Filter Images

brainglobe_registration/registration_widget.py

@@ -24,7 +24,7 @@
 from napari.utils.notifications import show_error
 from napari.viewer import Viewer
 from pytransform3d.rotations import active_matrix_from_angle
-from qtpy.QtWidgets import QPushButton, QTabWidget
+from qtpy.QtWidgets import QCheckBox, QPushButton, QTabWidget
 from skimage.segmentation import find_boundaries
 from skimage.transform import rescale
 
@@ -33,6 +33,7 @@
     adjust_napari_image_layer,
     calculate_rotated_bounding_box,
     check_atlas_installed,
+    filter_plane,
     find_layer_index,
     get_image_layer_names,
     open_parameter_file,
@@ -141,6 +142,9 @@
             self._on_default_file_selection_change
         )
 
+        self.filter_checkbox = QCheckBox("Filter Images")
+        self.filter_checkbox.setChecked(False)
+
         self.run_button = QPushButton("Run")
         self.run_button.clicked.connect(self._on_run_button_click)
         self.run_button.setEnabled(False)
@@ -176,6 +180,9 @@
         self.add_widget(
             self.parameters_tab, widget_title="Advanced Settings (optional)"
         )
+
+        self.add_widget(self.filter_checkbox, collapsible=False)
+
         self.add_widget(self.run_button, collapsible=False)
 
         self.layout().itemAt(1).widget().collapse(animate=False)
@@ -276,9 +283,22 @@
 
         current_atlas_slice = self._viewer.dims.current_step[0]
 
+        if self.filter_checkbox.isChecked():
+            atlas_layer = filter_plane(
+                self._atlas_data_layer.data[
+                    current_atlas_slice, :, :
+                ].compute()
+            )
+            moving_image_layer = filter_plane(self._moving_image.data)
+        else:
+            atlas_layer = self._atlas_data_layer.data[
+                current_atlas_slice, :, :
+            ]
+            moving_image_layer = self._moving_image.data
+
         result, parameters, registered_annotation_image = run_registration(
-            self._atlas_data_layer.data[current_atlas_slice, :, :],
-            self._moving_image.data,
+            atlas_layer,
+            moving_image_layer,
             self._atlas_annotations_layer.data[current_atlas_slice, :, :],
             self.transform_selections,
         )

brainglobe_registration/utils/utils.py

@@ -8,6 +8,8 @@
 from brainglobe_utils.qtpy.dialog import display_info
 from pytransform3d.rotations import active_matrix_from_angle
 from qtpy.QtWidgets import QWidget
+from scipy.ndimage import gaussian_filter
+from skimage import morphology
 
 
 def adjust_napari_image_layer(
@@ -175,3 +177,80 @@
             "brainglobe-atlasapi</a> or <a href='https://brainglobe.info/"
             "tutorials/manage-atlases-in-GUI.html'>brainrender-napari</a>",
         )
+
+
+def filter_plane(img_plane):
+    """
+    Apply a set of filter to the plane (typically to avoid overfitting details
+    in the image during registration)
+    The filter is composed of a despeckle filter using opening and a pseudo
+    flatfield filter
+
+    Originally from: [https://github.com/brainglobe/brainreg/blob/main
+    /brainreg/core/utils/preprocess.py]
+
+    Parameters
+    ----------
+    img_plane : np.array
+        A 2D array to filter
+
+    Returns
+    -------
+    np.array
+        Filtered image
+    """
+
+    img_plane = despeckle_by_opening(img_plane)
+    img_plane = pseudo_flatfield(img_plane)
+    return img_plane
+
+
+def despeckle_by_opening(img_plane, radius=2):
+    """
+    Despeckle the image plane using a grayscale opening operation
+
+    Originally from: [https://github.com/brainglobe/brainreg/blob/main
+    /brainreg/core/utils/preprocess.py]
+
+    Parameters
+    ----------
+    img_plane : np.array
+        The image to filter
+
+    radius: int
+        The radius of the opening kernel
+
+    Returns
+    -------
+    np.array
+        The despeckled image
+    """
+    kernel = morphology.disk(radius)
+    morphology.opening(img_plane, out=img_plane, footprint=kernel)
+    return img_plane
+
+
+def pseudo_flatfield(img_plane, sigma=5):
+    """
+    Pseudo flat field filter implementation using a de-trending by a
+    heavily gaussian filtered copy of the image.
+
+    Originally from: [https://github.com/brainglobe/brainreg/blob/main
+    /brainreg/core/utils/preprocess.py]
+
+    Parameters
+    ----------
+    img_plane : np.array
+        The image to filter
+
+    sigma : int
+        The sigma of the gaussian filter applied to the
+        image used for de-trending
+
+    Returns
+    -------
+    np.array
+        The pseudo flat field filtered image
+    """
+    filtered_img = gaussian_filter(img_plane, sigma)
+    return img_plane / (filtered_img + 1)