code: def correct_image_if_necessary(img):
      """
      Check image object header's format,
      update the object if necessary
  
      :param img:
      :return:
      """
      if img.header["dim"][0] == 5:
          # do nothing for high-dimensional array
          return img
      # Check that affine matches zooms
      pixdim = img.header.get_zooms()
      if not np.array_equal(
          np.sqrt(np.sum(np.square(img.affine[0:3, 0:3]), 0)),
          np.asarray(pixdim),
      ):
          if hasattr(img, "get_sform"):
              # assume it is a malformed NIfTI and try to fix it
              img = rectify_header_sform_qform(img)
      return img
  
imports: from __future__ import absolute_import, print_function, unicode_literals
  import errno
  import importlib
  import logging
  import os
  import re
  import sys
  import warnings
  import nibabel
  import numpy
  import pandas
  import scipy.ndimage
  import tensorflow
  from tensorflow.core.framework import summary_pb2
  from niftynet.io.image_loader import load_image_obj
  from niftynet.utilities.niftynet_global_config import NiftyNetGlobalConfig
  from niftynet.utilities.util_import import require_module
label_desc: Use image node_id 4 for calling a global function with example usage: correct_image_if_necessary(img) and returns: img, img