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arXiv · 2309.13747

Look Ma, no code: fine tuning nnU-Net for the AutoPET II challenge by only adjusting its JSON plans

Fabian Isensee·Klaus H. Maier-Hein
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Abstract

We participate in the AutoPET II challenge by modifying nnU-Net only through its easy to understand and modify 'nnUNetPlans.json' file. By switching to a UNet with residual encoder, increasing the batch size and increasing the patch size we obtain a configuration that substantially outperforms the automatically configured nnU-Net baseline (5-fold cross-validation Dice score of 65.14 vs 33.28) at the expense of increased compute requirements for model training. Our final submission ensembles the two most promising configurations.

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Fabian Isensee, Klaus H. Maier-Hein. 2023-09-24. Look Ma, no code: fine tuning nnU-Net for the AutoPET II challenge by only adjusting its JSON plans. https://arxiv.org/abs/2309.13747

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