diff --git a/platipy/imaging/label/utils.py b/platipy/imaging/label/utils.py
index 35f8d64a..f3e8138f 100644
--- a/platipy/imaging/label/utils.py
+++ b/platipy/imaging/label/utils.py
@@ -168,8 +168,16 @@ def prime_encode_structure_list(structure_list):
 
         # Multiply with the encoded image
         prime_encoded_image = (
-            sitk.MaskNegated(prime_encoded_image, s_img_int)
-            + sitk.Mask(prime_encoded_image, s_img_int) * prime * s_img_int
+            sitk.Cast(
+                sitk.MaskNegated(
+                    sitk.Cast(prime_encoded_image, sitk.sitkUInt8),
+                    sitk.Cast(s_img_int, sitk.sitkUInt8),
+                ),
+                sitk.sitkUInt64,
+            )
+            + sitk.Mask(prime_encoded_image, sitk.Cast(s_img_int, sitk.sitkUInt8))
+            * prime
+            * s_img_int
         )
 
     return prime_encoded_image
@@ -262,7 +270,6 @@ def binary_decode_image(binary_encoded_img):
     num_nonzero_voxels = 1
 
     for power in range(32):
-
         # Calculate the region originally defined with this prime
         s_arr = np.bitwise_and(binary_encoded_arr, 2 ** (power + 1))
 
diff --git a/platipy/imaging/registration/deformable.py b/platipy/imaging/registration/deformable.py
index ced1d60c..39231c9d 100644
--- a/platipy/imaging/registration/deformable.py
+++ b/platipy/imaging/registration/deformable.py
@@ -65,7 +65,6 @@ def multiscale_demons(
     moving_images = []
 
     for resolution, smoothing_sigma in zip(resolution_staging, smoothing_sigmas):
-
         isotropic_voxel_size_mm = None
         shrink_factor = None
 
@@ -123,9 +122,7 @@ def multiscale_demons(
                 )
             initial_displacement_field.CopyInformation(fixed_image)
     else:
-        initial_displacement_field = sitk.Resample(
-            initial_displacement_field, fixed_image
-        )
+        initial_displacement_field = sitk.Resample(initial_displacement_field, fixed_image)
 
     # Run the registration.
     # Start at the top of the pyramid and work our way down.
@@ -139,9 +136,7 @@ def multiscale_demons(
         # we now apply the (total) transform to the moving image
         dvf_total = sitk.Resample(dvf_total, f_image)
 
-        tfm_total = sitk.DisplacementFieldTransform(
-            sitk.Cast(dvf_total, sitk.sitkVectorFloat64)
-        )
+        tfm_total = sitk.DisplacementFieldTransform(sitk.Cast(dvf_total, sitk.sitkVectorFloat64))
         m_image = sitk.Resample(m_image, tfm_total, interp_order)
 
         # set up iteration staging
@@ -258,7 +253,7 @@ def fast_symmetric_forces_demons_registration(
     regularisation_kernel_vox = np.array(regularisation_kernel_mm) / np.array(
         fixed_image.GetSpacing()
     )
-    print("regularisation_kernel_vox", regularisation_kernel_vox)
+
     registration_method.SetStandardDeviations(regularisation_kernel_vox.tolist())
 
     # This allows monitoring of the progress