code: def median(image, size = 5, voxelspacing = None, mask = slice(None)):
      
      return _extract_feature(_extract_median, image, mask, size = size, voxelspacing = voxelspacing)
docs: Computes the multi-dimensional median filter and returns the resulting values per
      voxel.
      
      Optionally a binary mask can be supplied to select the voxels for which the feature
      should be extracted.
      
      Parameters
      ----------
      image : array_like or list/tuple of array_like 
          A single image or a list/tuple of images (for multi-spectral case).
      size : number or sequence of numbers
          Size of the structuring element. Can be given given for each axis as a sequence,
          or as a single number, in which case it is equal for all axes. Note that the
          voxel spacing of the image is taken into account, the given values are treated
          as mm.
      voxelspacing : sequence of floats
          The side-length of each voxel.
      mask : array_like
          A binary mask for the image.
          
      Returns
      -------
      median : ndarray
          Multi-dimesnional median filtered version of the input images.