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2c_fibertyping.py 100755 → 100644
View file @ 8ad0e271
# this is a python rewrite of the original ijm published at # this is a python rewrite of the original ijm published at
# https://github.com/Hyojung-Choo/Myosoft/blob/Myosoft-hub/Scripts/central%20nuclei%20counter.ijm # https://github.com/Hyojung-Choo/Myosoft/blob/Myosoft-hub/Scripts/central%20nuclei%20counter.ijm
# IJ imports # IJ imports
...@@ -33,37 +33,47 @@ import os ...@@ -33,37 +33,47 @@ import os
def fix_ij_options(): def fix_ij_options():
"""put IJ into a defined state """Configure ImageJ (IJ) to a predefined state.
This function sets various options in ImageJ to ensure a consistent
environment for image processing tasks. It includes settings for appearance,
color management, binary image options, and file output format.
""" """
# disable inverting LUT # Disable inverting LUT (Look-Up Table) for images
IJ.run("Appearance...", " menu=0 16-bit=Automatic") IJ.run("Appearance...", " menu=0 16-bit=Automatic")
# set foreground color to be white, background black
# Set foreground color to be white and background color to be black, with red for selections
IJ.run("Colors...", "foreground=white background=black selection=red") IJ.run("Colors...", "foreground=white background=black selection=red")
# black BG for binary images and pad edges when eroding
# Enable black background for binary images and pad edges when eroding
IJ.run("Options...", "black pad") IJ.run("Options...", "black pad")
# set saving format to .txt files
# Set saving format to .txt files, saving both columns and rows
IJ.run("Input/Output...", "file=.txt save_column save_row") IJ.run("Input/Output...", "file=.txt save_column save_row")
# ============= DON’T MOVE UPWARDS =============
# set "Black Background" in "Binary Options" # Set "Black Background" option for binary operations
IJ.run("Options...", "black") IJ.run("Options...", "black")
# scale when converting = checked
# Enable scaling when converting images between types
IJ.run("Conversions...", "scale") IJ.run("Conversions...", "scale")
def fix_ij_dirs(path): def fix_ij_dirs(path):
"""use forward slashes in directory paths """Replace backslashes with forward slashes in directory paths.
This function takes a directory path obtained from a dialogue or script
parameter and returns a more robust path with forward slashes as separators.
Parameters Parameters
---------- ----------
path : string path : str
a directory path obtained from dialogue or script parameter A directory path
Returns Returns
------- -------
string str
a more robust path with forward slashes as separators A directory path with forward slashes as separators
""" """
fixed_path = str(path).replace("\\", "/") fixed_path = str(path).replace("\\", "/")
# fixed_path = fixed_path + "/" # fixed_path = fixed_path + "/"
...@@ -71,169 +81,239 @@ def fix_ij_dirs(path): ...@@ -71,169 +81,239 @@ def fix_ij_dirs(path):
def open_image_with_BF(path_to_file): def open_image_with_BF(path_to_file):
""" use Bio-Formats to opens the first image from an image file path """Open the first image from a file using Bio-Formats.
This function utilizes Bio-Formats to open an image file and returns
the first image contained within the file. The image is opened in
grayscale mode with autoscaling enabled.
Parameters Parameters
---------- ----------
path_to_file : string path_to_file : str
path to the image file The file path to the image file to be opened.
Returns Returns
------- -------
ImagePlus ImagePlus
the first imp stored in a give file The first image contained in the specified file.
""" """
# Create an ImporterOptions object for configuring the import process
options = ImporterOptions() options = ImporterOptions()
options.setColorMode(ImporterOptions.COLOR_MODE_GRAYSCALE) # Set the color mode to grayscale
options.setColorMode(ImporterOptions.COLOR_MODE_COMPOSITE )
# Enable autoscaling for the image
options.setAutoscale(True) options.setAutoscale(True)
# Set the file path for the image to be opened
options.setId(path_to_file) options.setId(path_to_file)
imps = BF.openImagePlus(options) # is an array of ImagePlus # Open the image(s) using Bio-Formats and store them in an array
imps = BF.openImagePlus(options)
# Return the first image in the array
return imps[0] return imps[0]
def fix_BF_czi_imagetitle(imp): def fix_BF_czi_imagetitle(imp):
image_title = os.path.basename( imp.getShortTitle() ) """
Fix the title of an image read using the bio-formats importer.
The title is modified to remove the ".czi" extension and replace
spaces with underscores.
Parameters
----------
imp : ij.ImagePlus
The image to be processed.
Returns
-------
str
The modified title of the image.
"""
# Get the short title of the image (without path)
image_title = os.path.basename(imp.getShortTitle())
# Remove the ".czi" extension
image_title = image_title.replace(".czi", "") image_title = image_title.replace(".czi", "")
# Replace spaces with underscores
image_title = image_title.replace(" ", "_") image_title = image_title.replace(" ", "_")
# Remove any double underscores
image_title = image_title.replace("_-_", "") image_title = image_title.replace("_-_", "")
# Remove any double underscores
image_title = image_title.replace("__", "_") image_title = image_title.replace("__", "_")
# Remove any "#" characters
image_title = image_title.replace("#", "Series") image_title = image_title.replace("#", "Series")
return image_title return image_title
def clear_ij_roi_manager(rm): def clear_ij_roi_manager(rm):
"""delete all ROIs from the RoiManager """
Clear all ROIs from the RoiManager.
Parameters Parameters
---------- ----------
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager a reference of the IJ-RoiManager
""" """
# Run the "reset" command in the RoiManager to clear all ROIs
rm.runCommand('reset') rm.runCommand('reset')
def get_threshold_from_method(imp, channel, method): def get_threshold_from_method(imp, channel, method):
"""returns the threshold value of chosen IJ AutoThreshold method in desired channel """Get the threshold value of chosen IJ AutoThreshold method in desired channel.
Parameters Parameters
---------- ----------
imp : ImagePlus imp : ImagePlus
the imp from which to get the threshold value The imp from which to get the threshold value.
channel : integer channel : int
the channel in which to get the treshold The channel in which to get the threshold.
method : string method : str
the AutoThreshold method to use The AutoThreshold method to use.
Returns Returns
------- -------
list list
the upper and the lower threshold (integer values) A list containing the upper and the lower threshold (integer values).
""" """
# Set the channel of the imp to the desired channel
imp.setC(channel) # starts at 1 imp.setC(channel) # starts at 1
# Get the processor of the imp
ip = imp.getProcessor() ip = imp.getProcessor()
# Set the AutoThreshold method to the desired method
ip.setAutoThreshold(method + " dark") ip.setAutoThreshold(method + " dark")
# Get the minimum and maximum threshold values
lower_thr = ip.getMinThreshold() lower_thr = ip.getMinThreshold()
upper_thr = ip.getMaxThreshold() upper_thr = ip.getMaxThreshold()
# Reset the threshold so that the imp is not affected by this function
ip.resetThreshold() ip.resetThreshold()
return lower_thr, upper_thr return [lower_thr, upper_thr]
def measure_in_all_rois( imp, channel, rm ): def measure_in_all_rois( imp, channel, rm ):
"""measures in all ROIS on a given channel of imp all parameters that are set in IJ "Set Measurements" """Measures in all ROIs on a given channel of imp all parameters that are set in IJ "Set Measurements".
This function takes an ImagePlus (imp), a channel (integer, starts at 1), and a RoiManager (rm) as
parameters. It then sets the channel of the imp to the desired channel, deselects all ROIs in the
RoiManager, and measures in all ROIs of the RoiManager on the channel of the imp. The parameters
that are measured are the ones that are set in IJ "Set Measurements".
Parameters Parameters
---------- ----------
imp : ImagePlus imp : ij.ImagePlus
the imp to measure on the imp to measure on
channel : integer channel : int
the channel to measure in. starts at 1. the channel to measure in. starts at 1.
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager a reference of the IJ-RoiManager
""" """
# Set the channel of the imp to the desired channel
imp.setC(channel) imp.setC(channel)
# Deselect all ROIs in the RoiManager
rm.runCommand(imp,"Deselect") rm.runCommand(imp,"Deselect")
# Measure in all ROIs of the RoiManager on the channel of the imp
rm.runCommand(imp,"Measure") rm.runCommand(imp,"Measure")
def change_all_roi_color( rm, color ): def change_all_roi_color(rm, color):
"""change the color of all ROIs in the RoiManager """
Change the color of all ROIs in the RoiManager.
Parameters Parameters
---------- ----------
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager A reference to the IJ-RoiManager.
color : string color : str
the desired color. e.g. "green", "red", "yellow", "magenta" ... The desired color, e.g., "green", "red", "yellow", "magenta".
Returns
-------
None
""" """
number_of_rois = rm.getCount() # Select all ROIs in the RoiManager
for roi in range( number_of_rois ): #rm.setSelectedIndexes(range(rm.getCount()))
rm.select(roi) rm.runCommand("Deselect")
rm.runCommand("Set Color", color) # Change the color of all ROIs to the desired color
rm.runCommand("Set Color", color)
# # Deselect all ROIs again to finalize changes
# rm.runCommand("Deselect")
def change_subset_roi_color( rm, selected_rois, color ): def change_subset_roi_color(rm, selected_rois, color):
"""change the color of selected ROIs in the RoiManager """
Change the color of selected ROIs in the RoiManager.
Parameters Parameters
---------- ----------
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager A reference to the IJ-RoiManager.
selected_rois : array selected_rois : list of int
ROIs in the RoiManager to change Indices of ROIs in the RoiManager to change.
color : string color : str
the desired color. e.g. "green", "red", "yellow", "magenta" ... The desired color, e.g., "green", "red", "yellow", "magenta", etc.
""" """
# Deselect all currently selected ROIs in the RoiManager
rm.runCommand("Deselect") rm.runCommand("Deselect")
# Select the specified ROIs by their indices
rm.setSelectedIndexes(selected_rois) rm.setSelectedIndexes(selected_rois)
# Change the color of the selected ROIs to the specified color
rm.runCommand("Set Color", color) rm.runCommand("Set Color", color)
# Deselect all ROIs again to finalize changes
rm.runCommand("Deselect") rm.runCommand("Deselect")
def show_all_rois_on_image(rm, imp): def show_all_rois_on_image(rm, imp):
"""shows all ROIs in the ROiManager on imp """
Display all ROIs on the given image using the ROI Manager.
Parameters Parameters
---------- ----------
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager A reference to the IJ-RoiManager.
imp : ImagePlus imp : ij.ImagePlus
the imp on which to show the ROIs The image on which to display the ROIs.
""" """
# Show the image in the ImageJ window
imp.show() imp.show()
rm.runCommand(imp,"Show All") # Use the ROI Manager to show all ROIs on the image
rm.runCommand(imp, "Show All")
def save_all_rois(rm, target): def save_all_rois(rm, target):
"""save all ROIs in the RoiManager as zip to target path """Save all ROIs in the RoiManager as a zip file to the given target path.
Parameters Parameters
---------- ----------
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager A reference to the IJ-RoiManager.
target : string target : str
the path in to store the ROIs. e.g. /my-images/resulting_rois.zip The file path in which to save the ROIs, e.g., /my-images/resulting_rois.zip
""" """
# Save all ROIs in the RoiManager to the given target path
rm.runCommand("Save", target) rm.runCommand("Save", target)
def save_selected_rois( rm, selected_rois, target ): def save_selected_rois(rm, selected_rois, target):
"""save selected ROIs in the RoiManager as zip to target path """
Save selected ROIs in the RoiManager as a zip file to the given target path.
Parameters Parameters
---------- ----------
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager A reference to the IJ-RoiManager.
selected_rois : array selected_rois : list of int
ROIs in the RoiManager to save Indices of ROIs in the RoiManager to save.
target : string target : str
the path in to store the ROIs. e.g. /my-images/resulting_rois_subset.zip The file path in which to save the ROIs, e.g., /my-images/resulting_rois_subset.zip
""" """
# Deselect all currently selected ROIs in the RoiManager to ensure a clean start
rm.runCommand("Deselect") rm.runCommand("Deselect")
# Select the specified ROIs by their indices
rm.setSelectedIndexes(selected_rois) rm.setSelectedIndexes(selected_rois)
# Save the selected ROIs to the given target path as a zip file
rm.runCommand("save selected", target) rm.runCommand("save selected", target)
# Deselect all ROIs again to finalize changes and maintain a clean state
rm.runCommand("Deselect") rm.runCommand("Deselect")
...@@ -243,19 +323,19 @@ def select_positive_fibers( imp, channel, rm, min_intensity ): ...@@ -243,19 +323,19 @@ def select_positive_fibers( imp, channel, rm, min_intensity ):
Parameters Parameters
---------- ----------
imp : ImagePlus imp : ij.ImagePlus
the imp on which to measure The ImagePlus on which to measure.
channel : integer channel : int
the channel on which to measure. starts at 1 The channel on which to measure. starts at 1.
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager A reference of the IJ-RoiManager.
min_intensity : integer min_intensity : int
the selection criterion (here: intensity threshold) The selection criterion (here: intensity threshold).
Returns Returns
------- -------
array list
a selection of ROIs which passed the selection criterion (are above the threshold) A selection of ROIs which passed the selection criterion (are above the threshold).
""" """
imp.setC(channel) imp.setC(channel)
all_rois = rm.getRoisAsArray() all_rois = rm.getRoisAsArray()
...@@ -266,33 +346,34 @@ def select_positive_fibers( imp, channel, rm, min_intensity ): ...@@ -266,33 +346,34 @@ def select_positive_fibers( imp, channel, rm, min_intensity ):
if stats.mean > min_intensity: if stats.mean > min_intensity:
selected_rois.append(i) selected_rois.append(i)
return selected_rois return selected_rois
def open_rois_from_zip( rm, path ): def open_rois_from_zip(rm, path):
"""open RoiManager ROIs from zip and adds them to the RoiManager """
Open ROIs from a zip file and add them to the RoiManager.
Parameters Parameters
---------- ----------
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager A reference to the IJ-RoiManager.
path : string path : str
path to the ROI zip file The file path to the ROI zip file.
""" """
rm.runCommand("Open", path) rm.runCommand("Open", path)
def preset_results_column( rt, column, value): def preset_results_column( rt, column, value):
"""pre-set all rows in given column of the IJ-ResultsTable with desired value """Pre-set all rows in given column of the IJ-ResultsTable with desired value.
Parameters Parameters
---------- ----------
rt : ResultsTable rt : ij.measure.ResultsTable
a reference of the IJ-ResultsTable A reference of the IJ-ResultsTable
column : string column : str
the desired column. will be created if it does not yet exist The desired column. Will be created if it does not yet exist
value : string or float or integer value : str or float or int
the value to be set The value to be set
""" """
for i in range( rt.size() ): for i in range( rt.size() ):
rt.setValue(column, i, value) rt.setValue(column, i, value)
...@@ -300,46 +381,52 @@ def preset_results_column( rt, column, value): ...@@ -300,46 +381,52 @@ def preset_results_column( rt, column, value):
rt.show("Results") rt.show("Results")
def add_results( rt, column, row, value ): def add_results(rt, column, row, value):
"""adds a value in desired rows of a given column """Add a value in specified rows of a given column.
Parameters Parameters
---------- ----------
rt : ResultsTable rt : ij.measure.ResultsTable
a reference of the IJ-ResultsTable A reference to the IJ-ResultsTable.
column : string column : str
the column in which to add the values The column in which to add the values.
row : array row : list of int
the row numbers in which too add the values. The row numbers in which to add the values.
value : string or float or integer value : str, float, or int
the value to be set The value to be set.
""" """
for i in range( len( row ) ): # Iterate over each row index in the row list
for i in range(len(row)):
# Set the specified value in the given column and row
rt.setValue(column, row[i], value) rt.setValue(column, row[i], value)
# Display the updated ResultsTable
rt.show("Results") rt.show("Results")
def enhance_contrast( imp ): def enhance_contrast(imp):
"""use "Auto" Contrast & Brightness settings in each channel of imp """Use "Auto" Contrast & Brightness settings in each channel of imp.
Parameters Parameters
---------- ----------
imp : ImagePlus imp : ij.ImagePlus
the imp on which to change C&B The imp on which to change C&B.
""" """
for channel in range( imp.getDimensions()[2] ): for channel in range(imp.getDimensions()[2]):
imp.setC(channel + 1) # IJ channels start at 1 imp.setC(channel + 1) # IJ channels start at 1
IJ.run(imp, "Enhance Contrast", "saturated=0.35") IJ.run(imp, "Enhance Contrast", "saturated=0.35")
def renumber_rois(rm): def renumber_rois(rm):
"""rename all ROIs in the RoiManager according to their number """Rename all ROIs in the RoiManager according to their number.
The RoiManager uses 0-based indexing, so the first ROI is at index 0.
This function renames each ROI with its index (starting from 1).
Parameters Parameters
---------- ----------
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager A reference to the IJ-RoiManager.
""" """
number_of_rois = rm.getCount() number_of_rois = rm.getCount()
for roi in range( number_of_rois ): for roi in range( number_of_rois ):
...@@ -347,18 +434,28 @@ def renumber_rois(rm): ...@@ -347,18 +434,28 @@ def renumber_rois(rm):
def setup_defined_ij(rm, rt): def setup_defined_ij(rm, rt):
"""set up a clean and defined Fiji user environment """Set up a clean and defined Fiji user environment.
This function configures the ImageJ environment to a predefined state by
resetting the RoiManager and ResultsTable, and clearing the IJ log.
Parameters Parameters
---------- ----------
rm : RoiManager rm : ij.plugin.frame.RoiManager
a reference of the IJ-RoiManager A reference to the IJ-RoiManager.
rt : ResultsTable rt : ij.measure.ResultsTable
a reference of the IJ-ResultsTable A reference to the IJ-ResultsTable.
""" """
# Configure IJ options to a predefined state
fix_ij_options() fix_ij_options()
# Reset the RoiManager to remove all existing ROIs
rm.runCommand('reset') rm.runCommand('reset')
# Reset the ResultsTable to clear all previous results
rt.reset() rt.reset()
# Clear the IJ log to ensure a fresh output window
IJ.log("\\Clear") IJ.log("\\Clear")
...@@ -368,6 +465,7 @@ setup_defined_ij(rm, rt) ...@@ -368,6 +465,7 @@ setup_defined_ij(rm, rt)
# open image using Bio-Formats # open image using Bio-Formats
path_to_image = fix_ij_dirs(path_to_image) path_to_image = fix_ij_dirs(path_to_image)
raw = open_image_with_BF(path_to_image) raw = open_image_with_BF(path_to_image)
raw.hide()
# get image info # get image info
raw_image_calibration = raw.getCalibration() raw_image_calibration = raw.getCalibration()
...@@ -383,7 +481,7 @@ if not os.path.exists( str(output_dir) ): ...@@ -383,7 +481,7 @@ if not os.path.exists( str(output_dir) ):
# open ROIS and show on image # open ROIS and show on image
open_rois_from_zip( rm, str(input_rois_path) ) open_rois_from_zip( rm, str(input_rois_path) )
change_all_roi_color(rm, "blue") change_all_roi_color(rm, "blue")
show_all_rois_on_image( rm, raw ) # show_all_rois_on_image( rm, raw )
# update the log for the user # update the log for the user
IJ.log( "Now working on " + str(raw_image_title) ) IJ.log( "Now working on " + str(raw_image_title) )
...@@ -412,7 +510,7 @@ for index, fiber_channel in enumerate(all_fiber_channels): ...@@ -412,7 +510,7 @@ for index, fiber_channel in enumerate(all_fiber_channels):
preset_results_column( rt, "channel " + str(fiber_channel) + " positive (" + roi_colors[index] + ")", "NO" ) preset_results_column( rt, "channel " + str(fiber_channel) + " positive (" + roi_colors[index] + ")", "NO" )
if all_min_fiber_intensities[index] == 0: if all_min_fiber_intensities[index] == 0:
all_min_fiber_intensities[index] = get_threshold_from_method(raw, fiber_channel, "Mean")[0] all_min_fiber_intensities[index] = get_threshold_from_method(raw, fiber_channel, "Mean")[0]
IJ.log( "fiber channel " + str(fiber_channel) + " intensity threshold: " + str(all_min_fiber_intensities[index]) ) IJ.log( "fiber channel " + str(fiber_channel) + " intensity threshold: " + str(all_min_fiber_intensities[index]) )
positive_fibers = select_positive_fibers( raw, fiber_channel, rm, all_min_fiber_intensities[index] ) positive_fibers = select_positive_fibers( raw, fiber_channel, rm, all_min_fiber_intensities[index] )
all_fiber_subsets[index] = positive_fibers all_fiber_subsets[index] = positive_fibers
if len(positive_fibers) > 0: if len(positive_fibers) > 0:
...@@ -432,29 +530,21 @@ positive_c2_c3 = list( set(all_fiber_subsets[1]).intersection(all_fiber_subsets[ ...@@ -432,29 +530,21 @@ positive_c2_c3 = list( set(all_fiber_subsets[1]).intersection(all_fiber_subsets[
positive_c1_c2_c3 = list( set(positive_c1_c2).intersection(all_fiber_subsets[2]) ) positive_c1_c2_c3 = list( set(positive_c1_c2).intersection(all_fiber_subsets[2]) )
# update ROI color & results table for double and triple positives # update ROI color & results table for double and triple positives
if len(positive_c1_c2) > 0: channels = [
preset_results_column( rt, "channel " + str(fiber_channel_1) + "," + str(fiber_channel_2) + " positive (magenta)", "NO" ) (positive_c1_c2, [fiber_channel_1, fiber_channel_2], "magenta"),
change_subset_roi_color(rm, positive_c1_c2, "magenta") (positive_c1_c3, [fiber_channel_1, fiber_channel_3], "yellow"),
save_selected_rois( rm, positive_c1_c2, output_dir + "/" + raw_image_title + "_positive_fiber_rois_c" + str(fiber_channel_1) + "_c" + str(fiber_channel_2) + ".zip") (positive_c2_c3, [fiber_channel_2, fiber_channel_3], "cyan"),
add_results( rt, "channel " + str(fiber_channel_1) + "," + str(fiber_channel_2) + " positive (magenta)", positive_c1_c2, "YES") (positive_c1_c2_c3, [fiber_channel_1, fiber_channel_2, fiber_channel_3], "white")
]
if len(positive_c1_c3) > 0:
preset_results_column( rt, "channel " + str(fiber_channel_1) + "," + str(fiber_channel_3) + " positive (yellow)", "NO" ) for positives, ch_nums, color in channels:
change_subset_roi_color(rm, positive_c1_c3, "yellow") if positives:
save_selected_rois( rm, positive_c1_c3, output_dir + "/" + raw_image_title + "_positive_fiber_rois_c" + str(fiber_channel_1) + "_c" + str(fiber_channel_3) + ".zip") ch_str = ",".join(map(str, ch_nums))
add_results( rt, "channel " + str(fiber_channel_1) + "," + str(fiber_channel_3) + " positive (yellow)", positive_c1_c3, "YES") color_label = "channel %s positive (%s)" % (ch_str, color)
preset_results_column(rt, color_label.replace(',', '-'), "NO")
if len(positive_c2_c3) > 0: change_subset_roi_color(rm, positives, color)
preset_results_column( rt, "channel " + str(fiber_channel_2) + "," + str(fiber_channel_3) + " positive (cyan)", "NO" ) save_selected_rois(rm, positives, "%s/%s_positive_fiber_rois_c%s.zip" % (output_dir, raw_image_title, '_c'.join(map(str, ch_nums))))
change_subset_roi_color(rm, positive_c2_c3, "cyan") add_results(rt, color_label.replace(',', '-'), positives, "YES")
save_selected_rois( rm, positive_c2_c3, output_dir + "/" + raw_image_title + "_positive_fiber_rois_c" + str(fiber_channel_2) + "_c" + str(fiber_channel_3) + ".zip")
add_results( rt, "channel " + str(fiber_channel_2) + "," + str(fiber_channel_3) + " positive (cyan)", positive_c2_c3, "YES")
if len(positive_c1_c2_c3) > 0:
preset_results_column( rt, "channel " + str(fiber_channel_1) + "," + str(fiber_channel_2) + "," + str(fiber_channel_3) + " positive(white)", "NO" )
change_subset_roi_color(rm, positive_c1_c2_c3, "white")
save_selected_rois( rm, positive_c1_c2_c3, output_dir + "/" + raw_image_title + "_positive_fiber_rois_c" + str(fiber_channel_1) + "_c" + str(fiber_channel_2) + "_c" + str(fiber_channel_3) + ".zip")
add_results( rt, "channel " + str(fiber_channel_1) + "," + str(fiber_channel_2) + "," + str(fiber_channel_3) + " positive(white)", positive_c1_c2_c3, "YES")
# save all results together # save all results together
save_all_rois( rm, output_dir + "/" + raw_image_title + "_all_fiber_type_rois_color-coded.zip" ) save_all_rois( rm, output_dir + "/" + raw_image_title + "_all_fiber_type_rois_color-coded.zip" )
...@@ -463,16 +553,16 @@ rt.save(output_dir + "/" + raw_image_title + "_fibertyping_results.csv") ...@@ -463,16 +553,16 @@ rt.save(output_dir + "/" + raw_image_title + "_fibertyping_results.csv")
# dress up the original image, save a overlay-png, present original to the user # dress up the original image, save a overlay-png, present original to the user
raw.show() raw.show()
show_all_rois_on_image( rm, raw ) show_all_rois_on_image( rm, raw )
raw.setDisplayMode(IJ.COMPOSITE) # raw.setDisplayMode(IJ.COMPOSITE)
enhance_contrast( raw ) enhance_contrast( raw )
IJ.run("From ROI Manager", "") # ROIs -> overlays so they show up in the saved png IJ.run("From ROI Manager", "") # ROIs -> overlays so they show up in the saved png
qc_duplicate = raw.duplicate() qc_duplicate = raw.duplicate()
IJ.saveAs(qc_duplicate, "PNG", output_dir + "/" + raw_image_title + "_fibertyping") IJ.saveAs(qc_duplicate, "PNG", output_dir + "/" + raw_image_title + "_fibertyping")
qc_duplicate.close() qc_duplicate.close()
wm.toFront( raw.getWindow() ) wm.toFront( raw.getWindow() )
IJ.run("Remove Overlay", "") # IJ.run("Remove Overlay", "")
raw.setDisplayMode(IJ.GRAYSCALE) # raw.setDisplayMode(IJ.GRAYSCALE)
show_all_rois_on_image( rm, raw ) # show_all_rois_on_image( rm, raw )
total_execution_time_min = (time.time() - execution_start_time) / 60.0 total_execution_time_min = (time.time() - execution_start_time) / 60.0
IJ.log("total time in minutes: " + str(total_execution_time_min)) IJ.log("total time in minutes: " + str(total_execution_time_min))
IJ.log( "~~ all done ~~" ) IJ.log( "~~ all done ~~" )
......
README.md
View file @ 8ad0e271
...@@ -11,9 +11,10 @@ Original code: <https://github.com/Hyojung-Choo/Myosoft/tree/Myosoft-hub> ...@@ -11,9 +11,10 @@ Original code: <https://github.com/Hyojung-Choo/Myosoft/tree/Myosoft-hub>
## [`1_identify_fibers.py`](1_identify_fibers.py) ## [`1_identify_fibers.py`](1_identify_fibers.py)
- Will identify all fibers based on the membrane staining using [Cellpose](https://github.com/MouseLand/cellpose) segmentation, filter them according to the morphometric gates and save the - Will identify all fibers based on the membrane staining using [Cellpose](https://github.com/MouseLand/cellpose)
corresponding ROIs. segmentation, filter them according to the morphometric gates and save the corresponding ROIs.
- Need to be installed ont the machine where the script is run. Follow [this guide](https://wiki.biozentrum.unibas.ch/display/IMCF/Cellpose+python+environment) to create the environment. - Need to be installed on the machine where the script is run. Follow
[this guide](https://wiki.biozentrum.unibas.ch/display/IMCF/Cellpose+python+environment) to create the environment. Please don't recreate the environment if it already exists!
- Will now also save the Cellpose segmentation as a binary so it can be edited - Will now also save the Cellpose segmentation as a binary so it can be edited
manually. If you do so, you need to run the "extended particle analyzer" manually. If you do so, you need to run the "extended particle analyzer"
manually as well to choose & apply the morphometric gates. manually as well to choose & apply the morphometric gates.
......