code: def gaussian_gradient_magnitude(image, sigma = 5, voxelspacing = None, mask = slice(None)):
      r
      return _extract_feature(_extract_gaussian_gradient_magnitude, image, mask, sigma = sigma, voxelspacing = voxelspacing)
docs: r"""
      Computes the gradient magnitude (edge-detection) of the supplied image using gaussian
      derivates and returns the intensity values.
      
      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).
      sigma : number or sequence of numbers
          Standard deviation for Gaussian kernel. The standard deviations of the
          Gaussian filter are 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
      -------
      gaussian_gradient_magnitude : ndarray
          The gaussian gradient magnitude of the supplied image.