From d05bc41b3b5716754e29c4233fd5694fbccf8458 Mon Sep 17 00:00:00 2001
From: Kai Schleicher <kai.schleicher@unibas.ch>
Date: Mon, 12 Oct 2020 13:35:45 +0200
Subject: [PATCH] adds MHC pos detection
---
myosoft-imcf_identify_fibers.py | 146 ++++++++++++++++++++++++++++++++
1 file changed, 146 insertions(+)
diff --git a/myosoft-imcf_identify_fibers.py b/myosoft-imcf_identify_fibers.py
index 0f8390d..cca6074 100644
--- a/myosoft-imcf_identify_fibers.py
+++ b/myosoft-imcf_identify_fibers.py
@@ -40,6 +40,8 @@ import os
#@ Float (label="ROI expansion [microns]", value=1) enlarge
#@ String (visibility=MESSAGE, value="<html><b> channel positions in the hyperstack </b></html>") msg5
#@ Integer (label="Membrane staining channel number", style="slider", min=1, max=5, value=1) membrane_channel
+#@ Integer (label="Fiber staining (MHC) channel number (0=skip)", style="slider", min=0, max=5, value=3) fiber_channel
+#@ Integer (label="minimum fiber intensity (0=auto)", description="0 = automatic threshold detection", value=0) min_fiber_intensity
#@ Integer (label="sub-tiling to economize RAM", style="slider", min=1, max=8, value=4) tiling_factor
#@ ResultsTable rt
#@ RoiManager rm
@@ -143,6 +145,33 @@ def preprocess_membrane_channel(imp):
IJ.run(imp, "Convolve...", "text1=[-1.0 -1.0 -1.0 -1.0 -1.0\n-1.0 -1.0 -1.0 -1.0 0\n-1.0 -1.0 24.0 -1.0 -1.0\n-1.0 -1.0 -1.0 -1.0 -1.0\n-1.0 -1.0 -1.0 -1.0 0] normalize")
+def get_threshold_from_method(imp, channel, method):
+ """returns the threshold value of chosen IJ AutoThreshold method in desired channel
+
+ Parameters
+ ----------
+ imp : ImagePlus
+ the imp from which to get the threshold value
+ channel : integer
+ the channel in which to get the treshold
+ method : string
+ the AutoThreshold method to use
+
+ Returns
+ -------
+ list
+ the upper and the lower threshold (integer values)
+ """
+ imp.setC(channel) # starts at 1
+ ip = imp.getProcessor()
+ ip.setAutoThreshold(method + " dark")
+ lower_thr = ip.getMinThreshold()
+ upper_thr = ip.getMaxThreshold()
+ ip.resetThreshold()
+
+ return lower_thr, upper_thr
+
+
def apply_weka_model(model_path, imp, tiles_per_dim):
"""apply a pretrained WEKA model to an ImagePlus
@@ -261,6 +290,40 @@ def measure_in_all_rois( imp, channel, rm ):
rm.runCommand(imp,"Measure")
+def change_all_roi_color( rm, color ):
+ """change the color of all ROIs in the RoiManager
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ color : string
+ the desired color. e.g. "green", "red", "yellow", "magenta" ...
+ """
+ number_of_rois = rm.getCount()
+ for roi in range( number_of_rois ):
+ rm.select(roi)
+ rm.runCommand("Set Color", color)
+
+
+def change_subset_roi_color( rm, selected_rois, color ):
+ """change the color of selected ROIs in the RoiManager
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ selected_rois : array
+ ROIs in the RoiManager to change
+ color : string
+ the desired color. e.g. "green", "red", "yellow", "magenta" ...
+ """
+ rm.runCommand("Deselect")
+ rm.setSelectedIndexes(selected_rois)
+ rm.runCommand("Set Color", color)
+ rm.runCommand("Deselect")
+
+
def show_all_rois_on_image(rm, imp):
"""shows all ROIs in the ROiManager on imp
@@ -308,6 +371,76 @@ def enlarge_all_rois( amount_in_um, rm, pixel_size_in_um ):
rm.addRoi(enlarged_roi)
+def select_positive_fibers( imp, channel, rm, min_intensity ):
+ """For all ROIs in the RoiManager, select ROIs based on intensity measurement in given channel of imp.
+ See https://imagej.nih.gov/ij/developer/api/ij/process/ImageStatistics.html
+
+ Parameters
+ ----------
+ imp : ImagePlus
+ the imp on which to measure
+ channel : integer
+ the channel on which to measure. starts at 1
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ min_intensity : integer
+ the selection criterion (here: intensity threshold)
+
+ Returns
+ -------
+ array
+ a selection of ROIs which passed the selection criterion (are above the threshold)
+ """
+ imp.setC(channel)
+ all_rois = rm.getRoisAsArray()
+ selected_rois = []
+ for i, roi in enumerate(all_rois):
+ imp.setRoi(roi)
+ stats = imp.getStatistics()
+ if stats.mean > min_intensity:
+ selected_rois.append(i)
+
+ return selected_rois
+
+
+def preset_results_column( rt, column, value):
+ """pre-set all rows in given column of the IJ-ResultsTable with desired value
+
+ Parameters
+ ----------
+ rt : ResultsTable
+ a reference of the IJ-ResultsTable
+ column : string
+ the desired column. will be created if it does not yet exist
+ value : string or float or integer
+ the value to be set
+ """
+ for i in range( rt.size() ):
+ rt.setValue(column, i, value)
+
+ rt.show("Results")
+
+
+def add_results( rt, column, row, value ):
+ """adds a value in desired rows of a given column
+
+ Parameters
+ ----------
+ rt : ResultsTable
+ a reference of the IJ-ResultsTable
+ column : string
+ the column in which to add the values
+ row : array
+ the row numbers in which too add the values.
+ value : string or float or integer
+ the value to be set
+ """
+ for i in range( len( row ) ):
+ rt.setValue(column, row[i], value)
+
+ rt.show("Results")
+
+
def enhance_contrast( imp ):
"""use "Auto" Contrast & Brightness settings in each channel of imp
@@ -409,10 +542,23 @@ enlarge_all_rois( enlarge, rm, raw_image_calibration.pixelWidth )
renumber_rois(rm)
save_all_rois( rm, output_dir + "all_fiber_rois.zip" )
+# check for positive fibers
+if fiber_channel > 0:
+ if min_fiber_intensity == 0:
+ min_fiber_intensity = get_threshold_from_method(raw, fiber_channel, "Mean")[0]
+ IJ.log( "fiber intensity threshold: " + str(min_fiber_intensity) )
+
+ positive_fibers = select_positive_fibers( raw, fiber_channel, rm, min_fiber_intensity )
+ change_subset_roi_color(rm, positive_fibers, "magenta")
+ save_selected_rois( rm, positive_fibers, output_dir + "mhc_positive_fiber_rois.zip")
+ change_all_roi_color(rm, "blue")
+
# measure size & shape, save
IJ.run("Set Measurements...", "area perimeter shape feret's redirect=None decimal=4")
IJ.run("Clear Results", "")
measure_in_all_rois( raw, membrane_channel, rm )
+preset_results_column( rt, "MHC Positive Fibers (magenta)", "NO" )
+add_results( rt, "MHC Positive Fibers (magenta)", positive_fibers, "YES")
rt.save(output_dir + "all_fibers_results.csv")
# dress up the original image, save a overlay-png, present original to the user
--
GitLab