Adapt the steps from abcd-noddi-tbss-experiments to this pipeline

[ebrahimebrahim]

Relies on #2 being done

Feel free to use the "convert to issue" feature on these tasks to break them out into dedicated discussions or track separately.

• [ ] #15
  • A sort of compatibility layer from $DATASET -> dwi ready for consumption.
  • extract_images.py
  • concatenate_scans.py
  • generate_nrrd_headers.py
• [x] #16
  • generate_b0_averages.py
  • hd-bet
• [ ] DTI Fit (optional)
  • fit_dti.py
• [ ] NODDI Fit
  • fit_watson_noddi.py
  • fit_noddi_amico.py
• [ ] Estimate FODs
  • estimate_fods_dipy.py
• [ ] Compute degree powers
  • compute_degree_powers.py
• [x] #7
• [ ] Register to population template
  • Depends on https://github.com/brain-microstructure-exploration-tools/abcd-noddi-tbss-experiments/issues/21

Some notes:

The "NODDI Fit" step is the slow part by far, and then the data conversion step. These are where caching and avoiding duplicate work is critical.

dipy is easy to get in Slicer, but we need mrtrix for registration.

[ebrahimebrahim]

Note that the slicer dipy workflows idea can support the task here to some extent. Right now it's just the DTI fit and one of the methods for CSD, but ultimately we may end up adding more and more dipy-related steps in the future. And if we implement some novel algorithm ourselves then dipy would be the primary place to contribute it.