code: def remove_clusters_by_size(clusters, min_size=0):
      ob = filter(lambda c: len(c) >= min_size, clusters)
  
      centroids = Streamlines()
      for cluster in ob:
          centroids.append(cluster.centroid)
  
      return centroids
  
imports: import logging
  import abc
  from itertools import combinations
  import numpy
  from dipy.core.optimize import Optimizer
  from dipy.align.bundlemin import _bundle_minimum_distance, _bundle_minimum_distance_asymmetric, distance_matrix_mdf
  from dipy.tracking.streamline import transform_streamlines, unlist_streamlines, center_streamlines, set_number_of_points, select_random_set_of_streamlines, length, Streamlines
  from dipy.segment.clustering import qbx_and_merge
  from dipy.core.geometry import compose_transformations, compose_matrix, decompose_matrix
  from time import time
label_desc: Use image node_id 5 for calling a global function with example usage: remove_clusters_by_size(clusters, min_size) and returns: centroids