[Neuroimaging] select all voxels in one hemisphere

[Amit Akula]

Hi Sam!

Hope you are doing well.

There are many segmentation algorithms that can be used to do this in a
more robust approach.

The Roland Henry Laboratory at UCSF (where I work) generally uses
Freesurfer's recon_all
<https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all> pipeline.
It can be used go generate a brain mask and further pipelines
<http://narr.bmap.ucla.edu/protocols/data_processing_archives/convert_freesurfer_outputs_and_calculate_dist_q/>
can
be use to generate hemisphere masks. It may be a bit overkill for your work
as it does much more subcortical segmentations.

There is also a way to manually segment/correct ROIs using nilearn if you
want to manually do more sophisticated segmentations/corrections. Here
<https://nilearn.github.io/auto_examples/04_manipulating_images/plot_roi_extraction.html>
is
a starting guide on that using nilearn.

Let me know if you want to take this offline and I can walk you through it.

Sincerely,
Amit

p.s. I can look into and send you more stuff like hemisplit
<https://nipype.readthedocs.io/en/0.12.1/interfaces/generated/nipype.interfaces.brainsuite.brainsuite.html#hemisplit>,
etc. if you would like a more focused tool other than recon_all. Lemme know!

On Wed, Nov 20, 2019 at 2:25 PM Sam W <samfmri at gmail.com> wrote:

> Hello!
> I've been trying unsuccessfully to select all voxels in one hemisphere
> using nilearn/nibabel
> I tried selecting all voxels that are to the left of the center of the
> image, something along these lines:
>
> im = load_img('my_im.nii')
> mid = int(np.ceil(im.shape[0]/2)) #centre of image
> data = im.get_data()
> data[mid:,:,:] #this should select the left side of image
>
> This wont work however because mid might not be exactly the middle of the
> brain...
> Is there a better way to do this?
> Thanks!
> Sam
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