Resample only one axis#

In this example, we create a custom preprocessing transfom that changes the image spacing across one axis only.

Inspired by this discussion.

original (sagittal), original (coronal), original (axial), transformed (sagittal), transformed (coronal), transformed (axial)
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import torch
import torchio as tio


class ResampleZ:

    def __init__(self, spacing_z):
        self.spacing_z = spacing_z

    def __call__(self, subject):
        # We'll assume all images in the subject have the same spacing
        sx, sy, _ = subject.spacing
        resample = tio.Resample((sx, sy, self.spacing_z))
        resampled = resample(subject)
        return resampled


torch.manual_seed(42)
image = tio.datasets.FPG().t1
transforms = tio.ToCanonical(), ResampleZ(spacing_z=7)
transform = tio.Compose(transforms)
transformed = transform(image)
subject = tio.Subject(original=image, transformed=transformed)
subject.plot()

Total running time of the script: ( 0 minutes 2.891 seconds)

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