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Comparing the means of 2 images#
The goal of this example is to illustrate the use of the function
nilearn.image.math_img with a list of images as input.
We compare the means of 2 resting state 4D images. The mean of the images
could have been computed with nilearn nilearn.image.mean_img function.
Fetching 2 subject movie watching brain development fMRI datasets.
from nilearn import datasets
dataset = datasets.fetch_development_fmri(n_subjects=2)
Print basic information on the adhd subjects resting state datasets.
print(f"Subject 1 resting state dataset at: {dataset.func[0]}")
print(f"Subject 2 resting state dataset at: {dataset.func[1]}")
Subject 1 resting state dataset at: /home/himanshu/nilearn_data/development_fmri/development_fmri/sub-pixar123_task-pixar_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz
Subject 2 resting state dataset at: /home/himanshu/nilearn_data/development_fmri/development_fmri/sub-pixar001_task-pixar_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz
Comparing the means of the 2 movie watching datasets.
from nilearn import image, plotting
result_img = image.math_img(
"np.mean(img1, axis=-1) - np.mean(img2, axis=-1)",
img1=dataset.func[0],
img2=dataset.func[1],
)
plotting.plot_stat_map(
result_img, title="Comparing means of 2 resting state 4D images."
)
plotting.show()
Total running time of the script: (0 minutes 10.909 seconds)
Estimated memory usage: 898 MB
