Dear Ajay,

Thank you for your email.

1) BundleWarp is specifically designed to register individual bundles
rather than whole-brain tractograms. While it is technically possible to
use BundleWarp to register two tractograms by treating them as sets of
streamlines (static and moving), it will require significantly more memory
and time. Additionally, registration may not be optimal due to the presence
of false positives in whole-brain tractograms. A better way to register
whole brain tractograms with BundleWarp involves clustering the tractograms
first to establish correspondences between clusters of two tractograms,
then registering the corresponding clusters individually using BundleWarp.
However, we have yet to test this approach thoroughly. In short, we
recommend using BundleWarp exclusively for bundles.

2) We use the HCP atlas of bundles in the MNI space, which can be
downloaded from
https://figshare.com/articles/dataset/Atlas_of_30_Human_Brain_Bundles_in_MNI_space/12089652
You can register bundles from your subject to the same type of bundles in
the atlas. BundleWarp outputs a warp map for each bundle.

3) It saves the Gaussian kernel and transformation matrix containing
transforms for every streamline in the moving bundle as NumPy files.

Best,
Bramsh

On Fri, May 17, 2024 at 2:09 PM Ajay Kurani <[email protected]>
wrote:

> To whom it may concern,
>   I recently saw a video regarding bundle warp and I had a few questions:
>
> 1) Are we able to use this on whole brain streamlines or only smaller
> bundles?
>
> 2) If we are only able to do smaller bundles, is there an MNI atlas you
> are currently using to warp to MNI space?  If so are you just taken segment
> at a time and getting individual warp fields?
>
> 3)Are the deformations in a format that we can convert to be ANTS
> compatible for other applications (such as improving T1 warping to an atlas
> by incorporating streamline warp calculations)?
>
> Thanks,
> Ajay
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