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Tutorial: Deep Learning Advancing the State-of-the-Art in Medical Image Analysis.

, , , , , , and . Bildverarbeitung für die Medizin, page 6-7. Springer, (2017)

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nnU-Net: Breaking the Spell on Successful Medical Image Segmentation., , , , and . CoRR, (2019)Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection., , , , and . CoRR, (2018)An attempt at beating the 3D U-Net., and . CoRR, (2019)ModelHub.AI: Dissemination Platform for Deep Learning Models., , , , , , , , , and 6 other author(s). CoRR, (2019)Biomedical image analysis competitions: The state of current participation practice, , , , , , , , , and 1 other author(s). arXiv preprint arXiv:2212.08568, (2022)MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images., , , , , , , , , and 24 other author(s). IEEE Trans. Medical Imaging, 41 (10): 2728-2738 (2022)Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency., , , , , , and . CoRR, (2023)RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement., , , , , , , , and . CoRR, (2023)Why is the winner the best?, , , , , , , , , and 41 other author(s). CoRR, (2023)MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation., , , , , , , and . CoRR, (2023)