This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.
Indexes into a 4D Niimg-like object in the fourth dimension.
Common use cases include extracting a 3D image out of img or creating a 4D image whose data is a subset of img data.
imgs: 4D Niimg-like object
index: Any type compatible with numpy array indexing
First we concatenate two mni152 images to create a 4D-image:
>>> from nilearn import datasets >>> from nilearn.image import concat_imgs, index_img >>> joint_mni_image = concat_imgs([datasets.load_mni152_template(), ... datasets.load_mni152_template()]) >>> print(joint_mni_image.shape) (91, 109, 91, 2)
We can now select one slice from the last dimension of this 4D-image:
>>> single_mni_image = index_img(joint_mni_image, 1) >>> print(single_mni_image.shape) (91, 109, 91)