HT-PropagatedNeuriteSkeletonization/preprocessing_deprecated.ijm at master · RUB-Bioinf/HT-PropagatedNeuriteSkeletonization · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
inputDir = getArgument();
print(inputDir);
processFolder(inputDir);


function processAlexaFile(input){
	print("3");

	open(input);
	subStr = split(input, ".");

	getMinAndMax(min, max);
	setMinAndMax(min, (max/2));
	run("Apply LUT");
	getMinAndMax(min, max);
	setMinAndMax(min, (max/2));
	run("Apply LUT");
	run("8-bit");
	run("Auto Local Threshold", "method=Phansalkar radius=35 parameter_1=0 parameter_2=0 white");
	saveAs("PNG", ".."+ subStr[0]);
	close();
}

function processDapiFile(input){
	print("2");

	open(input);
	subStr = split(input, ".");

	getMinAndMax(min, max);
	setMinAndMax(min, (max/2));
	run("Apply LUT");
	getMinAndMax(min, max);
	setMinAndMax(min, (max/2));
	run("Apply LUT");
	run("8-bit");
	saveAs("PNG", ".."+ subStr[0]);
	close();
}

function processFolder(input){
	print("1");
	list = getFileList(input);
	for(i = 0; i < list.length; i++){
		if(File.isDirectory(input + list[i]))
		{
			print(input + list[i]);
			print("8");
			processFolder(input + list[i]);
		}
		if (endsWith(list[i], ".tif"))
		{
			if (matches(list[i], ".*Alexa.*")){
				print(input + list[i]);
				print("9");
				processAlexaFile(input + list[i]);
			}
			if (matches(list[i], ".*DAPI.*")){
				print(input + list[i]);
				processDapiFile(input + list[i]);
			}
		}
	}
	print("ImageJ Vorverarbeitung fertig");
}