[Neuroimaging] Find masked data voxel coordinates in the original Nifiti structure

[Sulantha Sanjeewa]

Hi,
You may be able to simply do,
zeros = numpy.zeros_like(mask_file_data)
zeros[numpy.where(mask_file_data > 0.5)] = vector

and then use the zeros to create a new Nifti1Image as mentioned in
https://bic-berkeley.github.io/psych-214-fall-2016/saving_images.html

Best regards,
Sulantha

On Fri, Nov 4, 2022 at 4:32 PM Jingyi Wang <jy_wang at ucsb.edu> wrote:

> Dear all,
>
> I computed a vector that each element in the vector corresponding to each
> voxel in my mask. I want to find out a way to put those values back to
> Nifiti data structure in the original mask file space.
>
> The total number of elements in the vector is exactly the same as the
> number of voxels in my mask. I used "nib.load" from the nibabel package to
> get the data for the whole brain time series. I load the mask file using
> "image.load_img" from the nilearn package, then mask the whole brain time
> series using "apply_mask" from the nilearn package. After masking, I got a
> 2D matrix with each column in the matrix corresponding to a voxel in the
> mask region. Then I did some computations to this 2D matrix that reduced
> this matrix into a vector, which the index of each element correlates with
> the original 2D matrix column index.
>
> I am trying to find whether there is a command that allows me to find the
> coordinates in Nifiti structure data for each column (that corresponds to
> the voxel) in the 2D matrix (that I got from "apply_mask").
>
> I also tried the command "new_img_like", but failed as I don't know how to
> find the element coordinates to the original 3D numpy array.
>
> Thanks in advance!
>
> Jingyi
>
>
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