class_docstr: This class is responsible for the search of the appropriate files to use
  as input based on the constraints given in the config file.
code: def __init__(
      self,
      list_paths=(),
      list_contain=(),
      list_not_contain=(),
      regex_remove=(),
  ):
      self.path_to_search = list_paths
      self.filename_contains = list_contain
      self.filename_not_contains = list_not_contain
      self.filename_toremove_fromid = regex_remove
  
file_path: NiftyNet/niftynet/utilities/filename_matching.py
imports: from __future__ import absolute_import, print_function
  import os
  import re
  import six
  import niftynet.io.misc_io
  import tensorflow
label_desc: Use image node_id 1 to create a new KeywordsMatching object from inherited base classes: object with example: obj = KeywordsMatching(list_paths, list_contain, list_not_contain, regex_remove)