content: from typing import Type
  
  from nnunetv2.preprocessing.normalization.default_normalization_schemes import CTNormalization, NoNormalization, \
      ZScoreNormalization, RescaleTo01Normalization, RGBTo01Normalization, ImageNormalization
  
  channel_name_to_normalization_mapping = {
      'ct': CTNormalization,
      'nonorm': NoNormalization,
      'zscore': ZScoreNormalization,
      'rescale_to_0_1': RescaleTo01Normalization,
      'rgb_to_0_1': RGBTo01Normalization
  }
  
  
  def get_normalization_scheme(channel_name: str) -> Type[ImageNormalization]:
      """
      If we find the channel_name in channel_name_to_normalization_mapping return the corresponding normalization. If it is
      not found, use the default (ZScoreNormalization)
      """
      norm_scheme = channel_name_to_normalization_mapping.get(channel_name.casefold())
      if norm_scheme is None:
          norm_scheme = ZScoreNormalization
      # print('Using %s for image normalization' % norm_scheme.__name__)
      return norm_scheme
  