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<div class="moz-cite-prefix"> Hi Greg,<br>
<br>
You might take at look at <code class="descclassname">nilearn.image.</code><code
class="descname">resample_img<br>
<a class="moz-txt-link-freetext" href="https://nilearn.github.io/modules/generated/nilearn.image.resample_img.html">https://nilearn.github.io/modules/generated/nilearn.image.resample_img.html</a><br>
Best,<br>
<br>
Bertrand<br>
</code><br>
On 01/12/2015 18:55, Greg Kiar wrote:<br>
</div>
<blockquote
cite="mid:CAB7SS2vEC0DhuDh9q9QNmvWjjJucqhm+K4O_o-NGH6vjG3mHfg@mail.gmail.com"
type="cite">
<div dir="ltr">Hi,
<div><br>
</div>
<div>I'm working with various parcellations of the brain which
have been defined at a 3mm resolution, though my data exists
in a 1mm space (the MNI152 space). When opening these images
with a nifti viewer it is fine as the affine transform maps
them properly to scale. However, when I'm working with data in
python I would like my labels defined at 3mm to be in the
MNI152 space (that they also overlap in voxel space, as well).
I would like to write a script that "ingests" a low resolution
(3mm) atlas into the 1mm MNI152 space, and nearest-neighbor
interpolates values not defined, if you will. Do you know how
I can easily do this?</div>
<div><br>
</div>
<div>Thanks so much,</div>
<div>Greg <br clear="all">
<div>
<div class="gmail_signature">
<div dir="ltr">
<div>--</div>
<div>Greg Kiar <<a moz-do-not-send="true"
href="mailto:gkiar07@gmail.com" target="_blank">gkiar07@gmail.com</a>></div>
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