Source code for torchio.transforms.preprocessing.label.remap_labels

from typing import Dict

from ...transform import TypeMaskingMethod
from .label_transform import LabelTransform

[docs]class RemapLabels(LabelTransform): r"""Remap the integer ids of labels in a LabelMap. This transformation may not be invertible if two labels are combined by the remapping. A masking method can be used to correctly split the label into two during the `inverse transformation <invertibility>`_ (see example). Args: remapping: Dictionary that specifies how labels should be remapped. The keys are the old label ids, and the corresponding values replace them. masking_method: Defines a mask for where the label remapping is applied. It can be one of: - ``None``: the mask image is all ones, i.e. all values in the image are used. - A string: key to a :class:`torchio.LabelMap` in the subject which is used as a mask, OR an anatomical label: ``'Left'``, ``'Right'``, ``'Anterior'``, ``'Posterior'``, ``'Inferior'``, ``'Superior'`` which specifies a side of the mask volume to be ones. - A function: the mask image is computed as a function of the intensity image. The function must receive and return a :class:`torch.Tensor`. **kwargs: See :class:`~torchio.transforms.Transform` for additional keyword arguments. Example: >>> import torchio as tio >>> # Target label map has the following labels: >>> # {'left_ventricle': 1, 'right_ventricle': 2, 'left_caudate': 3, 'right_caudate': 4, >>> # 'left_putamen': 5, 'right_putamen': 6, 'left_thalamus': 7, 'right_thalamus': 8} >>> transform = tio.RemapLabels({2:1, 4:3, 6:5, 8:7}) >>> # Merge right side labels with left side labels >>> transformed = transform(subject) >>> # Undesired behavior: The inverse transform will remap ALL left side labels to right side labels >>> # so the label map only has right side labels. >>> inverse_transformed = transformed.apply_inverse_transform() >>> # Here's the *right* way to do it with masking: >>> transform = tio.RemapLabels({2:1, 4:3, 6:5, 8:7}, masking_method="Right") >>> # Remap the labels on the right side only (no difference yet). >>> transformed = transform(subject) >>> # Apply the inverse on the right side only. The labels are correctly split into left/right. >>> inverse_transformed = transformed.apply_inverse_transform() """ # noqa: E501 def __init__( self, remapping: Dict[int, int], masking_method: TypeMaskingMethod = None, **kwargs ): super().__init__(**kwargs) self.kwargs = kwargs self.remapping = remapping self.masking_method = masking_method self.args_names = ('remapping', 'masking_method',) def apply_transform(self, subject): for image in self.get_images(subject): new_data = mask = self.get_mask_from_masking_method( self.masking_method, subject, new_data, ) for old_id, new_id in self.remapping.items(): new_data[mask & ( == old_id)] = new_id image.set_data(new_data) return subject def is_invertible(self): return True def inverse(self): inverse_remapping = {v: k for k, v in self.remapping.items()} inverse_transform = RemapLabels( inverse_remapping, masking_method=self.masking_method, **self.kwargs, ) return inverse_transform