// Macro for calculating percentage of fibrose componnent compared to cardiomyocyte component
// taking into account the lumen part or not in batch
// 
// Folder structure:
// Source folder selected contains subfolders that contain the images
// Result folder, just a folder to store results
//
// Artificial example of folder structure
// C:\temp\rat_images contains subfolders per rat with images like
// C:\temp\rat_images\rat1\LV1.tif	
// C:\temp\rat_images\rat1\RV1.tif
// C:\temp\rat_images\rat1\... (etc. for rat1)
// C:\temp\rat_images\rat2\LV1.tif
// C:\temp\rat_images\rat2\RV1.tif
// C:\temp\rat_images\rat2\... (etc. for rat2)
//
// The colour thresholding algorithm used by this macro is based on an algorithm written by G. Landini (version v1.8) available at:
// http://www.dentistry.bham.ac.uk/landinig/software/software.html

// 
// Note: This only works with Black background and White foreground!
run("Colors...", "foreground=white background=black selection=yellow");
run("Options...", "iterations=1 black count=1");

//
// All image calculation using logical operators take zero values as zero and 255 as "one" in the case below
// So inverted luts only change black to white and white to black but zero stays zero meaning black was zero and after
// inverting the LUT white is now zero.
// Anything measured needs to have value 255
// So 255 or '1' is the object

// Creation 18-07-2007 J.A.M. Belien
// Update history:
// Small modifications with respect to version updates:
// - last modification: modified to operate correctly with latest version 1.43u, dd 19-07-2010

// Required ImageJ version 
requires("1.43u");

dir1 = getDirectory("Choose Source Directory ");
list1 = getFileList(dir1);
setBatchMode(true);

for (my_list1=0; my_list1<list1.length; my_list1++)  {
	open(dir1+list1[my_list1]);
	AssessFibrosisComponents();
	close();

	
 
function AssessFibrosisComponents() {

	// Initialisation based on emperical analyses of test data set
	exclude_high_th=72;
	lumen_low_th=240;
	fibrosis_high_th=130;
	name= getTitle
	image_name = File.name;
	OriginalImage = getImageID();



	//Now obtain fibrosis component
	selectImage(OriginalImage);
	run("Duplicate...", "title=fibrosis_area");
	FibrosisImage = getImageID();
	selectImage(FibrosisImage);
	min=newArray(3);
            max=newArray(3);
            filter=newArray(3);
	a=getTitle();
	run("RGBtoLab ");
	run("RGB Stack");
	run("Convert Stack to Images");
	selectWindow("Red");
	rename("0");
	selectWindow("Green");
	rename("1");
	selectWindow("Blue");
	rename("2");
	min[0]=0;
	max[0]=lumen_low_th-1;
	filter[0]="pass";
	min[1]=fibrosis_high_th;
	max[1]=255;
	filter[1]="pass";
	min[2]=0;
	max[2]=255;
	filter[2]="pass";
	for (i=0;i<3;i++){
  		selectWindow(""+i);
  		setThreshold(min[i], max[i]);
  		run("Make Binary", "thresholded remaining");
  		if (filter[i]=="stop")
  			run("Invert");
	}
	imageCalculator("AND create", "0","1");
	imageCalculator("AND create", "Result of 0","2");
	for (i=0;i<3;i++){
  		selectWindow(""+i);
  		close();
	}
	selectWindow("Result of 0");
	close();
	selectWindow("Result of Result of 0");
	rename(a);
	// Colour Thresholding------------
	run("8-bit");

	// Fibrosis
	selectImage("fibrosis_area");
	run("Invert");
	totarea_fibrosis=0;
	run("Analyze Particles...", "size=0-Infinity circularity=0.00-1.00 show=Nothing clear");
	for (i=0; i<nResults; i++) {
		totarea_fibrosis = totarea_fibrosis+ getResult("Area",i);
	}
	close();

	run("Clear Results");
	setResult("Total area fibrosis (pixels) "+ name, 0, totarea_fibrosis);
        	updateResults();
        	selectWindow("Results" );
       	run("Text..."); // File>Save As>
	run("Measure")
	run("Text..."); // File>Save As>
	selectWindow("fibrosis_area");
	saveAs("Tiff..."); // File>Save As.\>

}
}//End of for my_list
}//End if list.length>0
}//End of for my_list1