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.F. Isensee, J. Petersen, A. Klein, D. Zimmerer, P. Jaeger, S. Kohl, J. Wasserthal, G. Koehler, T. Norajitra, S. Wirkert and 1 other author(s). Bildverarbeitung für die Medizin, page 22. Springer Vieweg, (2019)nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.F. Isensee, J. Petersen, A. Klein, D. Zimmerer, P. Jaeger, S. Kohl, J. Wasserthal, G. Koehler, T. Norajitra, S. Wirkert and 1 other author(s). CoRR, (2018)Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.T. Roß, D. Zimmerer, A. Vemuri, F. Isensee, M. Wiesenfarth, S. Bodenstedt, F. Both, P. Kessler, M. Wagner, B. Müller and 5 other author(s). Int. J. Comput. Assist. Radiol. Surg., 13 (6): 925-933 (2018)Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.T. Roß, D. Zimmerer, A. Vemuri, F. Isensee, S. Bodenstedt, F. Both, P. Kessler, M. Wagner, B. Müller, H. Kenngott and 3 other author(s). CoRR, (2017)Unsupervised Anomaly Localization Using Variational Auto-Encoders.D. Zimmerer, F. Isensee, J. Petersen, S. Kohl, and K. Maier-Hein. MICCAI (4), volume 11767 of Lecture Notes in Computer Science, page 289-297. Springer, (2019)

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Disambiguation of "Zimmerer, David"

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

Please choose a person to relate this publication to

Dr. Marie Davidova University of Stuttgart

David Inkermann

David Briesenick University of Stuttgart

David Gudnason University of Stuttgart

David Stieler University of Stuttgart

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Zimmerer, David"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.

Please choose a person to relate this publication to

Dr. Marie Davidova University of Stuttgart

David Inkermann

David Briesenick University of Stuttgart

David Gudnason University of Stuttgart

David Stieler University of Stuttgart

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
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Chicago
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nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.