Skip to content

Resize

Resize

Bases: SpatialTransform

Resample images so the output shape matches the given target shape.

The field of view remains the same.

Warning

In most medical image applications, this transform should not be used as it will deform the physical object by scaling anisotropically along the different dimensions. The solution to change an image size is typically applying Resample and CropOrPad.

Parameters:

Name Type Description Default
target_shape TypeSpatialShape

Tuple \((W, H, D)\). If a single value \(N\) is provided, then \(W = H = D = N\). The size of dimensions set to -1 will be kept.

 required
image_interpolation str

See Interpolation.

 'linear'
label_interpolation str

See Interpolation.

 'nearest'

__call__(data)

Transform data and return a result of the same type.

Parameters:

Name Type Description Default
data InputType

Instance of torchio.Subject, 4D torch.Tensor or numpy.ndarray with dimensions \((C, W, H, D)\), where \(C\) is the number of channels and \(W, H, D\) are the spatial dimensions. If the input is a tensor, the affine matrix will be set to identity. Other valid input types are a SimpleITK image, a torchio.Image, a NiBabel Nifti1 image or a dict. The output type is the same as the input type.

 required

get_base_args()

Provides easy access to the arguments used to instantiate the base class (Transform) of any transform.

This method is particularly useful when a new transform can be represented as a variant of an existing transform (e.g. all random transforms), allowing for seamless instantiation of the existing transform with the same arguments as the new transform during apply_transform.

Note

The p argument (probability of applying the transform) is excluded to avoid multiplying the probability of both existing and new transform.

add_base_args(arguments, overwrite_on_existing=False)

Add the init args to existing arguments

validate_keys_sequence(keys, name) staticmethod

Ensure that the input is not a string but a sequence of strings.

to_hydra_config()

Return a dictionary representation of the transform for Hydra instantiation.