code: def determine_normalization_scheme(self):
      schemes = OrderedDict()
      modalities = self.dataset_properties["modalities"]
      num_modalities = len(list(modalities.keys()))
  
      for i in range(num_modalities):
          if modalities[i] == "CT" or modalities[i] == "ct":
              schemes[i] = "CT"
          elif modalities[i] == "noNorm":
              schemes[i] = "noNorm"
          else:
              schemes[i] = "nonCT"
      return schemes
  
imports: import os
  import pickle
  import shutil
  from collections import OrderedDict
  from .image_crop import get_case_identifier_from_npz
  from .preprocessing import GenericPreprocessor, PreprocessorFor2D
  from .experiment_utils import *
  from .path_utils import join_paths
label_desc: Use image node_id 7 for calling the ExperimentPlanner obj's underlying member method code with example usage: obj.determine_normalization_scheme() and returns: schemes