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ZFVascQuant_GUI_23052022.ijm
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/* GUI for zebrafish vasculature analysis
* Author: Elisabeth Kugler 2020
* contact: [email protected]
BSD 3-Clause License
Copyright (c) [2020], [Elisabeth C. Kugler, The University of Sheffield, United Kingdom]
All rights reserved.
// Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
// 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
// 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
// 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
* USE:
* hit run
* select which steps should be performed and whether parameters need to be changed
* select input folder (path to .czi files)
* select output folder (path for .tiff and MIPs)
* when Macro is done - popup window will say "Macro is finished."
* contact: [email protected]
* update 17.10.2020
* line 397 deselection of pointROI for TH/density/surface
* minor GUI changes to make it more intuitive
* closing edge tiff
* line 563 "TH_template" to "template"
* update 26.10.2020
* correct histogram count [allow 0 or 255 to be vascular; whichever is smaller]
* update 02.12.2020
* FScale over-write issue; write selected input and output folder into Log;
* only print the steps that were selected into log
*
* more user feedback needed to decide whether to write MIPs into seperate folder;
* ToDo Mac vs windows - Mac doesn't show "input folder" etc;
* update 15.08.2021 (Thanks to Nick Condon - Github comments)
* file name input with and without space
* line 197 - falsely included link to github
*
* update 19.01.2022 (Thanks to Guy Malkinson - pers comm)
* ROI was required for segmentation > included option to run without;
* solved issue with downsampling after segmentation without ROI
* 512x512 (x,y) downsampling was hard-coded > needs to be made user input
*
* update 23.05.2022 (Thanks to Elysse Morris - pers comm)
* > change path = THDir for intersample reg to "path = path"
* > change calling of files for MorpholibJ - workaround to rename images rather than calling vars
* based on: https://forum.image.sc/t/morpholibj-intensity-measurements-input-not-valid/49953/3
*/
// GUI for selection of steps
Dialog.create("ZVQ - Zebrafish Vascular Quantification");
// parameters / choices
choices = newArray("No", "Yes");
singleMulti = newArray("Single-colour", "Dual-Colour");
// czi to tiff conversion
Dialog.addChoice("(1) Czi to tiff conversion:", choices);
Dialog.addChoice("Single- or Multiple Channels:", singleMulti);
// Dialog.addMessage("(Check output Vasc (C=1) and NonVasc (C=0) are correct.)");
// Linear Stack Alignment using SIFT
Dialog.addChoice("(2) Motion Correction:", choices);
// Tubeness Filter
Dialog.addChoice("(3) Tubular Filtering for Vessel Enhancement:", choices);
Dialog.addNumber("Sigma Size [um]:", 10.6848); // empirical measure of optimum pending
// Segmentation and Vascular Volume Measurement
Dialog.addChoice("(4) Segmentation >> vascular volume, surface, and density:", choices);
Dialog.addChoice("'RoiSet.zip' * exists:", choices);
Dialog.addChoice("Do you want to perform downsampling?:", choices)
// Inter-sample registration
Dialog.addChoice("(5) Inter-sample registration:", choices);
Dialog.addChoice("Template exists ('template' should be in folder 'TH'; other files to start with 'TH'):", choices);
// Intra-sample symmetry
Dialog.addChoice("(6) Intra-sample symmetry ('RoiSetLine.zip' * should be in the same folder):", choices);
Dialog.addChoice("Are the data registered (provide 'TemplateLineROI.roi' *)?:", choices);
// Vasculature Quantification
Dialog.addChoice("(7) Vasculature Quantification >> length, branching points, diameter:", choices);
Dialog.addChoice("Are the data downsamples?:", choices);
Dialog.addChoice("Are the data registered (provide 'TemplateROI.roi' *)?:", choices);
Dialog.addMessage("Manuscript: Kugler et al., 2022; Development https://doi.org/10.1242/dev.199720");
Dialog.addMessage("GitHub: https://github.com/ElisabethKugler/ZFVascularQuantification");
Dialog.addMessage("Contact: kugler.elisabeth[at]gmail.com");
Dialog.addMessage("* case-sensitive");
// create dialog
Dialog.show();
///// parse choices and input /////
// czi to tiff conversion
cziConv = Dialog.getChoice();
Colours = Dialog.getChoice();
// Motion Correction
MC = Dialog.getChoice();
MCScale = 8; // Steps per Scale Octave (4-8 recommended)
imgSize = 1920; // Image size
MCDescr = 8; // Feature Descriptor Size (4-8 recommended)
MCCtN = 0.98; // Feature closest-to-next ratio (0.92-0.98 recommended)
MCError = 10; // Maximal Alignment Error Consensus Filter (3-10px recommended)
// Tubeness filter
TF = Dialog.getChoice();
TFScale = Dialog.getNumber();
// Segmentation and Vascular Volume Measurement
TH = Dialog.getChoice();
THROIs = Dialog.getChoice();
DS = Dialog.getChoice();
// Inter-sample registration
InterSReg = Dialog.getChoice();
regTemplate = Dialog.getChoice();
// Intra-sample symmetry
IntraSym = Dialog.getChoice();
RegForSym = Dialog.getChoice();
// Vasculature Quantification
VascQ = Dialog.getChoice();
downSampled = Dialog.getChoice();
RegForQuant = Dialog.getChoice();
path = getDirectory("Input Folder");
filelist = getFileList(path);
print("Selected input folder: " + path);
// this is where we set foreground and background colour
setForegroundColor(255, 255, 255);
setBackgroundColor(255, 255, 255);
// Calling individual steps and parsing parameter input
///// czi to tiff conversion /////
if (cziConv==choices[1]){
print("Running .czi to .tiff conversion");
VascDir = path + "/VascTiff/";
File.makeDirectory(VascDir);
print("Output folder: " + VascDir);
filelistTiff = getFileList(path);
if (Colours==singleMulti[0]) { //single colour
for (i=0; i< filelistTiff.length; i++) {
if (endsWith(filelistTiff[i], ".czi")) {
// Import czi with Bioformater
"Bio-Formats Importer", "open=[" + path + filelist[i] + "] autoscale color_mode=Default split_channels view=Hyperstack stack_order=XYCZT"
// MIP with Contrast Enhancement
run("Z Project...", "projection=[Max Intensity]");
run("Color Balance...");
run("Enhance Contrast", "saturated=0.35");
run("Enhance Contrast", "saturated=0.35");
saveAs("Jpeg", VascDir + "MAX_" + filelistTiff[i]);
run("Close");
// Save as Tiff Stack
selectWindow(filelistTiff[i]);
saveAs("Tiff", VascDir + filelistTiff[i]);
run("Close");
}
}
}else{ // multiple colours
NonVascDir = path + "/NonVascTiff/"; // folder for non-vascular output needed
File.makeDirectory(NonVascDir);
print("Running double-channel .czi to .tiff conversion"); // need to split channels .. save vascular in correct folder -- add at later time-point
for (i=0; i< filelist.length; i++) {
if (endsWith(filelist[i], ".czi")) {
// czi import using Bioformats with splitting channels so they can be saved individually (ie vascular and non-vascular)
run("Bio-Formats Importer", "open=" + path + filelist[i] + " autoscale color_mode=Default split_channels view=Hyperstack stack_order=XYCZT");
// Save as tiff stack
selectWindow(filelist[i] + " - C=0"); // green
saveAs("Tiff", NonVascDir + filelist[i]);
run("Z Project...", "projection=[Max Intensity]");
run("Color Balance...");
run("Enhance Contrast", "saturated=0.35");
run("Enhance Contrast", "saturated=0.35");
saveAs("Jpeg", path + "MAX_" + filelist[i]);
// selectWindow(filelist[i]);
close();
selectWindow(filelist[i] + " - C=1"); // red
saveAs("Tiff", VascDir + filelist[i]);
run("Z Project...", "projection=[Max Intensity]");
saveAs("Jpeg", path + "MAX_" + filelist[i]);
close();
close();
}
}
}
while(nImages>0){ // close all windows
selectImage(nImages);
close();
}
} // end czi-to-tiff conversion
///// LINEAR STACK ALIGNMENT USING SIFT
// aka Motion Correction using Scale Invariant Feature Transformation
if (MC==choices[1]){
print("Running Motion Correction.");
// input and output path
if(cziConv==choices[1]){
print("Opening images from .tiff folder.");
path = VascDir;
filelistMC = getFileList(path);
}else{
filelistMC = getFileList(path);
}
SIFTDir = path + "/SIFT/";
File.makeDirectory(SIFTDir);
print("Output folder: " + SIFTDir);
for (i=0; i< filelistMC.length; i++) {
if (endsWith(filelistMC[i], ".tif")) {
open(path + filelistMC[i]);
selectWindow(filelistMC[i]);
//get image properties
getDimensions(width, height, channels, slices, frames);
preChannels = channels;
preSlices = slices;
preFrames = frames;
// get voxel properties
getPixelSize(unit,pixelWidth,pixelHeight,voxelDepth);
prePixelWidth =pixelWidth;
prePixelHeight = pixelHeight;
preVoxelDepth = voxelDepth;
// Intrastack Linear Stack Alignment using SIFT algorithm
run("Linear Stack Alignment with SIFT", "initial_gaussian_blur=1.60 steps_per_scale_octave=" + MCScale + " minimum_image_size=64 maximum_image_size=" + imgSize + " feature_descriptor_size=8 feature_descriptor_orientation_bins=" + MCDescr + " closest/next_closest_ratio=" + MCCtN + " maximal_alignment_error=" + MCError + " inlier_ratio=0.05 expected_transformation=Rigid interpolate");
// re-set original image values
run("Properties...", "channels=" + preChannels + " slices=" + preSlices + " frames=" + preFrames +" unit=µm pixel_width=" + prePixelWidth + " pixel_height=" + prePixelHeight + " voxel_depth=" + preVoxelDepth);
// get MIP of SIFT-aligned stack
run("Z Project...", "projection=[Max Intensity]");
saveAs("PNG", SIFTDir + "MAX_SIFTAligned_" + filelistMC[i]);
run("Close");
// Save SIFt-aligned stack as tiff stack
saveAs("Tiff", SIFTDir + "SIFTAligned_" + filelistMC[i]);
close();
}
}
// close();
while(nImages>0){ // close all windows
selectImage(nImages);
close();
}
} // end SIFT
///// TUBULAR FILTERING aka SATO ENHANCEMENT SECTION
if (TF==choices[1]){
print("Opening images for vascular enhancement.");
if(cziConv==choices[1]){ // yes czi con
if(MC==choices[1]){ // yes MC
path = SIFTDir;
filelistTF = getFileList(path);
}else{ // no MC
path = VascDir;
filelistTF = getFileList(path);
}
}else{ // no czi conv
if(MC==choices[1]){ // yes MC
path = SIFTDir;
filelistTF = getFileList(path);
}else{ // no MC
filelistTF = getFileList(path);
}
}
print("Running Vessel Enhancement.");
// Create output folders
TFDir = path + "/TF/"; // output folder
File.makeDirectory(TFDir); // make output folder
TFMIPDir = path + "/TF/MIP/"; // output folder
File.makeDirectory(TFMIPDir);
print("Output folder for enhancement (TF): " + TFDir);
// open images for TF
for (i=0; i< filelistTF.length; i++) {
if (endsWith(filelistTF[i], ".tif")) { // input needs to be .tiff files
open(path + filelistTF[i]);
selectWindow(filelistTF[i]);
//get image properties
getDimensions(width, height, channels, slices, frames);
preChannels = channels;
preSlices = slices;
preFrames = frames;
// get voxel properties
getPixelSize(unit,pixelWidth,pixelHeight,voxelDepth);
prePixelWidth =pixelWidth;
prePixelHeight = pixelHeight;
preVoxelDepth = voxelDepth;
// Run Plugins > Analyze > Tubeness Filter (Frangi Vessel Enhancement Implementation)
run("Tubeness", "sigma=" + TFScale); // scale size to be changed depending on data
// re-set original image values
run("Properties...", "channels=" + preChannels + " slices=" + preSlices + " frames=" + preFrames +" unit=µm pixel_width=" + prePixelWidth + " pixel_height=" + prePixelHeight + " voxel_depth=" + preVoxelDepth);
// get MIP of vessel enhanced stack and save it
run("Z Project...", "projection=[Max Intensity]");
saveAs("PNG", TFMIPDir + "MAX_TF_" + filelistTF[i]);
run("Close");
// Save enhanced stack as tiff stack
saveAs("Tiff", TFDir + "TF_" + filelistTF[i]);
close();
}
}
while(nImages>0){ // close all windows
selectImage(nImages);
close();
}
} // end TF aka Sato enhancement
///// SEGMENTATION and Vascular Volume Measurement
if (TH==choices[1]){ // yes TH
print("Running Segmentation and Volume Measurement.");
if(cziConv==choices[1]){ // yes czi con
if(MC==choices[1]){ // yes MC
if (TF==choices[1]){ // yes TF
path = TFDir;
filelistTF = getFileList(path);
}else{ // no TF
showMessage("Need pre-processed data for segmentation.");
}
}else{ // no MC
if (TF==choices[1]){ // yes TF
path = TFDir;
filelistTF = getFileList(path);
}else{ // no TF
showMessage("Need pre-processed data for segmentation.");
}
}
}else{ // no czi conv
if(MC==choices[1]){ // yes MC
if (TF==choices[1]){ // yes TF
path = TFDir;
filelistTF = getFileList(path);
}else{ // no TF
showMessage("Need pre-processed data for segmentation.");
}
}else{ // no MC
if (TF==choices[1]){ // yes TF
path = TFDir;
filelistTF = getFileList(path);
}else{ // no TF
filelistTF = getFileList(path); // ONLY segmentation run... get path to files from user
}
}
}
THDir = path + "/TH/"; // output folder
File.makeDirectory(THDir); // make output folder
print("Output folder segmentation: " + THDir);
EdgeDir = path + "/Edges/"; // output folder
File.makeDirectory(EdgeDir);
print("Output folder edges: " + EdgeDir);
while(nImages>0){ // close all windows
selectImage(nImages);
close();
}
// ROI selection
if(THROIs==choices[1]){ // ROI set exists
filelistTH = getFileList(path); // ROIs in the folder where enhanced (TF) images are; given in initial user prompt
// create file to write volume measurements
f = File.open(path + "VascVolResults.txt");
// ask WHERE RoiSet is; if "RoiSet exists" selected
pathROIs = getDirectory("Tell me in which folder I can find the 'RoiSet.zip' ...");
roiManager("Open", pathROIs + "RoiSet.zip");
//open ROI set
n = roiManager("count");
r=0; // counter for ROIset
// colourSetting needed for clearing outside for vascular volume quantification
setForegroundColor(255, 255, 255);
setBackgroundColor(255, 255, 255);
// start processing of files
for (i=0; i< filelistTH.length; i++) {
if (endsWith(filelistTH[i], ".tif")) {
run("Set Measurements...", "area mean standard min perimeter bounding fit stack redirect=None decimal=3"); // 25062019
open(path + filelistTH[i]);
// segmentation
selectWindow(filelistTH[i]);
//get image properties
getDimensions(width, height, channels, slices, frames);
preWidth = width;
preHeight = height;
preChannels = channels;
preSlices = slices;
preFrames = frames;
getPixelSize(unit,pixelWidth,pixelHeight,voxelDepth);
prePixelWidth = pixelWidth;
prePixelHeight = pixelHeight;
preVoxelDepth = voxelDepth;
voxelVol= (prePixelWidth * prePixelHeight * preVoxelDepth);
run("8-bit");
setSlice(50);
setAutoThreshold("Default dark");
run("Threshold...");
setThreshold(4, 255); // threshold to be changed if other image acquisition settings
setOption("BlackBackground", false);
run("Make Binary", "method=Default background=Light");
// re-set original image values
run("Properties...", "channels=" + preChannels + " slices=" + preSlices + " frames=" + preFrames +" unit=µm pixel_width=" + prePixelWidth + " pixel_height=" + prePixelHeight + " voxel_depth=" + preVoxelDepth);
//iterate through ROI set
roiManager("Select", r);
run("Measure"); // for density
AreaUm = getResult("Area"); // for density
// clear outside
//run("Invert", "stack");
roiManager("Select", r);
setBackgroundColor(255, 255, 255);
run("Clear Outside", "stack");
run("RGB Color");
run("8-bit");
// Save segmented stack as tiff stack
saveAs("Tiff", THDir + "TH_" + filelistTH[i]);
run("Invert", "stack");
// create MIP
run("Z Project...", "projection=[Max Intensity]");
run("Invert");
roiManager("Select", r);
run("Clear Outside");
saveAs("Jpeg", THDir + "MAX_TH_" + filelistTH[i]);
run("Close");
run("Invert", "stack");
if (DS==choices[1]){ // perform downsampling here
selectWindow("TH_" + filelistTH[i]);
DownSampleDir = path + "/Downsampled/"; // output folder
File.makeDirectory(DownSampleDir);
// prompt user for what the output height should be
Dialog.create("Select ... ");
Dialog.addNumber("Image output height [voxels]:", 512);
Dialog.show();
ImageOutSize = Dialog.getNumber();
getDimensions(width, height, channels, slices, frames);
// conversion for # slices after conversion
if(height <= ImageOutSize){
print("Image input smaller than the selected output height.");
}else {
factor = height / ImageOutSize;
DownsampledWidth = round(width/factor);
DownsampledSlices = round(slices/factor);
// actual downsampling step
run("Scale...", "x=- y=- z=1.0 width=" + DownsampledWidth + " height=" + ImageOutSize + " depth=" + DownsampledSlices + " interpolation=Bilinear average process create");
setThreshold(123, 255);
setOption("BlackBackground", false);
run("Make Binary", "method=Default background=Default");
saveAs("Tiff", DownSampleDir + "Downsampled_" + filelistTH[i]);
run("Invert", "stack");
run("Z Project...", "projection=[Max Intensity]");
run("Invert");
saveAs("Jpeg", DownSampleDir + "MAX_Downsampled_" + filelistTH[i]);
close();
}
}
//vascular volume [vx] quantification - ROI from MIPs
selectWindow("TH_" + filelistTH[i]);
// histogram count black
roiManager("Select", r); // 02112020
run("Histogram", "stack");
// [255] is VascVox
Plot.getValues(values, counts);
//VascVox=counts[255];
VascVoxVal1 = counts[0];
VascVoxVal2 = counts[255];
if(VascVoxVal1 < VascVoxVal2){
VascVox = VascVoxVal1;
}else{
VascVox = VascVoxVal2;
}
close(); // histogram
VascVol = voxelVol * VascVox;
// vascular density
selectWindow("TH_" + filelistTH[i]);
AreaVx = AreaUm / voxelVol; // change um to vx
FullVox = AreaVx * slices;
dens = FullVox / VascVox; // min 0, max 1
// vascular surface
selectWindow("TH_" + filelistTH[i]);
run("Find Edges", "stack");
run("Invert", "stack");
saveAs("Tiff", EdgeDir + "Edges_" + filelistTH[i]);
run("Invert", "stack");
run("Z Project...", "projection=[Max Intensity]");
run("Invert");
roiManager("Select", r);
run("Clear Outside");
saveAs("Jpeg", EdgeDir + "MAX_Edges_" + filelistTH[i]);
run("Close");
selectWindow("Edges_" + filelistTH[i]);
run("Invert", "stack");
// histogram count black
run("Histogram", "stack");
// [255] is VascVox
Plot.getValues(values, counts);
// EdgeVox=counts[255];
EdgeVoxVal1 = counts[0];
EdgeVoxVal2 = counts[255];
if(EdgeVoxVal1 < EdgeVoxVal2){
EdgeVox = EdgeVoxVal1;
}else{
EdgeVox = EdgeVoxVal2;
}
EdgeVol = voxelVol * EdgeVox;
// print(EdgeVox + " " + AreaVx + " " + FullVox + " " + dens); // debug 02112020
print(f, filelistTH[i] + " \t" + "VascVox" + "\t" + VascVox + "\t" + "VascVol" + "\t" + VascVol + "\t" + "EdgeVox" + "\t" + EdgeVox + "\t" + "EdgeVol" + "\t" + EdgeVol + "\t" + "density" + "\t"+ dens);
r++; // counter for ROI in ROIset
close(); // processed tiff
close(); // processed tiff Oct 2020
}
}
}else{ // ROI set does NOT exist
Dialog.create("Do you want to ... ");
// debug
THChoices = newArray("Cancel.", "Stop after segmentation.");
Dialog.addChoice("What do you want to do after the segmentation?:", THChoices);
Dialog.show();
whatAboutTH = Dialog.getChoice();
if(whatAboutTH==THChoices[0]){
print("You chose to cancel.");
exit;
}else{ // stop after segmentation
print("You chose to stop after segmentation");
filelistTH = getFileList(path); // ROIs in the folder where enhanced (TF) images are; given in initial user prompt
// create file to write volume measurements
f = File.open(path + "VascVolResults.txt");
// segment
// colourSetting needed for clearing outside for vascular volume quantification
setForegroundColor(255, 255, 255);
setBackgroundColor(255, 255, 255);
for (i=0; i< filelistTH.length; i++) {
if (endsWith(filelistTH[i], ".tif")) {
open(path + filelistTH[i]);
// segmentation
selectWindow(filelistTH[i]);
//get image properties
getDimensions(width, height, channels, slices, frames);
preWidth = width;
preHeight = height;
preChannels = channels;
preSlices = slices;
preFrames = frames;
getPixelSize(unit,pixelWidth,pixelHeight,voxelDepth);
prePixelWidth = pixelWidth;
prePixelHeight = pixelHeight;
preVoxelDepth = voxelDepth;
voxelVol= (prePixelWidth * prePixelHeight * preVoxelDepth);
run("8-bit");
setSlice(50);
setAutoThreshold("Default dark");
run("Threshold...");
setThreshold(4, 255); // threshold to be changed if other image acquisition settings
setOption("BlackBackground", false);
run("Make Binary", "method=Default background=Light");
// re-set original image values
run("Properties...", "channels=" + preChannels + " slices=" + preSlices + " frames=" + preFrames +" unit=µm pixel_width=" + prePixelWidth + " pixel_height=" + prePixelHeight + " voxel_depth=" + preVoxelDepth);
// Save segmented stack as tiff stack
THtiff = "TH_" + filelistTH[i];
saveAs("Tiff", THDir + "TH_" + filelistTH[i]);
// create MIP
run("Z Project...", "projection=[Max Intensity]");
saveAs("Jpeg", THDir + "MAX_TH_" + filelistTH[i]);
//vascular volume [vx] quantification - without ROIs
selectWindow("TH_" + filelistTH[i]);
// histogram count black
run("Histogram", "stack");
// [255] is VascVox
Plot.getValues(values, counts);
//VascVox=counts[255];
VascVoxVal1 = counts[0];
VascVoxVal2 = counts[255];
if(VascVoxVal1 < VascVoxVal2){
VascVox = VascVoxVal1;
}else{
VascVox = VascVoxVal2;
}
close(); // histogram
VascVol = voxelVol * VascVox;
if (DS==choices[1]){ // perform downsampling here
selectWindow("TH_" + filelistTH[i]);
run("Duplicate...", "title=forDS duplicate");
selectWindow("forDS");
DownSampleDir = path + "/Downsampled/"; // output folder
File.makeDirectory(DownSampleDir);
// prompt user for what the output height should be
Dialog.create("Select ... ");
Dialog.addNumber("Image output height [voxels]:", 512);
Dialog.show();
ImageOutSize = Dialog.getNumber();
getDimensions(width, height, channels, slices, frames);
// conversion for # slices after conversion
if(height <= ImageOutSize){
print("Image input smaller than the selected output height.");
}else {
factor = height / ImageOutSize;
DownsampledWidth = round(width/factor);
DownsampledSlices = round(slices/factor);
// actual downsampling step
run("Scale...", "x=- y=- z=1.0 width=" + DownsampledWidth + " height=" + ImageOutSize + " depth=" + DownsampledSlices + " interpolation=Bilinear average process create");
setThreshold(123, 255);
setOption("BlackBackground", false);
run("Make Binary", "method=Default background=Default");
saveAs("Tiff", DownSampleDir + "Downsampled_" + filelistTH[i]);
run("Invert", "stack");
run("Z Project...", "projection=[Max Intensity]");
run("Invert");
saveAs("Jpeg", DownSampleDir + "MAX_Downsampled_" + filelistTH[i]);
close();
}
}
// vascular density
selectWindow("TH_" + filelistTH[i]);
// AreaUm - in this case whole slice size - i.e. no ROI
AreaUmFull = preWidth * preHeight;
AreaVx = AreaUmFull / voxelVol; // change um to vx
FullVox = AreaVx * slices;
dens = FullVox / VascVox; // min 0, max 1
// vascular surface
selectWindow("TH_" + filelistTH[i]);
run("Find Edges", "stack");
// run("Invert", "stack");
saveAs("Tiff", EdgeDir + "Edges_" + filelistTH[i]);
run("Invert", "stack");
run("Z Project...", "projection=[Max Intensity]");
run("Invert");
saveAs("Jpeg", EdgeDir + "MAX_Edges_" + filelistTH[i]);
run("Close");
selectWindow("Edges_" + filelistTH[i]);
run("Invert", "stack");
// histogram count black
run("Histogram", "stack");
// [255] is VascVox
Plot.getValues(values, counts);
// EdgeVox=counts[255];
EdgeVoxVal1 = counts[0];
EdgeVoxVal2 = counts[255];
if(EdgeVoxVal1 < EdgeVoxVal2){
EdgeVox = EdgeVoxVal1;
}else{
EdgeVox = EdgeVoxVal2;
}
EdgeVol = voxelVol * EdgeVox;
// print(EdgeVox + " " + AreaVx + " " + FullVox + " " + dens); // debug 02112020
print(f, filelistTH[i] + " \t" + "VascVox" + "\t" + VascVox + "\t" + "VascVol" + "\t" + VascVol + "\t" + "EdgeVox" + "\t" + EdgeVox + "\t" + "EdgeVol" + "\t" + EdgeVol + "\t" + "density" + "\t"+ dens);
close(); // processed tiff
close(); // processed tiff Oct 2020
}
}
} // else stop segm
} // else ROI doesnt exist
while(nImages>0){ // close all windows
selectImage(nImages);
close();
}
} // end segmentation
///// Inter-sample registration
if (InterSReg==choices[1]){
if (regTemplate==choices[1]){ // template exists
// get template
//path = THDir;
path = path;
filelistReg = getFileList(path);
open(path + "template.tif"); // Oct 2020
template=getTitle();
getDimensions(width, height, channels, slices, frames);
preSlicesTemplate = slices;
}else { // template does not exist
// prompt for template selection
//filelistReg = getFileList(path);
// FileNameReg = File.openDialog("Choose a template file");
// duplicate and rename the selected file and save as "template"
open();
// run("Duplicate...", "duplicate");
saveAs("Tiff", path + "template.tif");
filelistReg = getFileList(path);
template=getTitle();
getDimensions(width, height, channels, slices, frames);
preSlicesTemplate = slices;
}
print("Running Inter-Sample Registration.");
RegDir = path + "/Reg/"; // output folder
File.makeDirectory(RegDir); // make output folder
print("Output folder registration: " + RegDir);
for (i=0; i< filelistReg.length; i++) {
if (endsWith(filelistReg[i], ".tif")){
open(path + filelistReg[i]);
// inter-sample registration
// get image/voxel properties
getDimensions(width, height, channels, slices, frames);
preChannels = channels;
preSlices = slices;
preFrames = frames;
getPixelSize(unit,pixelWidth,pixelHeight,voxelDepth);
preUnit=unit;
prePixelWidth =pixelWidth;
prePixelHeight = pixelHeight;
preVoxelDepth = voxelDepth;
// measure similarity before registration
repTemplate = replace(template, ".tif", "");
rename("template");
repMoving = replace(filelistReg[i], ".tif", "");
rename("moving");
run("Label Overlap Measures", "source=moving target=template overlap jaccard dice volume");
saveAs("Results", RegDir + repMoving + "_Unregistered_JacDicOv.csv");
// registration
selectWindow("moving");
run("Rigid Registration", "initialtransform=[] n=1 tolerance=20 level=7 stoplevel=4 materialcenterandbbox=[] showtransformed template=" + template + " measure=Euclidean");
selectWindow("transformed");
run("Invert", "stack");
//setThreshold(0, 132);
setOption("BlackBackground", false);
run("Make Binary", "method=Default background=Default");
// set image/voxel properties
run("Properties...", "channels=" + preChannels + " slices=" + preSlicesTemplate + " frames=" + preFrames + " unit=" + preUnit + " pixel_width=" + prePixelWidth + " pixel_height=" + prePixelHeight + " voxel_depth=" + preVoxelDepth);
saveAs("Tiff", RegDir + "InterSReg_" + filelistReg[i]);
repMovingAfter = replace("InterSReg_" + filelistReg[i], ".tif", "");
rename("movingAfter");
run("Label Overlap Measures", "source=movingAfter target=template overlap jaccard dice volume");
saveAs("Results", RegDir + repMovingAfter + "_Registered_JacDicOv.csv");
// create MIP
run("Z Project...", "projection=[Max Intensity]");
saveAs("Jpeg", RegDir + "MAX_InterSReg_" + filelistReg[i]);
close();
close();
}
}
run("Close All");
}
///// Intra-sample symmetry
if (IntraSym==choices[1]){
run("Set Measurements...", "area mean standard min perimeter bounding fit stack redirect=None decimal=3");
// WHAT IF registered before... can we skip the bit of line ROIs rotation and midline ROI for all of them
// just get the one for the initial template?
if(TH==choices[1]){ // segmentation was selected - we can use this path
if(InterSReg==choices[1]){ // inter-sample registration
path = RegDir;
filelistSym = getFileList(path);
}else{ // NO inter-sample registration
path = THDir;
filelistSym = getFileList(path);
}
}else{ // segmentation was not selected; need to prompt for path to find these files
filelistSym = getFileList(path);
}
print("Running Intra-Sample Symmetry Assessment.");
SymDir = path + "/Sym/"; // output folder
File.makeDirectory(SymDir);
print("Output folder symmetry: " + SymDir);
// create file to write quantification outputs
f = File.open(path + "IntraSampleSymmetryResults.txt");
//open ROI set
// roiManager("Open", path + "RoiSetLine.zip");
pathROIs = getDirectory("Tell me in which folder I can find the 'RoiSetLine.zip' ...");
if(RegForSym==choices[0]){ // samples not registered
roiManager("Open", pathROIs + "RoiSetLine.zip");
}else { // samples registered
roiManager("Open", pathROIs + "TemplateLineROI.roi");
}
n = roiManager("count");
t=0; // counter for RoiSetLine
// intra-sample symmetry
///// ROTATION /////
for (i=0; i< filelistSym.length; i++) {
if (endsWith(filelistSym[i], ".tif")) {
run("Set Measurements...", "area mean standard min perimeter bounding fit stack redirect=None decimal=3"); // 25062019
open(path + filelistSym[i]);
selectWindow(filelistSym[i]);
//get image properties
getDimensions(width, height, channels, slices, frames);
preChannels = channels;
preSlices = slices;
preFrames = frames;
getPixelSize(unit,pixelWidth,pixelHeight,voxelDepth);
prePixelWidth =pixelWidth;
prePixelHeight = pixelHeight;
preVoxelDepth = voxelDepth;
voxelVol= (prePixelWidth * prePixelHeight * preVoxelDepth);
roiManager("Select", t);
if(RegForSym==choices[0]){ // samples not registered
t++; // counter for ROI in ROIset
}
run("Measure"); // measure the angle of line ROI for rotation
MeasAngle = getResult("Angle"); // measured angle from LineROI
//debug
print(MeasAngle);
if (MeasAngle<0){
betrag = abs(MeasAngle);
rot = -(90 + betrag);
}else if (MeasAngle>0){
betrag = abs(MeasAngle);
rot = -(90 - betrag);
}else{
rot=90;
}
//debug
print(rot);
setSlice(50);
run("Invert", "stack");
run("Rotate... ", "angle=" + rot + " grid=1 interpolation=Bilinear stack"); // rotate image based on line ROI from MIPs
// BINARIZE images (rotation does change it)
//setThreshold(128, 255);
setOption("BlackBackground", false);
run("Make Binary", "method=Default background=Light");
// run("Invert", "stack");
// Save segmented stack as tiff stack
saveAs("Tiff", SymDir + "Rot_" + filelistSym[i]);
// create MIP
run("Z Project...", "projection=[Max Intensity]");
saveAs("Jpeg", SymDir + "MAX_rot_" + filelistSym[i]);
// close(); // keep MIPs open to draw midline ROI
close();
}
}
// delete all ROIs from ROILinesSet
arrayLines = newArray("0");;
for (k=1;k<roiManager("count");k++){
arrayLines = Array.concat(arrayLines,k);
}
roiManager("select", arrayLines);
roiManager("Delete");
selectWindow("Results"); // close RoiSetLine results table
run("Close");
////// L R symmetry /////
// prompt input for midline ROIs
waitForUser("Draw line ROI along midline of rotated images (need to be in order). \n 'Add' to ROI manager. \n Press 'ok'.");
n=0; // counter for ROIsetMiddle
// open rotated images
filelistMidline = getFileList(SymDir);
LRDir = path + "/LRVol/";
File.makeDirectory(LRDir);
for (m=0; m< filelistMidline.length; m++) {
if (endsWith(filelistMidline[m], ".tif")) {
run("Set Measurements...", "area mean standard min perimeter bounding fit stack redirect=None decimal=3"); // 25062019
open(SymDir + filelistMidline[m]);
selectWindow(filelistMidline[m]);
//get image properties for L and R box dimensions to be drawn
getDimensions(width, height, channels, slices, frames);
VolWidth = width;
HalfWidth = width / 2;
//print(HalfWidth);
VolHeight = height;
getPixelSize(unit,pixelWidth,pixelHeight,voxelDepth);
LRPixelWidth = pixelWidth;
LRprePixelHeight = pixelHeight;
LRpreVoxelDepth = voxelDepth;
LRvoxelVol= (prePixelWidth * prePixelHeight * preVoxelDepth);
roiManager("Select", n);
if(RegForSym==choices[0]){ // samples not registered
n++; // counter for ROI in ROIsetMiddle
}
run("Measure"); // measure the angle of line ROI for splitting L R box
MeasX = getResult("BX"); // measured X-position from LineROI for L and R box
MeasXvx = MeasX / LRPixelWidth;
RBoxWidth = width - MeasXvx;
RStart = width - (RBoxWidth * 2);
// box can only be that big.. L/R smaller/bigger - take smaller one and extend to both sides..
if(MeasXvx<HalfWidth){ // sample is more to the left -> left side taken for box size
setTool("rectangle");
makeRectangle(0, 0, MeasXvx, VolHeight); // x,y,w,h
////// LEFT BOX //////
run("Duplicate...", "duplicate");
// quant L vol
// histogram count black
run("Histogram", "stack");
// [255] is VascVox
Plot.getValues(values, counts);
// LVascVox=counts[255];
LVascVoxVal1 = counts[0];
LVascVoxVal2 = counts[255];
if(LVascVoxVal1 < LVascVoxVal2){
LVascVox = LVascVoxVal1;
}else{
LVascVox = LVascVoxVal2;