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add CCNet #532

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add CCNet #532

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agirodi
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@agirodi agirodi commented Jun 20, 2024

This PR adds the initial files for the corpus callosum segmentation module.

  • added CCNet directory, containing the complete module (with duplicate files from FastSurferCNN)
  • edited run_fastsurfer.sh to be able to run the CCNet

TODO:

  • Upload checkpoints and add to download checkpoint script
  • The module is based on another fork that has not been merged into dev yet. It needs to be merged, before this module can be comitted. Afterwards, the CCNet can be cut down, to the necessary files to avoid redundancy.
  • The CCNet currently uses the norm.mgz registered to upright space. Changes in the run_fastsurfer.sh could adress this constrain

@m-reuter
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m-reuter commented Jun 20, 2024

Please remove duplicate files first to avoid inflating our repository. Most of them are probably not even needed by CCNet?
Also merge current dev into your branch via a re-base, resolve conflicts and force push to your repo.
Not sure what you mean with "based on another fork that has not been merged into dev .." usually in your fork you need to merge our dev into your branch (preferred with rebase and force push to keep history linear).
Thanks.

@m-reuter m-reuter marked this pull request as draft July 2, 2024 08:30
@agirodi
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agirodi commented Jul 30, 2024

TODO:

  • Merge FSTumor branch into dev, rebase and remove copied changes
  • Strip legacy FSTumor code from CCNet structures
  • Remove repeated methods, that were modified by the FSTumor module
  • Add checkpoints download from websites functionality
  • Modify FastSurfer pipeline to create aligned images using asegs and use those as input for the CCNet
  • Add (Soft-) label mapping of CCNet segmentation into unaligned space
  • Post-processing cleanup of CC-oversegmentation
  • Retrain localization to use continuous distributions

@dkuegler
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Please remove data files (hdf5 files) from the commit and then squash your commits, we do not need the history to be "polluted" by really large data files.

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3 participants