From 449e8420f67e3a4dcd42c74fc6b72c303a6a250a Mon Sep 17 00:00:00 2001
From: schlda00 <kai.schleicher@unibas.ch>
Date: Tue, 22 Apr 2025 14:22:08 +0200
Subject: [PATCH] Add and use function to measure shape features
---
2d_spots_in_fibers.py | 61 ++++++++++++++++++++++++++++++++++++++++++-
1 file changed, 60 insertions(+), 1 deletion(-)
diff --git a/2d_spots_in_fibers.py b/2d_spots_in_fibers.py
index 6daff6e..7df8f36 100644
--- a/2d_spots_in_fibers.py
+++ b/2d_spots_in_fibers.py
@@ -349,6 +349,59 @@ def measure_intensity_sum(imp, rm):
return label_id, sum_intensity
+def measure_shape_parameters(imp, rm):
+ """
+ Measure theraw integrated intensity for all rois in target imp.
+
+ Parameters
+ ----------
+ imp : ImagePlus
+ The image from which the intensity will be measured.
+ rm : RoiManager
+ The ROI Manager containing the regions of interest to be analyzed.
+
+ Returns
+ -------
+ label_id : list of str
+ A list of labels corresponding to each ROI.
+ area : list of int
+ A list of the areas for each ROI.
+ perimeter : list of int
+ A list of the perimeters for each ROI.
+ min_feret : list of int
+ A list of the min feret diameters for each ROI.
+
+ Notes
+ -----
+ The results are stored in a `ij.ResultsTable`,
+ from which the values are extracted.
+
+ Example
+ -------
+ >>> label_id, area, perimeter, min_feret = measure_shape_parameters(imp, roi_manager)
+ """
+
+ rt_ = ResultsTable()
+ options = M.FERET | M.AREA | M.PERIMETER
+ an = Analyzer (imp, options, rt_)
+ an.setPrecision(1)
+
+ label_id = []
+ area = []
+ perimeter = []
+ min_feret = []
+
+ for index, roi in enumerate(rm.getRoisAsArray()):
+ imp.setRoi(roi)
+ an.measure()
+ label_id.append(roi.getName())
+ area.append(int(rt_.getColumn("Area")[index]))
+ perimeter.append(int(rt_.getColumn("MinFeret")[index]))
+ min_feret.append(int(rt_.getColumn("Perim.")[index]))
+
+ return label_id, area, perimeter, min_feret
+
+
def add_results_to_resultstable(results_table, column, values):
"""Add values to the ResultsTable starting from row 0 of a given column.
@@ -451,6 +504,12 @@ dapi_binary = convert_to_binary(dapi_channel, threshold)
# detect spots and count them per fiber
results_table = ResultsTable()
+load_rois_from_zip(fiber_segmentation_roiset, rm)
+fiber_label_IDs, area, perimeter, min_feret = measure_shape_parameters(dapi_binary, rm)
+add_results_to_resultstable(results_table, "fiber label ID", fiber_label_IDs)
+add_results_to_resultstable(results_table, "Area", area)
+add_results_to_resultstable(results_table, "Perimeter", perimeter)
+add_results_to_resultstable(results_table, "Min. Feret", min_feret)
for index, channel in enumerate(processing_channels):
channel = int(channel)
quality_threshold = float(quality_thresholds[index])
@@ -462,7 +521,7 @@ for index, channel in enumerate(processing_channels):
dapi_negative_spots_binary = ImageCalculator.run(spots_binary_imp, dapi_positive_spots_binary, "Subtract create")
load_rois_from_zip(fiber_segmentation_roiset, rm)
- fiber_label_IDs, n_spots_per_fiber = measure_intensity_sum(spots_binary_imp, rm)
+ _, n_spots_per_fiber = measure_intensity_sum(spots_binary_imp, rm)
_, n_dapi_positive_spots_per_fiber = measure_intensity_sum(dapi_positive_spots_binary, rm)
_, n_dapi_negative_spots_per_fiber = measure_intensity_sum(dapi_negative_spots_binary, rm)
--
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