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

[Franco Pestilli]

I started an issue on the format and cc’ed Ariel Rokem and Eleftherios Garyfallidis the leaders of Dipy.

It might be important to loop in others.
Franco

> On Jul 30, 2020, at 11:14 AM, Matthew Brett <matthew.brett at gmail.com> wrote:
> 
> Hi,
> 
> Emanuele - would you mind opening an issue for this?
> 
> Can anyone volunteer to lead the new streamlines format group?  I'm
> not an expert at all.
> 
> Cheers,
> 
> Matthew
> 
> On Thu, Jul 30, 2020 at 5:03 PM Emanuele Olivetti <olivetti at fbk.eu> wrote:
>> 
>> Hi Matthew,
>> 
>> My colleagues and I would like to have a (much) faster loader of tractography data with a smaller memory footprint, especially for TRK (Trackvis) files. Just to give you an idea - which, yes, it's an extreme case but definitely not so infrequent for us - when loading a very large tractogram of 10 million streamlines it takes:
>> - 15 minutes and approximately 10Gb of RAM with Nibabel
>> - 1 minute and approximately 5Gb of RAM with our custom TRK loader (it works but code style is meh, https://github.com/FBK-NILab/nilab/blob/master/load_trk.py)
>> - 6 seconds and 3.5Gb of RAM if we previously save the tractogram as numpy array (numpy.savez()) and then load it with numpy.load(). But in this case, the streamlines are resampled to a fixed number of points.
>> 
>> Thank you for all the work done!
>> 
>> Emanuele
>> 
>> 
>> On Thu, Jul 30, 2020 at 5:01 PM Matthew Brett <matthew.brett at gmail.com> wrote:
>>> 
>>> 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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>> 
>> 
>> 
>> --
>> Emanuele Olivetti, Ph.D.
>> Senior Research Scientist at Bruno Kessler Foundation (FBK-ICT)
>> NeuroInformatics Laboratory (NILab) http://nilab.fbk.eu
>> Center for Mind and Brain Sciences (CIMeC), University of Trento
>> Via delle Regole 101 - 38123 Mattarello (Trento), ITALY
>> olivetti at fbk.eu - +39 0461314179
>> emanuele.olivetti at unitn.it - +39 0461282760
>> 
>> 
>> 
>> FBK vi invita a leggere il suo Piano di rientro | FBK invites you to read its Premises Reopening Plan.
>> 
>> --
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