  We apply nnU-Net to the segmentation task of the BraTS 2020 challenge. The
unmodified nnU-Net baseline configuration already achieves a respectable
result. By incorporating BraTS-specific modifications regarding postprocessing,
region-based training, a more aggressive data augmentation as well as several
minor modifications to the nnUNet pipeline we are able to improve its
segmentation performance substantially. We furthermore re-implement the BraTS
ranking scheme to determine which of our nnU-Net variants best fits the
requirements imposed by it. Our final ensemble took the first place in the
BraTS 2020 competition with Dice scores of 88.95, 85.06 and 82.03 and HD95
values of 8.498,17.337 and 17.805 for whole tumor, tumor core and enhancing
tumor, respectively.
