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_affine
ndarray
offloat
, 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.
- interpolation
str
Interpolation to be used during the interpolation. Can be “linear” (default) or “nearest”.
- cval
float
|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.- verbose
bool
|str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- movinginstance of
- Returns:
- reg_imginstance of
SpatialImage
The image after affine (and SDR, if provided) registration.
- reg_imginstance of
Notes
New in version 0.24.
Examples using mne.transforms.apply_volume_registration
#
Locating intracranial electrode contacts