def METHOD_NAME(out_dir, DT_dir, prediction_dir, mean_prefix):
	# Step 1: Get list of test names
	test_names = []
	for file in os.listdir(prediction_dir):
		test_names.append(get_prefix(file))
	# Step 2: Get original meshes from test distance transforms
	print("\n\nGetting original meshes from distance transforms...")
	DT_files = []
	for file in os.listdir(DT_dir):
		prefix = get_prefix(file)
		if prefix in test_names:
			DT_files.append(DT_dir + '/'+ file)
	orig_mesh_list = sorted(get_mesh_from_DT(DT_files, out_dir + "OriginalMeshes/"))
	# Step 3: Get predicted meshes from predicted particles
	print("\n\nGetting meshes from predicted particles...")
	particle_files = []
	for file in os.listdir(prediction_dir):
		particle_files.append(prediction_dir + file)
	template_mesh = mean_prefix + "_dense.vtk"
	template_points = mean_prefix + "_sparse.particles"
	pred_mesh_list = sorted(get_mesh_from_particles(particle_files, out_dir + "PredictedMeshes/", template_points, template_mesh))
	# Step 4: Get distance between original and predicted mesh
	print("\n\nGetting distance between original and predicted meshes...")
	orig_dist_mesh_list, pred_dist_mesh_list, avg_distance = surface_to_surface_distance(orig_mesh_list, pred_mesh_list, out_dir)
	print("Done.\n")
	return avg_distance