Merge pull request #66 from fmi-faim/filter

filter: add dilate and feature filter

README.md

@@ -33,21 +33,29 @@ Configuration is managed in a `config.yml` file:
 
 ```yaml
 # Required
-file_selection: # criteria for file selection in case of multiple channels/slices per position
+
+# criteria for file selection in case of multiple channels/slices per position
+file_selection:
  channel: C01
-process: # choose method how to segment, filter, and sample the objects
- segment: threshold # choices: threshold, cellpose
- filter: [bounding_box, area, solidity, intensity]
- sample: centers # choices: centers, grid_overlap, dense_grid, object_centered_grid, region_centered_grid
 
-# Each subsequent section provides arguments to one of the methods defined in 'process'.
+# choose method how to segment, filter, and sample the objects
+process:
+ # segment methods: threshold, cellpose
+ segment: threshold
+ # filter methods: bounding_box, area, solidity, intensity
+ filter: [bounding_box, area, solidity, feature, dilate, intensity]
+ # sample methods: centers, grid_overlap, dense_grid,
+ # object_centered_grid, region_centered_grid
+ sample: centers
+
+# Each section below provides arguments to one of the methods set in 'process'.
 # Config sections for methods not selected above will be ignored.
 
 # segment
 threshold:
  threshold: 128
- include_holes: yes
- gaussian_sigma: 2.0 # default: 0.0 
+ include_holes: true
+ gaussian_sigma: 0.0 # default: 0.0
 
 # filter
 bounding_box:
@@ -61,13 +69,19 @@ area:
 solidity:
  min_solidity: 0.9
  max_solidity: 1.0
+feature:
+ feature: eccentricity
+ min_value: 0.0
+ max_value: 0.99
+dilate:
+ pixel_distance: 1.0
 intensity:
  target_channel: C03
  min_intensity: 128
 
 # sample
 dense_grid:
- binning_factor: 20 # default: 50
+ binning_factor: 50 # default: 50
 grid_overlap:
  mag_first_pass: 4
  mag_second_pass: 60

config.yml

@@ -14,7 +14,7 @@ process:
  # segment methods: threshold, cellpose
  segment: threshold
  # filter methods: bounding_box, area, solidity, intensity
- filter: [bounding_box, area, solidity, intensity]
+ filter: [bounding_box, area, solidity, feature, intensity, dilate]
  # sample methods: centers, grid_overlap, dense_grid,
  # object_centered_grid, region_centered_grid
  sample: centers
@@ -40,6 +40,12 @@ area:
 solidity:
  min_solidity: 0.9
  max_solidity: 1.0
+feature:
+ feature: eccentricity
+ min_value: 0.0
+ max_value: 0.99
+dilate:
+ pixel_distance: 1.0
 intensity:
  target_channel: C03
  min_intensity: 128

src/faim_wako_searchfirst/filter.py

@@ -15,6 +15,7 @@
 
 from numpy import ndarray
 from skimage.measure import regionprops
+from skimage.segmentation import expand_labels
 from tifffile import imread
 
 
@@ -40,6 +41,23 @@ def area(
  labels[labels == region.label] = 0
 
 
+def feature(
+ tif_file: Path,
+ labels: ndarray,
+ feature: str,
+ min_value: float,
+ max_value: float,
+):
+ """Filter objects in 'labels' by specified feature value range."""
+ regions = regionprops(labels)
+ if hasattr(regions[0], feature):
+ for region in regions:
+ if not min_value <= getattr(region, feature) <= max_value:
+ labels[labels == region.label] = 0
+ else:
+ raise AttributeError(f"'regionprops' object has no attribute '{feature}'")
+
+
 def solidity(
  tif_file: Path,
  labels: ndarray,
@@ -53,6 +71,15 @@ def solidity(
  labels[labels == region.label] = 0
 
 
+def dilate(
+ tif_file: Path,
+ labels: ndarray,
+ pixel_distance: float = 10.0,
+):
+ """Dilate objects by specified amount."""
+ labels[:] = expand_labels(label_image=labels, distance=pixel_distance)
+
+
 def intensity(
  tif_file: Path,
  labels: ndarray,

tests/test_filter.py

@@ -0,0 +1,42 @@
+# SPDX-FileCopyrightText: 2024 Friedrich Miescher Institute for Biomedical Research (FMI), Basel (Switzerland)
+#
+# SPDX-License-Identifier: MIT
+
+"""Test faim_wako_searchfirst.filter module."""
+
+from pathlib import Path
+
+import numpy as np
+import pytest
+from faim_wako_searchfirst.filter import dilate, feature
+from skimage.io import imread
+
+
+@pytest.fixture
+def _label_image():
+ return imread(Path("tests") / "resources" / "simple_labels.tif")
+
+
+def test_feature(_label_image: np.ndarray):
+ """Test generic feature filter."""
+ labels = _label_image.copy()
+ feature(
+ tif_file=None,
+ labels=labels,
+ feature="solidity",
+ min_value=0.9,
+ max_value=1.0,
+ )
+ assert np.unique(labels).tolist() == [0, 2, 3, 4]
+
+
+def test_dilate(_label_image: np.ndarray):
+ """Test oject dilation."""
+ labels = _label_image.copy()
+ assert np.sum(labels[labels == 1]) == 1353
+ dilate(
+ tif_file=None,
+ labels=labels,
+ pixel_distance=5.0,
+ )
+ assert np.sum(labels[labels == 1]) == 2803