diff --git a/python/cucim/src/cucim/skimage/feature/tests/test_corner.py b/python/cucim/src/cucim/skimage/feature/tests/test_corner.py
index d0d2a3930..0e6d5836b 100644
--- a/python/cucim/src/cucim/skimage/feature/tests/test_corner.py
+++ b/python/cucim/src/cucim/skimage/feature/tests/test_corner.py
@@ -252,6 +252,7 @@ def test_hessian_matrix_eigvals_3d(im3d, dtype):
     assert np.min(response2) < 0
     assert np.max(response0) > 0
 
+
 def _reference_eigvals_computation(S_elems):
     """Legacy eigenvalue implementation based on cp.linalg.eigvalsh."""
     matrices = _symmetric_image(S_elems)
diff --git a/python/cucim/src/cucim/skimage/filters/ridges.py b/python/cucim/src/cucim/skimage/filters/ridges.py
index d383c36ce..b6f379e52 100644
--- a/python/cucim/src/cucim/skimage/filters/ridges.py
+++ b/python/cucim/src/cucim/skimage/filters/ridges.py
@@ -481,8 +481,8 @@ def frangi(image, sigmas=range(1, 10, 2), scale_range=None,
         H = hessian_matrix(image, sigma, mode=mode, cval=cval,
                            use_gaussian_derivatives=True)
 
-        # using _symmetric_compute_eigenvalues rather than hessian_matrix_eigvals
-        # so we can directly sort by ascending magnitude
+        # Use _symmetric_compute_eigenvalues rather than
+        # hessian_matrix_eigvals so we can directly sort by ascending magnitude
         eigvals = _symmetric_compute_eigenvalues(
             H, sort='ascending', abs_sort=True
         )