I have the two files for every brain - Brain.nii.gz and Mask.nii.gz.
The first file is the full MRI, and the second is just a mask of segmentation of a tumor. I want to overlay the segmentation on the brain and highlight / intensify that area to be able to more clearly see the tumor and export this file / save this.
I have been exploring various options but cannot find how to do it. I have explored nilearn, FSL, NiftiMasker, and more but cannot figure it out.
Hi Steven,
Many thanks for the prompt response. The page is really useful but do you know if there is a way I can then export the plots created as its own nifti file?
I am a bit confused, could you describe what you want in this output nifti file? Are you saying that you want to export just the part of Brain.nii.gz that is contained in Mask.nii.gz?
Keep in mind that a NIFTI file is essentially a 3D (or 4D if time is an axis) matrix with header information. You won’t be able to export a fancy art effect to numerical form.
In that case, as long as the two images have the same resolution and are in the same space, then you can load the image in nilearn, get the indexes of the mask data, and then index your brain data with the mask data and add some arbitrary value to those points to make them more intense.
mask=nilearn.image.load_img(path_to_mask) will load the image, then I think you can do mask_data = mask.get_fdata() to get the data matrix. Assuming your mask is just binary, you can then find the indexes that of the mask by saying mask_indexes=(mask_data==1). Load your brain data the same way you did the mask, and then add your modifier to your brain data at the mask_indexes.
There is probably a more efficient way to do this, but one way is to loop over coordinates of the mask indexes, and do brain_data[i,j,k]=brain_data[i,j,k] + mod, where i,j,k is a single coordinate of the mask.
I see I made a slight typo in my original solution, the affine should come from brain not brain_data, thanks for pointing that out. I should also note that the solution above will only work if the mask and brain have the same resolution, if not, you will have to resample your mask to the brain data.
You might want to use the nilearn resample to img function instead (using nearest neighbor interpolation since you are working with a mask) nilearn.image.resample_to_img - Nilearn
I tried resample_to_img but was still getting error. So just swapped source image and target image in the highlighted code and that generated the .nii file.
