code: def get_measurement_images(
      self, pipeline, object_name, category, measurement
  ):
      if object_name != "Image" or category != C_IMAGE_QUALITY:
          return []
      if measurement in (
          F_FOCUS_SCORE,
          F_LOCAL_FOCUS_SCORE,
          F_POWER_SPECTRUM_SLOPE,
          F_CORRELATION,
      ):
          result = []
          for image_group in self.image_groups:
              if image_group.check_blur.value:
                  result += self.images_to_process(
                      image_group, None, pipeline
                  )
          return result
  
      if measurement in SATURATION_FEATURES:
          result = []
          for image_group in self.image_groups:
              if image_group.check_saturation.value:
                  result += self.images_to_process(
                      image_group, None, pipeline
                  )
          return result
  
      if measurement in INTENSITY_FEATURES + [
          F_TOTAL_AREA,
          F_TOTAL_VOLUME,
      ]:
          result = []
          for image_group in self.image_groups:
              if image_group.check_intensity.value:
                  result += self.images_to_process(
                      image_group, None, pipeline
                  )
          return result
  
      if measurement.startswith(F_THRESHOLD):
          result = []
          for image_group in self.image_groups:
              all_threshold_groups = (
                  self.build_threshold_parameter_list()
                  if image_group.use_all_threshold_methods.value
                  else image_group.threshold_groups
              )
              for threshold_group in all_threshold_groups:
                  if (
                      image_group.calculate_threshold.value
                      and measurement
                      == F_THRESHOLD
                      + threshold_group.threshold_algorithm
                  ):
                      result += self.images_to_process(
                          image_group, None, pipeline
                      )
          return result
  
imports: import itertools
  import logging
  import cellprofiler_core.utilities.image
  import centrosome.cpmorphology
  import centrosome.haralick
  import centrosome.radial_power_spectrum
  import centrosome.threshold
  import centrosome.threshold
  import numpy
  import scipy.linalg.basic
  import scipy.ndimage
  from cellprofiler_core.constants.image import C_SCALING
  from cellprofiler_core.constants.measurement import COLTYPE_FLOAT, EXPERIMENT, MCA_AVAILABLE_POST_RUN
  from cellprofiler_core.constants.module._identify import O_WEIGHTED_VARIANCE, O_ENTROPY, O_FOREGROUND, O_BACKGROUND
  from cellprofiler_core.module import Module
  from cellprofiler_core.preferences import get_headless
  from cellprofiler_core.setting import Divider, HiddenCount, SettingsGroup, Binary, ValidationError
  from cellprofiler_core.setting.choice import Choice
  from cellprofiler_core.setting.do_something import DoSomething, RemoveSettingButton
  from cellprofiler_core.setting.subscriber import ImageListSubscriber
  from cellprofiler_core.setting.text import ImageName, Integer, Float
  from cellprofiler.modules.threshold import O_THREE_CLASS, O_TWO_CLASS
label_desc: Use image node_id 21 for calling the MeasureImageQuality obj's underlying member method code with example usage: obj.get_measurement_images(pipeline, object_name, category, measurement) and returns: list, result, result, result, result