from collections.abc import Sequence
from ...transform import TypeMaskingMethod
from .remap_labels import RemapLabels
[docs]
class RemoveLabels(RemapLabels):
r"""Remove labels from a label map.
The removed labels are remapped to the background label.
This transformation is not `invertible <invertibility>`_.
Args:
labels: A sequence of label integers that will be removed.
background_label: integer that specifies which label is considered to
be background (typically, ``0``).
masking_method: See :class:`~torchio.transforms.RemapLabels`.
**kwargs: See :class:`~torchio.transforms.Transform` for additional
keyword arguments.
.. plot::
import torchio as tio
colin = tio.datasets.Colin27(2008)
label_map = colin.cls
colin.remove_image('t2')
colin.remove_image('pd')
names_to_remove = (
'Fat',
'Muscles',
'Skin and Muscles',
'Skull',
'Fat 2',
'Dura',
'Marrow'
)
labels = [colin.NAME_TO_LABEL[name] for name in names_to_remove]
skull_stripping = tio.RemoveLabels(labels)
only_brain = skull_stripping(label_map)
colin.add_image(only_brain, 'brain')
colors = {
0: (0, 0, 0),
1: (127, 255, 212),
2: (96, 204, 96),
3: (240, 230, 140),
4: (176, 48, 96),
5: (48, 176, 96),
6: (220, 247, 164),
7: (103, 255, 255),
9: (205, 62, 78),
10: (238, 186, 243),
11: (119, 159, 176),
12: (220, 216, 20),
}
colin.plot(cmap_dict={'cls': colors, 'brain': colors})
"""
def __init__(
self,
labels: Sequence[int],
background_label: int = 0,
masking_method: TypeMaskingMethod = None,
**kwargs,
):
remapping = {label: background_label for label in labels}
super().__init__(remapping, masking_method, **kwargs)
self.labels = labels
self.background_label = background_label
self.masking_method = masking_method
self.args_names = ['labels', 'background_label', 'masking_method']
def is_invertible(self):
return False