class_docstr: Performs skull-stripping using a model trained in DeepNeuro.
      
class_docstr_tok: ["Performs","skull-stripping","using","a","model","trained","in","DeepNeuro","."]
code: def initialize(self, data_collection):
      super(SkullStrip_Model, self).initialize(data_collection)
  
      if self.model is None:
          skullstripping_prediction_parameters = {
              "inputs": ["input_data"],
              "output_filename": self.output_filename,
              "batch_size": 50,
              "patch_overlaps": 3,
              "output_patch_shape": (56, 56, 6, 1),
              "save_to_file": False,
              "data_collection": data_collection,
              "verbose": self.verbose,
          }
  
          self.model = load_model_with_output(
              model_name="skullstrip_mri",
              outputs=[
                  PatchesInference(
                      **skullstripping_prediction_parameters
                  )
              ],
              postprocessors=[
                  BinarizeLabel(),
                  FillHoles(),
                  LargestComponents(),
              ],
          )
  
file_path: DeepNeuro/deepneuro/preprocessing/skullstrip.py
imports: import subprocess
  import os
  import numpy
  from deepneuro.preprocessing.preprocessor import Preprocessor
  from deepneuro.utilities.conversion import read_image_files, save_numpy_2_nifti
  from deepneuro.utilities.util import add_parameter, quotes
  from deepneuro.outputs.segmentation import PatchesInference
  from deepneuro.postprocessing.label import BinarizeLabel, FillHoles, LargestComponents
  from deepneuro.models.model import load_model_with_output
label_desc: Use image node_id 2 for calling the SkullStrip_Model obj's underlying member method code with example usage: obj.initialize(data_collection) without return types