Note
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.
nilearn.masking.intersect_masks#
- nilearn.masking.intersect_masks(mask_imgs, threshold=0.5, connected=True)[source]#
Compute intersection of several masks.
Given a list of input mask images, generate the output image which is the threshold-level intersection of the inputs.
- Parameters:
- mask_imgs
listof Niimg-like objects See Input and output: neuroimaging data representation. 3D individual masks with same shape and affine.
- threshold
float, default=0.5 Gives the level of the intersection, must be within [0, 1]. threshold=1 corresponds to keeping the intersection of all masks, whereas threshold=0 is the union of all masks.
- connected
bool, optional If connected is True, only the largest connect component is kept. Default=True.
- mask_imgs
- Returns:
- grp_mask3D
nibabel.nifti1.Nifti1Image Intersection of all masks.
- grp_mask3D