code: def preprocess(self, data_group):
      for file_idx, filename in enumerate(data_group.preprocessed_case):
          if self.reference_channel is None:
              specific_command = self.command + [
                  "ResampleScalarVolume",
                  "-i",
                  self.interpolation,
                  "-s",
                  self.dimensions,
                  quotes(filename),
                  quotes(self.output_filenames[file_idx]),
              ]
          else:
              specific_command = self.command + [
                  "ResampleScalarVectorDWIVolume",
                  "-R",
                  self.reference_channel,
                  "--interpolation",
                  self.interpolation_dict[self.interpolation],
                  quotes(self.base_file),
                  quotes(self.output_filename),
              ]
          subprocess.call(
              " ".join(specific_command),
              shell=True,
              stdout=FNULL,
              stderr=subprocess.STDOUT,
          )
  
      self.output_data = self.output_filenames
      data_group.preprocessed_case = self.output_filenames
  
imports: import subprocess
  import os
  import numpy
  import itertools
  from deepneuro.preprocessing.preprocessor import Preprocessor
  from deepneuro.utilities.util import add_parameter, quotes
label_desc: Use image node_id 2 for calling the Resize obj's underlying member method code with example usage: obj.preprocess(data_group) without return types