code: def _mask_filter_result(result, mask):
      """Return result after masking.
  
      Input masks are eroded so that mask areas in the original image don't
      affect values in the result.
      """
      if mask is not None:
          erosion_footprint = ndi.generate_binary_structure(
              mask.ndim, mask.ndim
          )
          mask = binary_erosion(mask, erosion_footprint, border_value=0)
          result *= mask
      return result
  
imports: import numpy
  from scipy import ndimage
  from scipy.ndimage import binary_erosion, convolve
  from .._shared.utils import _supported_float_type, check_nD
  from ..restoration.uft import laplacian
  from ..util.dtype import img_as_float
label_desc: Use image node_id 1 for calling a global function with example usage: _mask_filter_result(result, mask) and returns: result