[Neuroimaging] [Nibabel] up/downsample image in Python

Christopher Markiewicz effigies at bu.edu
Fri Aug 18 17:28:32 EDT 2017

Hi Michael,

At first glance this looks reasonable to me, so if I were to try to figure
out the issue, I'd probably end up digging through nilearn's image
resampling, which uses ndimage.affine_transform under the hood [0]. It's a
much more flexible function that what you're looking for, but I think you
should be able to find what you need in all of that.

I'm also pretty sure that, with a nipy image, you can do this with
`img[::2, ::2, ::2]`, but not sure quite where to point you to in that



On Fri, Aug 18, 2017 at 4:52 PM, Michael Waskom <mwaskom at nyu.edu> wrote:

> Hi Matthew/Chris/others,
> Building on my previous question, I would also like to implement a
> pure-python downsampling of my images. I have done:
> import nibabel as nib
> from scipy import ndimage
> img = nib.load("brain.nii")
> data = img.get_data()
> lowres_data = ndimage.zoom(data, .5)
> zoom_xfm = np.eye(4)
> zoom_xfm[:3, :3] /= .5
> lowres_affine = img.affine.dot(zoom_xfm)
> lowres_img = nib.Nifti1Image(lowres_data, lowres_affine, img.header)
> lowres_img.to_fileame("lowres_brain.nii")
> This is very close, but when I view the resulting image in Freeview (my
> downsampled image is also slightly stretched relative to the anatomical).
> I can also compare to the result from mri_convert, i.e. mri_convert
> brain.nii -vs 2 2 2 lowres_brain.nii. The resulting image is not
> stretched relative to the hires brain, so it's not an artifact on
> Freeview's side. The images also don't have an identical affine (it is off
> by 0.5 in the third row of the final column.
> What am I missing about how to alter to affine of a downsampled image?
> Alternative, is ndimage.zoom not the right Python function to use here?
> Best,
> Michael
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