@@ -58,6 +58,7 @@
     np_unique,
     np_unique_withoutzero,
     np_volume,
+    np_voronoi_labels,
 )
 from TPTBox.core.vert_constants import (
     AFFINE,
@@ -1808,6 +1809,59 @@ def dilate_msk_(self, n_pixel: int = 5, labels: LABEL_REFERENCE = None, connecti
         """In-place variant of `dilate_msk`."""
         return self.dilate_msk(n_pixel=n_pixel, labels=labels, connectivity=connectivity, mask=mask, inplace=True, verbose=verbose,use_crop=use_crop,ignore_direction=ignore_direction)
 
+    def voronoi_labels(self, labels: LABEL_REFERENCE = None, max_distance: float | None = None, use_mm: bool = True, signed_background: bool = True, tie_to_zero: bool = True, inplace=False, verbose: logging = True) -> Self:
+        """Assigns every voxel the label of the nearest labelled region (a Voronoi partition).
+
+        Args:
+            labels (LABEL_REFERENCE, optional): Labels to partition by. Everything else is treated as
+                background. Defaults to None (all labels present in the segmentation).
+            max_distance (float | None, optional): Leave background voxels further than this from any
+                region at 0. In mm when `use_mm` is True, else in voxels. Defaults to None (no limit).
+            use_mm (bool, optional): If True, distances are measured in mm using this image's voxel
+                spacing, so the partition is correct on anisotropic images. If False, voxels are
+                treated as isotropic. Defaults to True.
+            signed_background (bool, optional): If True, voxels filled in from the background get the
+                negated label of their region, so the input mask stays recoverable as `out > 0`. The
+                returned NII then has a signed dtype. Defaults to True.
+            tie_to_zero (bool, optional): If True, voxels equidistant to two different regions are set
+                to 0 instead of being assigned to one of them. Defaults to True.
+            inplace (bool, optional): Whether to modify this NII in place or return a new object.
+                Defaults to False.
+            verbose (bool, optional): Whether to print a message. Defaults to True.
+
+        Returns:
+            NII: The partition, signed when `signed_background` is set.
+
+        Notes:
+            Runtime is independent of the number of labels (one Euclidean feature transform for the
+            whole volume), unlike `dilate_msk`.
+            Set `signed_background=False, tie_to_zero=False` and a `max_distance` for a plain,
+            unsigned expansion of the labels (`np_expand_labels`).
+
+        Examples:
+            >>> nii.voronoi_labels(max_distance=10)  # doctest: +SKIP
+            # every voxel within 1 cm of a labelled region takes its label
+        """
+        assert self.seg
+        log.print("voronoi labels", end="\r", verbose=verbose)
+        out = np_voronoi_labels(
+            self.get_seg_array(),
+            label_ref=labels,
+            max_distance=max_distance,
+            zoom=self.zoom if use_mm else None,
+            signed_background=signed_background,
+            tie_to_zero=tie_to_zero,
+        )
+        if not signed_background:
+            # keep the image dtype; the negated labels of a signed partition would not fit an unsigned one
+            out = out.astype(self.dtype)
+        log.print("Voronoi partition of", len(np_unique_withoutzero(np.abs(out))), "labels", verbose=verbose)
+        return self.set_array(out, inplace=inplace)
+
+    def voronoi_labels_(self, labels: LABEL_REFERENCE = None, max_distance: float | None = None, use_mm: bool = True, signed_background: bool = True, tie_to_zero: bool = True, verbose: logging = True) -> Self:
+        """In-place variant of `voronoi_labels`."""
+        return self.voronoi_labels(labels=labels, max_distance=max_distance, use_mm=use_mm, signed_background=signed_background, tie_to_zero=tie_to_zero, inplace=True, verbose=verbose)
+
 
     def fill_holes(self, labels: LABEL_REFERENCE = None, slice_wise_dim: int|str | None = None, verbose:logging=False, inplace=False,use_crop=True) -> Self:  # noqa: ARG002
         """Fills holes in segmentation.
 
@@ -694,5 +694,62 @@ def test_ethmoid_style_pipeline(self):
         self.assertAlmostEqual(vols[107] / (20 * 15 * 9), 1 / 3, places=2)
 
 
+class Test_voronoi_labels_nii(unittest.TestCase):
+    @staticmethod
+    def _two_points(zoom=(1.0, 1.0, 1.0)) -> NII:
+        arr = np.zeros((5, 1, 1), dtype=np.uint8)
+        arr[0] = 1
+        arr[4] = 2
+        return _make_nii(arr, zoom=zoom)
+
+    def test_signed_partition_and_tie(self):
+        out = self._two_points().voronoi_labels(verbose=False)
+        self.assertEqual(out.get_seg_array().ravel().tolist(), [1, -1, 0, -2, 2])
+        self.assertTrue(np.issubdtype(out.dtype, np.signedinteger))
+
+    def test_input_mask_is_recoverable(self):
+        nii = self._two_points()
+        out = nii.voronoi_labels(verbose=False)
+        np.testing.assert_array_equal((out.get_seg_array() > 0) * out.get_seg_array(), nii.get_seg_array())
+
+    def test_unsigned_keeps_the_image_dtype(self):
+        nii = self._two_points()
+        out = nii.voronoi_labels(signed_background=False, tie_to_zero=False, verbose=False)
+        self.assertEqual(out.dtype, nii.dtype)
+        self.assertEqual(out.get_seg_array().ravel().tolist(), [1, 1, 1, 2, 2])
+
+    def test_use_mm_scales_max_distance_with_zoom(self):
+        arr = np.zeros((11, 1, 1), dtype=np.uint8)
+        arr[0] = 1
+        nii = _make_nii(arr, zoom=(2.0, 1.0, 1.0))
+        in_mm = nii.voronoi_labels(max_distance=3, signed_background=False, verbose=False)
+        in_vox = nii.voronoi_labels(max_distance=3, use_mm=False, signed_background=False, verbose=False)
+        self.assertEqual(int(np.count_nonzero(in_mm.get_seg_array())), 2)
+        self.assertEqual(int(np.count_nonzero(in_vox.get_seg_array())), 4)
+
+    def test_labels_treats_the_rest_as_background(self):
+        out = self._two_points().voronoi_labels(labels=1, verbose=False)
+        self.assertEqual(out.get_seg_array().ravel().tolist(), [1, -1, -1, -1, -1])
+
+    def test_grid_is_preserved(self):
+        nii = self._two_points(zoom=(2.0, 1.0, 0.5))
+        out = nii.voronoi_labels(verbose=False)
+        self.assertTrue(out.assert_affine(nii, raise_error=False))
+        self.assertEqual(out.shape, nii.shape)
+
+    def test_inplace_variant(self):
+        nii = self._two_points()
+        out = nii.voronoi_labels_(verbose=False)
+        self.assertIs(out, nii)
+        self.assertEqual(nii.get_seg_array().ravel().tolist(), [1, -1, 0, -2, 2])
+
+    def test_matches_the_array_level_function(self):
+        from TPTBox.core.np_utils import np_voronoi_labels
+
+        nii = self._two_points(zoom=(1.5, 1.0, 1.0))
+        expected = np_voronoi_labels(nii.get_seg_array(), zoom=nii.zoom)
+        np.testing.assert_array_equal(nii.voronoi_labels(verbose=False).get_seg_array(), expected)
+
+
 if __name__ == "__main__":
     unittest.main()