class_docstr: Implemented from https://stackoverflow.com/questions/31400769/bounding-box-of-numpy-array
  Removes all rows/columns/etc composed only of the provided values.
  
  mask_value: int
      Value to be cropped. Currently, only 0 supported.
  lead_data_group: str
      If provided, multiple data groups will be cropped according
      to the bounding box determined in the lead_data_group. Only
      applicable if different data_groups have the same shape. None
      by default, meaning that all data groups are cropped on an
      individual basis.
code: def execute(self, data_collection, return_array=False):
      super(CropValues, self).execute(data_collection, return_array)
  
      self.slice_boundaries = []
  
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 3 for calling the CropValues obj's underlying member method code with example usage: obj.execute(data_collection, return_array) without return types