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Repository for MICCAI 2022 work, "Few-Shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-learning"

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Running guidance

  1. Check your cuda version. I've tested cu102 and it is able to work.
  2. Python version >= 3.8 would be recommended.
  3. To install the python packages, change the variable CUDA in the script req_torch_geo.sh, then run it.
  4. To train the model, run the following command:
    python main.py --config demo --stage 1
  5. To evaluate the model, run the following command:
    python main.py --config demo --stage 2
  6. To perform meta-testing on the model, run the following command:
    # i = 1, 2, 3, 4, 5, 6
    # j = 1, 2, 3
    python main.py --config demo --stage 3 --eval spt<i>set<j> --pred qry<i>
  7. Clinical task:
    # i = 1, 2, 3, 4
    python main.py --config demo --stage 3 --eval real_spt<i> --pred real_qry<i>
  8. To make graphs based on the pre-defined geometry, run the following command:
    python main.py --config demo --stage 0
  9. Check here for data.

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Repository for MICCAI 2022 work, "Few-Shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-learning"

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