code: def _get_voxels_in_foreground(self, patient_identifier, modality_id):
      all_data = np.load(
          join_paths(self.folder_with_cropped_data, patient_identifier)
          + ".npz"
      )["data"]
      modality = all_data[modality_id]
      mask = all_data[-1] > 0
      voxels = list(modality[mask][::10])
      return voxels
  
file_path: PaddleSeg/contrib/MedicalSeg/tools/preprocess_utils/dataset_analyzer.py
imports: import json
  import os
  import pickle
  import numpy
  from skimage.morphology import label
  from collections import OrderedDict
  from multiprocessing import Pool
  from .path_utils import join_paths
label_desc: Use image node_id 8 for calling the DatasetAnalyzer obj's underlying member method code with example usage: obj._get_voxels_in_foreground(patient_identifier, modality_id) and returns: voxels