Analysis script organization

[evaalonsoortiz]

We should agree on an organization strategy for the analysis pipeline.

Option 1: Do everything in a jupyter notebook

• By "everything" I mean, download the dataset from openneuro, segment the spinal cord, identify pre-existing manual segmentations, co-register segmentation onto various contrasts, compute metrics, plot figures.
• This was first approach we took and we found that computation times (for downlaoding data, segmenting, co-registering) were generally very long.

Option 2: Separate data analysis from figure generation

• Create a script to download the dataset from openneuro, segment the spinal cord, identify pre-existing manual segmentations, co-register segmentation onto various contrasts, compute metrics. Save metrics to a file, save file to openneuro repo or github (?).
• Create a jupyter notebook to download metrics file and generate figures/plots of interest.
• Motivation: with this option, people who are interested to playing around with interactive figures and changing the way the data is represented do not have to go through the time-consuming steps listed above.

[jcohenadad]

Once https://github.com/spinal-cord-7t/coil-qc-code/pull/9 is merged and the data are uploaded on OpenNeuro, I will write a prototype notebook script that does "most" of the processing tasks. Then we can decide if having all the processing done on a notebook (option 1) is too cumbersome/slow.