image = torchio.Image(...)
print(image.spatial_shape) # -> (100, 100, 100)

crop = image[10:20, :, ::2] # returns a new ScalarImage where the affine matrix and data have been modified accordingly
print(crop.spatial_shape) # -> (10, 100, 50)

# image['data'] or image['affine'] would still work

def __getitem__(self, item):
    if isinstance(item, str):
        if item in (DATA, AFFINE):
            if item not in self:
                self.load()
        return super().__getitem__(item)
    else:
        check_validity(item) # do some checks
        if not isinstance(item, tuple):
            item = (item,)
        self.affine = modify_affine(self.affine, item) # to be implemented.
        if not self._loaded:
            self._slice = modify_slice(self._slice, item) # to be implemented. self._slice will be used when the
                                                          # image is finally loaded into memory. It would be
                                                          # initialized as an empty tuple.
        else:
            self.set_data(self.data[(slice(None), *item)]) # add the channel dim
        return self