FL4Health
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nnUNet PICAI
PR Type
[Feature | Fix | Documentation | Other ]
Short Description
Clickup Ticket(s): Initial nnUNet Integration for PICAI research
This PR does some initial work to leverage the nnUNet framework in FL4Health. This includes:
- Moving preprocessing into the repo so that we have the flexibility to produce preprocessed datasets in the format that nnUNet expects.
- Run preprocessing on raw dataset on cluster to produce desired dataset on cluster. Remove old datasets.
- Update the existing FL and central examples to use the new dataset format.
- Add scripts to train nnUNet on the Whole Gland Segmentation task. One script to train from scratch on PICAI dataset. Another script to finetune a model already trained on a private dataset in the Haider Lab.
- Update scripts to requeue if they are still running when they timeout (previously a huge issue since training always takes longer than max job time)
- Update documentation in the picai research folder to include the new functionality
In following tickets I will:
- Do some initial experiments to establish some baselines.
- More sophisticated data augmentation pipeline, possibly borrowed from nnUNet, to apply to current central and FL examples.
- Integrate architecture and training pipeline configuration from nnUNet to the federated setting.
Tests Added
Since a lot of this is research code and subject to change, I have not included tests. However, let me know if you think there are any tests that would be useful.