diff --git a/.github/workflows/test_and_deploy.yml b/.github/workflows/test_and_deploy.yml
index c92c391..69c83ee 100644
--- a/.github/workflows/test_and_deploy.yml
+++ b/.github/workflows/test_and_deploy.yml
@@ -11,7 +11,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.8, 3.9, '3.10']
+        python-version: [3.9, '3.10', 3.11]
         platform: [ubuntu-latest] #, macos-latest]  # windows-latest broken for now
     steps:
       - uses: actions/checkout@v2
diff --git a/napari_pyclesperanto_assistant/__init__.py b/napari_pyclesperanto_assistant/__init__.py
index 70bbc58..a3b0ec1 100644
--- a/napari_pyclesperanto_assistant/__init__.py
+++ b/napari_pyclesperanto_assistant/__init__.py
@@ -2,5 +2,5 @@
 from ._convert_to_numpy import *
 from ._napari_cle_functions import *
 
-__version__ = "0.22.1"
+__version__ = "0.23.0"
 __common_alias__ = "ncle"
diff --git a/napari_pyclesperanto_assistant/_napari_cle_functions.py b/napari_pyclesperanto_assistant/_napari_cle_functions.py
index 8a5dcd6..763420f 100644
--- a/napari_pyclesperanto_assistant/_napari_cle_functions.py
+++ b/napari_pyclesperanto_assistant/_napari_cle_functions.py
@@ -1,4 +1,5 @@
-import pyclesperanto_prototype as cle
+import pyclesperanto as cle
+import pyclesperanto_prototype as clep
 from napari_tools_menu import register_function
 from napari_time_slicer import time_slicer
 
@@ -8,51 +9,51 @@ def _package_ncle(func):
         func.__doc__ = getattr(cle, func.__name__).__doc__
     return func
 
-@register_function(menu="Segmentation / labeling > Connected component labeling (clesperanto)")
+@register_function(menu="Segmentation / labeling > Connected component labeling (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def label(binary_image: "napari.types.LabelsData") -> "napari.types.LabelsData":
     """Connected component labeling using box-neighborhood (8-connected in 2D, 26-connected in 3D)"""
-    result = cle.connected_components_labeling_box(binary_image)
+    result = cle.connected_components_labeling(binary_image)
     return result
 
 
-@register_function(menu="Segmentation / labeling > Voronoi-Otsu-labeling (clesperanto)")
+@register_function(menu="Segmentation / labeling > Voronoi-Otsu-labeling (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def voronoi_otsu_labeling(image:"napari.types.ImageData", spot_sigma: float = 2, outline_sigma: float = 2) -> "napari.types.LabelsData":
     return cle.voronoi_otsu_labeling(image, spot_sigma=spot_sigma, outline_sigma=outline_sigma)
 
 
-@register_function(menu="Segmentation / labeling > Eroded-Otsu-labeling (clesperanto)")
+@register_function(menu="Segmentation / labeling > Eroded-Otsu-labeling (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def eroded_otsu_labeling(image:"napari.types.ImageData", number_of_erosions: int = 2, outline_sigma: float = 2) -> "napari.types.LabelsData":
     return cle.eroded_otsu_labeling(image, number_of_erosions=number_of_erosions, outline_sigma=outline_sigma)
 
 
-@register_function(menu="Segmentation / labeling > Gauss-Otsu-labeling (clesperanto)")
+@register_function(menu="Segmentation / labeling > Gauss-Otsu-labeling (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def gauss_otsu_labeling(image:"napari.types.ImageData", outline_sigma: float = 2) -> "napari.types.LabelsData":
     return cle.gauss_otsu_labeling(image, outline_sigma=outline_sigma)
 
 
-@register_function(menu="Filtering / background removal > Top-hat (box, clesperanto)")
+@register_function(menu="Filtering / background removal > Top-hat (box, pyclesperanto)")
 @time_slicer
 @_package_ncle
 def top_hat_box(image:"napari.types.ImageData", radius_x: int = 10, radius_y: int = 10, radius_z: int = 0) -> "napari.types.ImageData":
-    return cle.top_hat_box(image, radius_x=radius_x, radius_y=radius_y, radius_z=radius_z)
+    return cle.top_hat(image, radius_x=radius_x, radius_y=radius_y, radius_z=radius_z)
 
 
-@register_function(menu="Filtering / noise removal > Mean (box, clesperanto)")
+@register_function(menu="Filtering / noise removal > Mean (box, pyclesperanto)")
 @time_slicer
 @_package_ncle
 def mean_box(image:"napari.types.ImageData", radius_x: int = 10, radius_y: int = 10, radius_z: int = 0) -> "napari.types.ImageData":
-    return cle.mean_box(image, radius_x=radius_x, radius_y=radius_y, radius_z=radius_z)
+    return cle.mean(image, radius_x=radius_x, radius_y=radius_y, radius_z=radius_z)
 
 
-@register_function(menu="Filtering > Difference of Gaussian (clesperanto)")
+@register_function(menu="Filtering > Difference of Gaussian (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def difference_of_gaussian(image:"napari.types.ImageData",
@@ -65,21 +66,21 @@ def difference_of_gaussian(image:"napari.types.ImageData",
                                       )
 
 
-@register_function(menu="Filtering > Laplacian of Gaussian (clesperanto)")
+@register_function(menu="Filtering > Laplacian of Gaussian (pyclesperanto)")
 @time_slicer
 def laplacian_of_gaussian(image:"napari.types.ImageData",
                            sigma_x: float = 1, sigma_y: float = 1, sigma_z: float = 0,
                            ) -> "napari.types.ImageData":
     """Applies a Laplace-box filter to a Gaussian-blurred image of the original.
     That might be useful for edge detection"""
-    return cle.laplace_box(
+    return cle.laplace(
                            cle.gaussian_blur(image,
                                       sigma_x=sigma_x, sigma_y=sigma_y, sigma_z=sigma_z,
                            )
     )
 
 
-@register_function(menu="Filtering / noise removal > Gaussian (clesperanto)")
+@register_function(menu="Filtering / noise removal > Gaussian (pyclesperanto)")
 @time_slicer
 def gaussian_blur(image:"napari.types.ImageData",
                            sigma_x: float = 1, sigma_y: float = 1, sigma_z: float = 0,
@@ -89,267 +90,267 @@ def gaussian_blur(image:"napari.types.ImageData",
            )
 
 
-@register_function(menu="Filtering / background removal > Subtract Gaussian background (clesperanto)")
+@register_function(menu="Filtering / background removal > Subtract Gaussian background (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def subtract_gaussian_background(image:"napari.types.ImageData", sigma_x: float = 1, sigma_y: float = 1, sigma_z: float = 0) -> "napari.types.ImageData":
     return cle.subtract_gaussian_background(image, sigma_x=sigma_x, sigma_y=sigma_y, sigma_z=sigma_z)
 
 
-@register_function(menu="Filtering / background removal > Divide by Gaussian background (clesperanto)")
+@register_function(menu="Filtering / background removal > Divide by Gaussian background (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def divide_by_gaussian_background(image:"napari.types.ImageData", sigma_x: float = 1, sigma_y: float = 1, sigma_z: float = 0) -> "napari.types.ImageData":
     return cle.divide_by_gaussian_background(image, sigma_x=sigma_x, sigma_y=sigma_y, sigma_z=sigma_z)
 
 
-@register_function(menu="Filtering > Small Hessian eigenvalue (clesperanto)")
+@register_function(menu="Filtering > Small Hessian eigenvalue (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def small_hessian_eigenvalue(image:"napari.types.ImageData") -> "napari.types.ImageData":
     return cle.small_hessian_eigenvalue(image)
 
 
-@register_function(menu="Filtering > Large Hessian eigenvalue (clesperanto)")
+@register_function(menu="Filtering > Large Hessian eigenvalue (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def large_hessian_eigenvalue(image:"napari.types.ImageData") -> "napari.types.ImageData":
     return cle.large_hessian_eigenvalue(image)
 
 
-@register_function(menu="Filtering / edge enhancement > Standard deviation (box, clesperanto)")
+@register_function(menu="Filtering / edge enhancement > Standard deviation (box, pyclesperanto)")
 @time_slicer
 @_package_ncle
 def standard_deviation_box(image:"napari.types.ImageData", radius_x: int = 10, radius_y: int = 10, radius_z: int = 0) -> "napari.types.ImageData":
-    return cle.standard_deviation_box(image, radius_x=radius_x, radius_y=radius_y, radius_z=radius_z)
+    return cle.standard_deviation(image, radius_x=radius_x, radius_y=radius_y, radius_z=radius_z)
 
 
-@register_function(menu="Filtering / edge enhancement > Variance (box, clesperanto)")
+@register_function(menu="Filtering / edge enhancement > Variance (box, pyclesperanto)")
 @time_slicer
 @_package_ncle
 def variance_box(image:"napari.types.ImageData", radius_x: int = 10, radius_y: int = 10, radius_z: int = 0) -> "napari.types.ImageData":
-    return cle.variance_box(image, radius_x=radius_x, radius_y=radius_y, radius_z=radius_z)
+    return cle.variance(image, radius_x=radius_x, radius_y=radius_y, radius_z=radius_z)
 
 
-@register_function(menu="Segmentation post-processing > Exclude large labels (clesperanto)")
+@register_function(menu="Segmentation post-processing > Exclude large labels (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def exclude_large_labels(labels:"napari.types.LabelsData", minimum_size: float = 1) -> "napari.types.LabelsData":
     return cle.exclude_large_labels(labels, minimum_size=minimum_size)
 
 
-@register_function(menu="Segmentation post-processing > Exclude small labels (clesperanto)")
+@register_function(menu="Segmentation post-processing > Exclude small labels (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def exclude_small_labels(labels:"napari.types.LabelsData", maximum_size: float = 1) -> "napari.types.LabelsData":
     return cle.exclude_small_labels(labels, maximum_size=maximum_size)
 
 
-@register_function(menu="Segmentation post-processing > Exclude labels with map values out of range (clesperanto)")
+@register_function(menu="Segmentation post-processing > Exclude labels with map values out of range (pyclesperanto_prototype)")
 @time_slicer
 @_package_ncle
 def exclude_labels_with_map_values_out_of_range(values_map:"napari.types.ImageData", labels:"napari.types.LabelsData", minimum_value_range: float = 0, maximum_value_range: float=100) -> "napari.types.LabelsData":
-    return cle.exclude_labels_with_map_values_out_of_range(values_map, labels, minimum_value_range=minimum_value_range, maximum_value_range=maximum_value_range)
+    return clep.exclude_labels_with_map_values_out_of_range(values_map, labels, minimum_value_range=minimum_value_range, maximum_value_range=maximum_value_range)
 
 
-@register_function(menu="Segmentation post-processing > Exclude labels with map values within range (clesperanto)")
+@register_function(menu="Segmentation post-processing > Exclude labels with map values within range (pyclesperanto_prototype)")
 @time_slicer
 @_package_ncle
 def exclude_labels_with_map_values_within_range(values_map:"napari.types.ImageData", labels:"napari.types.LabelsData", minimum_value_range: float = 0, maximum_value_range: float=100) -> "napari.types.LabelsData":
-    return cle.exclude_labels_with_map_values_within_range(values_map, labels, minimum_value_range=minimum_value_range, maximum_value_range=maximum_value_range)
+    return clep.exclude_labels_with_map_values_within_range(values_map, labels, minimum_value_range=minimum_value_range, maximum_value_range=maximum_value_range)
 
-@register_function(menu="Segmentation post-processing > Extend labels via Voronoi (clesperanto)")
+@register_function(menu="Segmentation post-processing > Extend labels via Voronoi (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def extend_labeling_via_voronoi(labels:"napari.types.LabelsData") -> "napari.types.LabelsData":
     return cle.extend_labeling_via_voronoi(labels)
 
 
-@register_function(menu="Segmentation post-processing > Reduce labels to label edges (clesperanto)")
+@register_function(menu="Segmentation post-processing > Reduce labels to label edges (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def reduce_labels_to_label_edges(labels:"napari.types.LabelsData") -> "napari.types.LabelsData":
     return cle.reduce_labels_to_label_edges(labels)
 
 
-@register_function(menu="Segmentation post-processing > Reduce labels to centroids (clesperanto)")
+@register_function(menu="Segmentation post-processing > Reduce labels to centroids (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def reduce_labels_to_centroids(labels:"napari.types.LabelsData") -> "napari.types.LabelsData":
     return cle.reduce_labels_to_centroids(labels)
 
 
-@register_function(menu="Segmentation post-processing > Binary not (clesperanto)")
+@register_function(menu="Segmentation post-processing > Binary not (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def binary_not(labels:"napari.types.LabelsData") -> "napari.types.LabelsData":
     return cle.binary_not(labels)
 
 
-@register_function(menu="Segmentation post-processing > Binary OR / union (clesperanto)")
+@register_function(menu="Segmentation post-processing > Binary OR / union (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def binary_or(labels1:"napari.types.LabelsData", labels2:"napari.types.LabelsData") -> "napari.types.LabelsData":
     return cle.binary_or(labels1, labels2)
 
 
-@register_function(menu="Segmentation post-processing > Binary AND / intersection (clesperanto)")
+@register_function(menu="Segmentation post-processing > Binary AND / intersection (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def binary_and(labels1:"napari.types.LabelsData", labels2:"napari.types.LabelsData") -> "napari.types.LabelsData":
     return cle.binary_and(labels1, labels2)
 
 
-@register_function(menu="Segmentation post-processing > Binary subtract (clesperanto)")
+@register_function(menu="Segmentation post-processing > Binary subtract (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def binary_subtract(labels1:"napari.types.LabelsData", labels2:"napari.types.LabelsData") -> "napari.types.LabelsData":
     return cle.binary_subtract(labels1, labels2)
 
 
-@register_function(menu="Segmentation post-processing > Binary XOR (clesperanto)")
+@register_function(menu="Segmentation post-processing > Binary XOR (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def binary_xor(labels1:"napari.types.LabelsData", labels2:"napari.types.LabelsData") -> "napari.types.LabelsData":
     return cle.binary_xor(labels1, labels2)
 
 
-@register_function(menu="Measurement maps > Extension ratio map (clesperanto)")
+@register_function(menu="Measurement maps > Extension ratio map (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def extension_ratio_map(labels:"napari.types.LabelsData") -> "napari.types.ImageData":
     return cle.extension_ratio_map(labels)
 
 
-@register_function(menu="Measurement maps > Pixel count map (clesperanto)")
+@register_function(menu="Measurement maps > Pixel count map (pyclesperanto_prototype)")
 @time_slicer
 @_package_ncle
 def pixel_count_map(labels:"napari.types.LabelsData") -> "napari.types.ImageData":
     return cle.pixel_count_map(labels)
 
 
-@register_function(menu="Image math > Reciprocal (clesperanto)")
+@register_function(menu="Image math > Reciprocal (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def reciprocal(image:"napari.types.ImageData") -> "napari.types.ImageData":
     return cle.reciprocal(image)
 
 
-@register_function(menu="Image math > Absolute difference (clesperanto)")
+@register_function(menu="Image math > Absolute difference (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def absolute_difference(image1:"napari.types.ImageData", image2:"napari.types.ImageData") -> "napari.types.ImageData":
     return cle.absolute_difference(image1, image2)
 
 
-@register_function(menu="Image math > Squared difference (clesperanto)")
+@register_function(menu="Image math > Squared difference (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def squared_difference(image1:"napari.types.ImageData", image2:"napari.types.ImageData") -> "napari.types.ImageData":
     return cle.squared_difference(image1, image2)
 
 
-@register_function(menu="Segmentation post-processing > Smooth labels (clesperanto)", radius={"widget_type": "FloatSlider", "min": 0, "max":10}, auto_call=True)
+@register_function(menu="Segmentation post-processing > Smooth labels (pyclesperanto)", radius={"widget_type": "FloatSlider", "min": 0, "max":10}, auto_call=True)
 @time_slicer
 @_package_ncle
 def smooth_labels(labels:"napari.types.LabelsData", radius: float = 1) -> "napari.types.LabelsData":
     return cle.smooth_labels(labels, radius=radius)
 
 
-@register_function(menu="Segmentation post-processing > Merge touching labels with intensity along borders within range (clesperanto)",
+@register_function(menu="Segmentation post-processing > Merge touching labels with intensity along borders within range (pyclesperanto_prototype)",
                    minimum_intensity={"min": 0, "max":100000},
                    maximum_intensity={"min": 0, "max":100000},
                    auto_call=True)
 @time_slicer
 @_package_ncle
 def merge_labels_with_border_intensity_within_range(image:"napari.types.ImageData", labels:"napari.types.LabelsData", minimum_intensity: float = 0, maximum_intensity: float = 1000) -> "napari.types.LabelsData":
-    return cle.merge_labels_with_border_intensity_within_range(image,
+    return clep.merge_labels_with_border_intensity_within_range(image,
                                                                labels,
                                                                minimum_intensity=minimum_intensity,
                                                                maximum_intensity=maximum_intensity
                                                                )
 
 
-@register_function(menu="Segmentation post-processing > Merge touching labels (clesperanto)")
+@register_function(menu="Segmentation post-processing > Merge touching labels (pyclesperanto_prototype)")
 @time_slicer
 @_package_ncle
 def merge_touching_labels(labels:"napari.types.LabelsData") -> "napari.types.LabelsData":
-    return cle.merge_touching_labels(labels)
+    return clep.merge_touching_labels(labels)
 
 
-@register_function(menu="Segmentation post-processing > Dilate Labels (clesperanto)")
+@register_function(menu="Segmentation post-processing > Dilate Labels (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def dilate_labels(labels:"napari.types.LabelsData", radius: int = 1) -> "napari.types.LabelsData":
     return cle.dilate_labels(labels, radius=radius)
 
 
-@register_function(menu="Segmentation post-processing > Erode Labels (clesperanto)")
+@register_function(menu="Segmentation post-processing > Erode Labels (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def erode_labels(labels:"napari.types.LabelsData", radius: int = 1) -> "napari.types.LabelsData":
     return cle.erode_labels(labels, radius=radius)
 
 
-@register_function(menu="Segmentation post-processing > Opening Labels (clesperanto)")
+@register_function(menu="Segmentation post-processing > Opening Labels (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def opening_labels(labels:"napari.types.LabelsData", radius: int = 1) -> "napari.types.LabelsData":
     return cle.opening_labels(labels, radius=radius)
 
 
-@register_function(menu="Segmentation post-processing > Closing Labels (clesperanto)")
+@register_function(menu="Segmentation post-processing > Closing Labels (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def closing_labels(labels:"napari.types.LabelsData", radius: int = 1) -> "napari.types.LabelsData":
     return cle.closing_labels(labels, radius=radius)
 
 
-@register_function(menu="Transforms > Rotate (clesperanto)")
+@register_function(menu="Transforms > Rotate (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def rotate(image:"napari.types.ImageData", angle_around_x_in_degrees: float = 0, angle_around_y_in_degrees: float = 0, angle_around_z_in_degrees: float = 0, rotate_around_center:bool=True, linear_interpolation:bool=False, auto_size:bool=False) -> "napari.types.ImageData":
     return cle.rotate(image, angle_around_x_in_degrees=angle_around_x_in_degrees, angle_around_y_in_degrees=angle_around_y_in_degrees, angle_around_z_in_degrees=angle_around_z_in_degrees, rotate_around_center=rotate_around_center, linear_interpolation=linear_interpolation, auto_size=auto_size)
 
 
-@register_function(menu="Transforms > Scale (clesperanto)")
+@register_function(menu="Transforms > Scale (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def scale(image:"napari.types.ImageData", factor_x: float = 0, factor_y: float = 0, factor_z: float = 0, centered:bool=False, linear_interpolation:bool=True, auto_size:bool=False) -> "napari.types.ImageData":
     return cle.scale(image, factor_x=factor_x, factor_y=factor_y, factor_z=factor_z, centered=centered, linear_interpolation=linear_interpolation, auto_size=auto_size)
 
 
-@register_function(menu="Transforms > Translate (clesperanto)")
+@register_function(menu="Transforms > Translate (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def translate(image:"napari.types.ImageData", translate_x: float = 0, translate_y: float = 0, translate_z: float = 0, linear_interpolation:bool=True) -> "napari.types.ImageData":
     return cle.translate(image, translate_x=translate_x, translate_y=translate_y, translate_z=translate_z, linear_interpolation=linear_interpolation)
 
 
-@register_function(menu="Transforms > Rigid transform (clesperanto)")
+@register_function(menu="Transforms > Rigid transform (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def rigid_transform(image:"napari.types.ImageData", translate_x: float = 0, translate_y: float = 0, translate_z: float = 0, angle_around_x_in_degrees: float = 0, angle_around_y_in_degrees: float = 0, angle_around_z_in_degrees: float = 0, rotate_around_center:bool=True, linear_interpolation:bool=False, auto_size:bool=False) -> "napari.types.ImageData":
     return cle.rigid_transform(image, translate_x=translate_x, translate_y=translate_y, translate_z=translate_z, angle_around_x_in_degrees=angle_around_x_in_degrees, angle_around_y_in_degrees=angle_around_y_in_degrees, angle_around_z_in_degrees=angle_around_z_in_degrees, rotate_around_center=rotate_around_center, linear_interpolation=linear_interpolation, auto_size=auto_size)
 
 
-@register_function(menu="Transforms > Sub-stack (clesperanto)")
+@register_function(menu="Transforms > Sub-stack (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def sub_stack(image:"napari.types.ImageData", start_z:int = 0, end_z:int = 1) -> "napari.types.ImageData":
     return cle.sub_stack(image, start_z=start_z, end_z=end_z)
 
 
-@register_function(menu="Transforms > Reduce stack (clesperanto)")
+@register_function(menu="Transforms > Reduce stack (pyclesperanto)")
 @time_slicer
 @_package_ncle
 def reduce_stack(image:"napari.types.ImageData", reduction_factor:int = 2, offset:int = 0) -> "napari.types.ImageData":
     return cle.reduce_stack(image, reduction_factor=reduction_factor, offset=offset)
 
 
-@register_function(menu="Segmentation post-processing > Merge annotated touching labels (clesperanto)")
+@register_function(menu="Segmentation post-processing > Merge annotated touching labels (pyclesperanto_prototype)")
 @time_slicer
 @_package_ncle
 def merge_annotated_touching_labels(labels:"napari.types.LabelsData", binary_annotation: "napari.types.LabelsData") -> "napari.types.LabelsData":
-    return cle.merge_annotated_touching_labels(labels, binary_annotation)
+    return clep.merge_annotated_touching_labels(labels, binary_annotation)
 
diff --git a/requirements.txt b/requirements.txt
index 285b59f..1e13e05 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -3,7 +3,8 @@ pyopencl
 toolz
 scikit-image
 napari >=0.4.15
-pyclesperanto-prototype >=0.22.0
+pyclesperanto-prototype >=0.24.5
+pyclesperanto==0.13.4
 magicgui
 numpy!=1.19.4
 pyperclip
diff --git a/setup.py b/setup.py
index f53ad5a..b2cefba 100644
--- a/setup.py
+++ b/setup.py
@@ -31,7 +31,7 @@ def read(fname):
 #use_scm = {"write_to": "napari_pyclesperanto_assistant/_version.py"}
 setup(
     name="napari_pyclesperanto_assistant",
-    version="0.22.1",
+    version="0.23.0",
     author="Robert Haase, Talley Lambert",
     author_email="robert.haase@tu-dresden.de",
     description="GPU-accelerated image processing in napari using OpenCL",
@@ -41,7 +41,7 @@ def read(fname):
     url="https://github.com/clesperanto/napari_pyclesperanto_assistant",
     packages=find_packages(),
     include_package_data=True,
-    python_requires=">=3.6",
+    python_requires=">=3.9",
     install_requires=requirements,
     #use_scm_version=use_scm,
     setup_requires=["setuptools_scm"],
diff --git a/tox.ini b/tox.ini
index c3a88b1..3c491c8 100644
--- a/tox.ini
+++ b/tox.ini
@@ -1,12 +1,13 @@
 # For more information about tox, see https://tox.readthedocs.io/en/latest/
 [tox]
-envlist = py{38,39}-{linux}
+envlist = py{39,310,311}-{linux}
 #,macos,windows}
 
 [gh-actions]
 python =
-    3.8: py38
     3.9: py39
+    3.10: py310
+    3.11: py311
     
 [gh-actions:env]
 PLATFORM =