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

[Michael Waskom]

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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