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Commit d05bc41b authored by Kai Schleicher's avatar Kai Schleicher
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adds MHC pos detection

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myosoft-imcf_identify_fibers.py
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......@@ -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
......
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