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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def mask_distance(image, voxelspacing = None, mask = slice(None)):
 r""" Computes the distance of each point under the mask to the mask border taking the voxel-spacing into account. Note that this feature is independent of the actual image content, but depends solely the mask image. Therefore always a one-dimensional feature is returned, even if a multi-spectral image has been supplied. If no mask has been supplied, the distances to the image borders are returned. Parameters image : array_like or list/tuple of array_like A single image or a list/tuple of images (for multi-spectral case). voxelspacing : sequence of floats The side-length of each voxel. mask : array_like A binary mask for the image. Returns ------- mask_distance : ndarray Each voxels distance to the mask borders. """

    if type(image) == tuple or type(image) == list:
        image = image[0]
        
    return _extract_mask_distance(image, mask = mask, voxelspacing = voxelspacing)