--- a
+++ b/ants/label/label_clusters.py
@@ -0,0 +1,53 @@
+
+ 
+
+__all__ = ['label_clusters']
+
+import ants
+from ants.internal import get_lib_fn, process_arguments
+from ants.decorators import image_method
+
+@image_method
+def label_clusters(image, min_cluster_size=50, min_thresh=1e-6, max_thresh=1, fully_connected=False):
+    """
+    This will give a unique ID to each connected 
+    component 1 through N of size > min_cluster_size
+
+    ANTsR function: `labelClusters`
+
+    Arguments
+    ---------
+    image : ANTsImage 
+        input image e.g. a statistical map
+    
+    min_cluster_size : integer  
+        throw away clusters smaller than this value
+    
+    min_thresh : scalar
+        threshold to a statistical map
+    
+    max_thresh : scalar
+        threshold to a statistical map
+    
+    fully_connected : boolean
+        boolean sets neighborhood connectivity pattern
+    
+    Returns
+    -------
+    ANTsImage
+
+    Example
+    -------
+    >>> import ants
+    >>> image = ants.image_read( ants.get_ants_data('r16') )
+    >>> timageFully = ants.label_clusters( image, 10, 128, 150, True )
+    >>> timageFace = ants.label_clusters( image, 10, 128, 150, False )
+    """
+    dim = image.dimension
+    clust = ants.threshold_image(image, min_thresh, max_thresh)
+    temp = int(fully_connected)
+    args = [dim, clust, clust, min_cluster_size, temp]
+    processed_args = process_arguments(args)
+    libfn = get_lib_fn('LabelClustersUniquely')
+    libfn(processed_args)
+    return clust