code: def images(download_path):
      img_path = os.path.join(download_path, "SA_64x64_v2.0", "DICOM")
      cmr_dcm_list = read_dicom_dir(
          img_path,
          sort_instance=True,
          sort_patient=True,
          check_series_uid=True,
      )
      dcms = []
      for i in range(5):
          for j in range(len(cmr_dcm_list[i])):
              dcms.append(cmr_dcm_list[i][j])
      dcm5_list = check_dicom_series_uid(dcms)
      cmr_images = dicom2arraylist(
          dicom_patient_list=dcm5_list, return_patient_id=False
      )
  
      return cmr_images
  
file_path: pykale/tests/prepdata/test_image_transform.py
imports: import os
  import matplotlib.figure
  import numpy
  import pytest
  from numpy import testing
  from kale.interpret.visualize import plot_multi_images
  from kale.loaddata.image_access import check_dicom_series_uid, dicom2arraylist, read_dicom_dir
  from kale.prepdata.image_transform import mask_img_stack, normalize_img_stack, reg_img_stack, rescale_img_stack
label_desc: Use image node_id 1 for calling a global function with example usage: images(download_path) and returns: cmr_images