Update for labeling components

flamingo_tools/segmentation/postprocessing.py

@@ -249,7 +249,7 @@ def erode_subset(
     Returns:
         The dataframe containing elements left after the erosion.
     """
-    print("initial length", len(table))
+    print(f"Initial length: {len(table)}")
     n_neighbors = 100
     for i in range(iterations):
         table = table[table[keyword] < threshold]
@@ -406,10 +406,12 @@ def components_sgn(
         min_cells = 20000
         threshold = threshold_erode if threshold_erode is not None else 40
 
-    print(f"Using threshold of {threshold} micrometer for eroding segmentation with keyword {keyword}.")
-
-    new_subset = erode_subset(table.copy(), iterations=iterations,
-                              threshold=threshold, min_cells=min_cells, keyword=keyword)
+    if iterations != 0:
+        print(f"Using threshold of {threshold} micrometer for eroding segmentation with keyword {keyword}.")
+        new_subset = erode_subset(table.copy(), iterations=iterations,
+                                  threshold=threshold, min_cells=min_cells, keyword=keyword)
+    else:
+        new_subset = table.copy()
 
     # create graph from coordinates of eroded subset
     centroids_subset = list(zip(new_subset["anchor_x"], new_subset["anchor_y"], new_subset["anchor_z"]))
@@ -486,41 +488,10 @@ def label_components_sgn(
     table.sort_values("label_id")
 
     component_labels = [0 for _ in range(len(table))]
+    table.loc[:, "component_labels"] = component_labels
     # be aware of 'label_id' of dataframe starting at 1
     for lab, comp in enumerate(components):
-        for comp_index in comp:
-            component_labels[comp_index - 1] = lab + 1
-
-    return component_labels
-
-
-def postprocess_sgn_seg(
-    table: pd.DataFrame,
-    min_size: int = 1000,
-    threshold_erode: Optional[float] = None,
-    min_component_length: int = 50,
-    max_edge_distance: float = 30,
-    iterations_erode: Optional[int] = None,
-) -> pd.DataFrame:
-    """Postprocessing SGN segmentation of cochlea.
-
-    Args:
-        table: Dataframe of segmentation table.
-        min_size: Minimal number of pixels for filtering small instances.
-        threshold_erode: Threshold of column value after erosion step with spatial statistics.
-        min_component_length: Minimal length for filtering out connected components.
-        max_edge_distance: Maximal distance in micrometer between points to create edges for connected components.
-        iterations_erode: Number of iterations for erosion, normally determined automatically.
-
-    Returns:
-        Dataframe with component labels.
-    """
-
-    comp_labels = label_components_sgn(table, min_size=min_size, threshold_erode=threshold_erode,
-                                       min_component_length=min_component_length,
-                                       max_edge_distance=max_edge_distance, iterations_erode=iterations_erode)
-
-    table.loc[:, "component_labels"] = comp_labels
+        table.loc[table["label_id"].isin(comp), "component_labels"] = lab + 1
 
     return table
 
@@ -583,37 +554,10 @@ def label_components_ihc(
     length_components, components = zip(*sorted(zip(length_components, components), reverse=True))
 
     component_labels = [0 for _ in range(len(table))]
+    table.loc[:, "component_labels"] = component_labels
     # be aware of 'label_id' of dataframe starting at 1
     for lab, comp in enumerate(components):
-        for comp_index in comp:
-            component_labels[comp_index - 1] = lab + 1
-
-    return component_labels
-
-
-def postprocess_ihc_seg(
-    table: pd.DataFrame,
-    min_size: int = 1000,
-    min_component_length: int = 50,
-    max_edge_distance: float = 30,
-) -> pd.DataFrame:
-    """Postprocessing IHC segmentation of cochlea.
-
-    Args:
-        table: Dataframe of segmentation table.
-        min_size: Minimal number of pixels for filtering small instances.
-        min_component_length: Minimal length for filtering out connected components.
-        max_edge_distance: Maximal distance in micrometer between points to create edges for connected components.
-
-    Returns:
-        Dataframe with component labels.
-    """
-
-    comp_labels = label_components_ihc(table, min_size=min_size,
-                                       min_component_length=min_component_length,
-                                       max_edge_distance=max_edge_distance)
-
-    table.loc[:, "component_labels"] = comp_labels
+        table.loc[table["label_id"].isin(comp), "component_labels"] = lab + 1
 
     return table
 

reproducibility/README.md

@@ -10,14 +10,14 @@ The extraction of blocks from a 3D volume is required for the creation of annota
 Usage:
 ```
 python repro_block_extraction.py --input <JSON-file> --output <out-dir>
-``` 
+```
 
-## Post-processing of SGN segmentation
+## Labeling components in the segmentation
 
-The post-processing of the SGN segmentation may involve the erosion of the segmentation to exclude artifacts, the variation of the minimal number of nodes within a component, or the minimal distance between nodes to consider them the same component.
+The labeling of the SGN segmentation may involve the erosion of the segmentation to exclude artifacts, the variation of the minimal number of nodes within a component, or the minimal distance between nodes to consider them the same component.
 
 Usage:
  ```
-python repro_postprocess_sgn_v1.py --input <JSON-file> --output <out-dir>
-``` 
+python repro_label_components.py --input <JSON-file> --output <out-dir>
+```
 

reproducibility/block_extraction/ChReef_MLR144R.json

@@ -6,6 +6,9 @@
 			"GFP",
 			"SGN_v2"
 		],
+		"segmentation_channel": "SGN_v2",
+		"type": "sgn",
+		"n_blocks": 6,
 		"crop_centers": [
 			[
 				1329,

reproducibility/block_extraction/ChReef_MLR145R.json

@@ -6,6 +6,9 @@
 			"GFP",
 			"SGN_v2"
 		],
+		"segmentation_channel": "SGN_v2",
+		"type": "sgn",
+		"n_blocks": 6,
 		"crop_centers": [
 			[
 				789,

reproducibility/block_extraction/ChReef_MLR155L.json

@@ -0,0 +1,53 @@
+[
+	{
+		"cochlea": "M_LR_000155_L",
+		"image_channel": [
+			"PV",
+			"GFP",
+			"SGN_v2"
+		],
+		"segmentation_channel": "SGN_v2",
+		"type": "sgn",
+		"n_blocks": 6,
+		"crop_centers": [
+			[
+				1725,
+				713,
+				482
+			],
+			[
+				1395,
+				810,
+				389
+			],
+			[
+				1070,
+				681,
+				454
+			],
+			[
+				1057,
+				677,
+				785
+			],
+			[
+				1121,
+				1002,
+				769
+			],
+			[
+				803,
+				1057,
+				690
+			]
+		],
+		"halo_size": [
+			256,
+			256,
+			50
+		],
+		"component_list": [
+			1
+		]
+	}
+]

reproducibility/block_extraction/ChReef_MLR155R.json

@@ -6,6 +6,9 @@
 			"GFP",
 			"SGN_v2"
 		],
+		"segmentation_channel": "SGN_v2",
+		"type": "sgn",
+		"n_blocks": 6,
 		"crop_centers": [
 			[
 				1634,

reproducibility/label_components/IHC_v4c_fig2.json

@@ -0,0 +1,26 @@
+[
+	{
+		"cochlea": "M_LR_000226_L",
+		"image_channel": "VGlut3",
+		"cell_type": "ihc",
+		"unet_version": "v4c"
+	},	
+	{
+		"cochlea": "M_LR_000226_R",
+		"image_channel": "VGlut3",
+		"cell_type": "ihc",
+		"unet_version": "v4c"
+	},
+	{
+		"cochlea": "M_LR_000227_L",
+		"image_channel": "VGlut3",
+		"cell_type": "ihc",
+		"unet_version": "v4c"
+	},
+	{
+		"cochlea": "M_LR_000227_R",
+		"image_channel": "VGlut3",
+		"cell_type": "ihc",
+		"unet_version": "v4c"
+	}
+]

reproducibility/label_components/SGN_v2_ChReef.json

@@ -0,0 +1,77 @@
+[
+	{
+		"cochlea": "M_LR_000143_L",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"max_edge_distance": 70,
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000144_L",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"max_edge_distance": 50,
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000145_L",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000153_L",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000155_L",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000189_L",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000143_R",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"max_edge_distance": 50,
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000144_R",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000145_R",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000153_R",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000155_R",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"unet_version": "v2"
+	},
+	{
+		"cochlea": "M_LR_000189_R",
+		"image_channel": "PV",
+		"cell_type": "sgn",
+		"unet_version": "v2"
+	}
+]