Hi @fepegar fepegar,
I am facing a similar issue pre-processing 3D cubes from a custom turbulence data.
I have managed to compute the mean and std deviation of all my cubes (of dimensions 21x21x21) along the three channels by splitting the dataset in batches, then I compute mean and std per batch and finally average them by the total dataset size.
I know I can not apply transforms.Normalize directly to my cubes because that function works with 2D data. When I look at the TorchIO documentation link you provide, I don’t see explicitly any example of normalizing 3D data.
Do you know if there is such an example within the documentation?