code: def metatensor_to_itk_image(
      meta_tensor: MetaTensor,
      channel_dim: int | None = 0,
      dtype: DtypeLike = np.float32,
      **kwargs,
  ):
      """
      Converts a MetaTensor object to an ITK image. Expects the MetaTensor to be in ChannelFirst format.
  
      Args:
          meta_tensor: The MetaTensor to be converted.
          channel_dim: channel dimension of the data array, defaults to ``0`` (Channel-first).
              ``None`` indicates no channel dimension. This is used to create a Vector Image if it is not ``None``.
          dtype: output data type, defaults to `np.float32`.
          kwargs: additional keyword arguments. Currently `itk.GetImageFromArray` will get ``ttype`` from this dictionary.
  
      Returns:
          The ITK image.
  
      See also: :py:func:`ITKWriter.create_backend_obj`
      """
      if (
          meta_tensor.meta.get(MetaKeys.SPACE, SpaceKeys.LPS)
          == SpaceKeys.RAS
      ):
          _meta_tensor = meta_tensor.clone()
          _meta_tensor.affine = orientation_ras_lps(meta_tensor.affine)
          _meta_tensor.meta[MetaKeys.SPACE] = SpaceKeys.LPS
      else:
          _meta_tensor = meta_tensor
      writer = ITKWriter(output_dtype=dtype, affine_lps_to_ras=False)
      writer.set_data_array(
          data_array=meta_tensor.data,
          channel_dim=channel_dim,
          squeeze_end_dims=True,
      )
      return writer.create_backend_obj(
          writer.data_obj,
          channel_dim=writer.channel_dim,
          affine=_meta_tensor.affine,
          affine_lps_to_ras=False,  # False if the affine is in itk convention
          dtype=writer.output_dtype,
          kwargs=kwargs,
      )
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, cast
  import numpy
  import torch
  from monai.config.type_definitions import DtypeLike
  from monai.data import ITKReader, ITKWriter
  from monai.data.meta_tensor import MetaTensor
  from monai.data.utils import orientation_ras_lps
  from monai.transforms import EnsureChannelFirst
  from monai.utils import MetaKeys, SpaceKeys, convert_to_dst_type, optional_import
label_desc: Use image node_id 2 for calling a global function with example usage: metatensor_to_itk_image(meta_tensor, channel_dim, dtype) and returns: writer