[Neuroimaging] CZI grant - what would you like to see in Nibabel?

Samuel St-Jean stjeansam at gmail.com
Sat Aug 1 08:27:18 EDT 2020

Even before talking multimodality, it would be useful to have something 
multi MRI weighting. As of now you have the bval/bvec for diffusion you 
need to carry around, if you are a bit fancy you have the gradient 
timings an other things, and if you use non spin-echo stuff you also 
need to carry around another layer of information. Other stuff like fmri 
seems to also carry around relevant info, and you can add to the game 
relaxometry experiments (I'd guess inversion time, flip angle and other 
things for T1 mapping for example), and if you play with more advanced 
diffusion sequences you have new data structures you need to know.

That's a lot of side files that can go around beyond your everyday 
nifti. And pretty much every tool uses his own internal format to keep 
track of all that because of this (on top of my mind there is .mif for 
mrtrix, exploredti stash everything in a matlab file after conversion, 
there is also an .xps format also for advanced diffusion with is using 
matlab, probably others).  I personally started stashing everything in a 
json file for convenience, but having a flexible, throw everything in it 
file would definitely be useful, and could potentially be used by other 
software, making mixing tools far easier if everything was read from a 
central file, just as now it is easy to go around with a nifti, bval and 
bvec files.

So I'd vote for something similar, say based on json because it is 
somewhat readable and standard, which would record relevant experimental 
info (similar to what dcm2niix does I'd guess, but with only the 
necessary info). It would also make it easy to add new stuff in it over 
time. I have a rough and barebone xps to json converter I made somewhere 
if it can serve and an example of what I mean.


Le 2020-07-30 à 11 h 27, thomas VINCENT a écrit :
> Hello,
> I think providing tools for multimodality would be great. The basic 
> experimental use case is that we have several simultaneous imaging 
> measures, eg fmri eeg and breathing. The first concern is to have a 
> common container for neuroimaging data from different modalities. The 
> second one is to conveniently handle temporal synchronization between 
> measures and then interpolation on the same temporal grid.
> My one cent.
> Thanks for all the great work on nibabel so far!
> Thomas.
> Le jeu. 30 juill. 2020 11 h 01, Matthew Brett <matthew.brett at gmail.com 
> <mailto:matthew.brett at gmail.com>> a écrit :
>     Hi,
>     Although this is pushing things close the wire, I am currently trying
>     to work out whether to apply for a Chan Zuckerberg grant for Nibabel:
>     https://chanzuckerberg.com/wp-content/uploads/2020/06/EOSS-3-RFA-Announcement-and-Instructions-CYCLE-3-COMBINED-1.pdf
>     Before we do that, I wanted to ask - if y'all could get anything into
>     Nibabel - what
>     would it be?
>     So far, in various conversations, Chris Markiewicz and I came up with:
>     * More comprehensive DICOM to NIfTI etc support
>     * Labelled axes for images, maybe via xarray
>     * Integrated API for surface formats [1]
>     * HDF5 serialization for many image formats
>     * Ability to read images directly from URLs, read / write images to /
>     from AWS, GCS, Azure data storage addresses [2]
>     * Optimized visualization for web and desktop
>     Is there anything else you'd like to see?
>     See you,
>     Matthew
>     [1] https://github.com/nipy/nibabel/issues/936
>     [2] c.f.
>     https://pandas.pydata.org/pandas-docs/version/1.1.0/whatsnew/v1.1.0.html#fsspec-now-used-for-filesystem-handling
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