[Neuroimaging] How to write a color 3D NIfTI

[sullivan, ken]

Worked perfect, thank you!

-Ken

On Thu, Nov 10, 2016 at 11:01 AM, Matthew Brett <matthew.brett at gmail.com>
wrote:

> Hi,
>
> On Thu, Nov 10, 2016 at 10:38 AM, sullivan, ken
> <ken.sullivan at kohyoung.com> wrote:
> > I've had no problem writing out 3D grayscale .nii files with nibabel and
> > opening them in NIfTI viewers (Mango, MCIcron). However I haven't been
> able
> > to write out 3D color, as each RGB plane is being interpreted as a
> different
> > volume.  Looking around a bit it seems there is a "dataset" field in the
> > header that needs to be set to 128 for 24-bit RGB planar images. One nice
> > thing about nibabel is how it automatically sets up the header based on
> the
> > numpy array fed to it. However this is an ambiguous case and if I print
> the
> > header information I can see it setting the datatype to 2 (uint8), which
> > presumably is why viewers are interpreting it as separate volumes, not
> > RGB24. I don't see any official support in the API for setting the
> datatype,
> > but the documentation does mention access to the raw fields for those
> with
> > "great courage". I tried this:
>
> Yes, it's a bit difficult to set the datatype post-hoc to the data
> array.  In practice, you'll have to cast the array correctly before
> passing it to the image constructor.  Something like:
>
> In [21]: shape_3d = (5, 6, 7)
> In [22]: rgb_arr = np.random.randint(0, 256, size=shape_3d +
> (3,)).astype('u1')
> In [23]: rgb_dtype = np.dtype([('R', 'u1'), ('G', 'u1'), ('B', 'u1')])
> In [24]: rgb_typed = rgb_arr.view(rgb_dtype).reshape(shape_3d)
> In [25]: import nibabel as nib
> In [26]: img = nib.Nifti1Image(rgb_typed, np.eye(4))
> In [27]: img.header['datatype']
> Out[27]: array(128, dtype=int16)
>
> Cheers,
>
> Matthew
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>

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