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.

8.7.3. nilearn.masking.compute_brain_mask

nilearn.masking.compute_brain_mask(target_img, threshold=0.5, connected=True, opening=2, memory=None, verbose=0, mask_type='whole-brain')[source]

Compute the whole-brain, grey-matter or white-matter mask. This mask is calculated using MNI152 1mm-resolution template mask onto the target image.

Parameters
target_imgNiimg-like object

See http://nilearn.github.io/manipulating_images/input_output.html Images used to compute the mask. 3D and 4D images are accepted. Only the shape and affine of target_img will be used here.

thresholdfloat, optional

The value under which the MNI template is cut off. Default=0.5

connectedbool, optional

If connected is True, only the largest connect component is kept. Default=True.

openingbool or int, optional

This parameter determines whether a morphological opening is performed, to keep only large structures. This step is useful to remove parts of the skull that might have been included. opening can be:

Note

Turning off opening (opening=False) will also prevent any smoothing applied to the image during the mask computation.

Default=2.

memoryinstance of joblib.Memory or str

Used to cache the masking process. By default, no caching is done. If a str is given, it is the path to the caching directory.

verboseint, optional

Verbosity level (0 means no message). Default=0.

mask_type{‘whole-brain’, ‘gm’, ‘wm’}, optional

Type of mask to be computed:

  • ‘whole-brain’: Computes the whole-brain mask.

  • ‘gm’: Computes the grey-matter mask.

  • ‘wm’: Computes the white-matter mask.

Default = ‘whole-brain’.

New in version 0.8.1.

Returns
masknibabel.nifti1.Nifti1Image

The whole-brain mask (3D image).