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raamana / visualqc

VisualQC : assistive tool to ease the quality control workflow of neuroimaging data.
https://raamana.github.io/visualqc/
Apache License 2.0
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ENH: Add RGB outputs for diffusion qc #80

Open araikes opened 1 year ago

araikes commented 1 year ago

Description

Directionally encoded color maps would be helpful to assess correct ordering of the b-vector files relative to the image files. Conventions are red: left/right, green: anterior/poster, blue: superior/inferior. This would also help to provide a rough assessment of image quality.

DIPY has the ability to produce the requisite files https://dipy.org/documentation/1.7.0/examples_built/07_reconstruction/reconst_dti/#sphx-glr-examples-built-07-reconstruction-reconst-dti-py

raamana commented 1 year ago

thanks Adam for this great suggestion! I can't recall our discussion at NACC meeting accurately, but would you have the time and interest to contribute this? that'd be fantastic (and I'd be happy to walk you through the codebase), but no pressure at all as I know you are too busy.

araikes commented 1 year ago

Yes, happy to work on it as I have time.

Any objection to using DIPY as a requirement?

raamana commented 1 year ago

great - no I do not have any objection at all. let me know if you want me to walk you through the codebase.

since this is needed only for the diffusion modules (not for 5 others), we might need to implement some input validation logic to ensure dipy is installed for usages of diffusion visualqc module.

if it requires only a small parts of dipy, better solution would be include those parts in our library (assuming dipy allows that etc) so it would be easier and faster for users.