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def load_labelled_volume(data, vmin=0, alpha=1, **kwargs):
docstring:
Load volume image from .nrrd file.
It assume that voxels with value = 0 are empty while voxels with
values > 0
are labelles (e.g. to indicate the location of a brain region in a
reference atlas)
:param data: str, path to file with volume data or 3d numpy array
:param vmin: float, values below this numner will be assigned an
alpha=0 and not be visualized
:param **kwargs: kwargs to pass to the Volume class from vedo
:param alpha: float in range [0, 1], transparency [for the part of
volume with value > vmin]
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def extract_volume_surface(vol, threshold=0.1, smooth=False):
docstring:
Returns a vedo mesh actor with just the outer surface of a volume
:param vol: instance of Volume class from vedo
:param threshold: float, min value to threshold the volume for
isosurface extraction
:param smooth: bool, if True the surface mesh is smoothed
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def extract_label_mesh(vol, lbl):
docstring:
Given a vedo Volume with a scalar value labelling each voxel,
this function returns a mesh of only the voxels whose value matches
the lbl argument
:param vol: a vedo Volume
:param lbl: float or int