mne.transforms.apply_volume_registration#

mne.transforms.apply_volume_registration(moving, static, reg_affine, sdr_morph=None, interpolation='linear', cval=0.0, verbose=None)[source]#

Apply volume registration.

Uses registration parameters computed by compute_volume_registration().

Parameters
movinginstance of SpatialImage

The image to morph (“from” volume).

staticinstance of SpatialImage

The image to align with (“to” volume).

reg_affinendarray of float, shape (4, 4)

The affine that registers one volume to another.

sdr_morphinstance of dipy.align.DiffeomorphicMap

The class that applies the the symmetric diffeomorphic registration (SDR) morph.

interpolationstr

Interpolation to be used during the interpolation. Can be “linear” (default) or “nearest”.

cvalfloat | str

The constant value to assume exists outside the bounds of the moving image domain. Can be a string percentage like '1%' to use the given percentile of image data as the constant value.

verbosebool | str | int | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns
reg_imginstance of SpatialImage

The image after affine (and SDR, if provided) registration.

Notes

New in version 0.24.

Examples using mne.transforms.apply_volume_registration#

Locating intracranial electrode contacts

Locating intracranial electrode contacts

Locating intracranial electrode contacts