QZM

I don't really use QuPath, I don't like it. But the person before me used it to annotate images and now I need to transfer these ROIs/Annotations to ImageJ where my pipeline is. Managed to find a good script for exporting with annotations, but it seems this person transformed the images (differently each time fml), and I need them to be the right orientation because I'm transferring those annotations to another set of images of the same samples from another microscope. Needless to say, I need to do some image registration, a very easy task /s. So is there any way to at least revert back to the initial orientation before export so I make the registration easier? I'm using SIFT which isn't really capable of accounting for mirroring/flipping, so that step really needs to be fixed beforehand. Any ideas? Or at the very least, is there a way to extract transformation history from the Metadata or so such that I can at least use that info to programmatically revert in ImageJ?

This community was inspired by the subreddit ImageJ and of course image.sc. It's meant to be a hub to show and tell your pipelines and codes, ask questions about scripting and approaches in any image processing software, bring new ideas and cool tricks, discuss how the field is evolving from classical towards computer vision and machine learning approaches, and much more. We're still a small community, and we'd love to have you to grow and become a lively hub of discussion of this awesome field.

I came across a small script that opens a window with a progress bar that increases after the completion of every iteration in a for loop. It's pretty useful in a big macro cycling through many images. Sometimes you just want to know your progress in batch mode. So here is the helpful script (from https://imagej.nih.gov/ij/macros/ProgressBar.txt):

// Progress Bar
//
// This macro demonstrates how to display status
// information and a progress bar in a text window. 
// It uses the Plugins>New>Text Window command
// to open a text window without a menu bar.

  title = "[Progress]";
  run("Text Window...", "name="+ title +" width=25 height=2 monospaced");
  for (i=0; i<100; i++) {
     print(title, "\\Update:"+i+"/"+100+" ("+(i*100)/100+"%)\n"+getBar(i, 100));
     wait(200);
  }
  print(title, "\\Close");

  function getBar(p1, p2) {
        n = 20;
        bar1 = "--------------------";
        bar2 = "********************";
        index = round(n*(p1/p2));
        if (index<1) index = 1;
        if (index>n-1) index = n-1;
        return substring(bar2, 0, index) + substring(bar1, index+1, n);
  }

Note: if you using other nested for loops, ensure that the variable you choose isn't the same as the one here (i), except of course the for loop you're actually trying to find track the process of. Happy macroing!

I had just bought the Zephyrus M16 for 2700 bucks. But for some reason it didn't get dispatched yet, so I just noticed they have this prime deal day thing on Amazon(.de, the German one, not sure about other Amazons) where I got it. It's now 2080 bucks (wtf!). So I cancelled my order and ordered again. Just an FYI, good time to buy I guess, lots of other laptops are on huge discounts with prime (I just got a trial, I'll unsubscribe later lol).

First of all, I am so happy that we're getting more and more members. Thank you all for joining!

I'm going to post the first question on here. Ideally, we should always try to post example images when asking a question, but I'm hypocritically not doing it mainly because I think it's a straightforward question.

I'm trying to do some analysis on histology images using ImageJ macro scripting (IJM language), and at some point in the script I have the coordinates of an approximate center of a cell, derived from it's cell body center of mass. However, my downstream quantification requires that I skeletonize. But now the coords may or may not fall on the 1-pixel wide skeleton. I need it to fall on it for subsequent analysis, so I want to find the nearest non-zero pixel to these coords on the skeleton image.

I did come up with an approach, and the script is enclosed below. But.. it's a bit slow, and it needs to be much faster because the script is gigantic.

The approach simply makes a circle centered on the coords I have, and the circle is only 10 pixels in radius, because it appears that's enough to capture the skeleton's nearest white pixel in all cases. Then I iterate through every pixel in this circular ROI computing its euclidean distance from my coords only if it's non-zero (white).

Question: So you see how it's not a quick approach, and if there is a plugin to do this instead, it would be so much faster because it's skipping the wrapping. For context, this is part of a nested for loop for many many objects in many many regions in hundreds of images.

Here is the code:

// Making a circular 10-px radius ROI centered on coords
makeEllipse(CoordX-10, CoordY, CoordX+10, CoordY, 1);
Roi.getContainedPoints(containedX, containedY);
// Iterating through all pixels contained in the search circle
// Euclidean distance is calculated for non-zero pixels and tabulated
Table.create("Non-Zero Contained Pixels");
for (p = 0; p < containedX.length; p++) {
	value = getPixel(containedX[p], containedY[p]);
	selectWindow("Non-Zero Contained Pixels");
	// Keeping indexing for the table independent of the loop as many pixels will be skipped
	outOfLoopSize = Table.size;
	if (value == 255) {
		distance = sqrt(pow(containedX[p]-CoordX, 2)+pow(containedY[p]-CoordY, 2));
		Table.set("CoordIndex", outOfLoopSize, p);
		Table.set("Distance", outOfLoopSize, distance); 
	}
}
selectWindow("Non-Zero Contained Pixels");
// Sorting by distance and setting new coordinates
Table.sort("Distance");
Table.update;
nearestNeighbor = Table.get("CoordIndex", 0);
// Setting the new seed pixel for downstream quantification
seedX = containedX[nearestNeighbor];
seedY = containedY[nearestNeighbor];
close("Non-Zero Contained Pixels");
// Add computed seed for Sholl analysis
// i refers to a much larger for loop, just writing this for contextual information for this script excerpt
selectWindow("Skeleton" + i);
run("Select None");
Overlay.clear
updateDisplay();
makePoint(seedX, seedY, "small yellow hybrid");

Thanks a lot! And keep spreading the word :D

I had a normal ThinkPad T590, for work. But I recently dropped it and the screen is busted, thought it's better I buy something new than pay to repair. Since I'm already knees deep in image analysis, which requires a crap ton of RAM, a strong CPU and ideally a semi decent GPU, and just started getting into python coding, thought why not get a gaming laptop, it'll make my life easier. Of course I already have access to a beast of a workstation, but sometimes it's booked and you wanna do some work on your own laptop. Anyway, I saw the Zephyrus and thought it looks good, excellent RAM (32GB and can be upgraded to 48), excellent i9 (12900H), and of course the beloved 3080 Ti (and 2TB of SSD is greet for when I have to work because single images can be up to 4 GB sometimes).

What do you guys think? I'm fkn poor, I'm a researcher afterall, so I got this on installments from Amazon, please tell me I didn't do an impulsive purchase.

I know I'm not posting anything, but I didn't abandon the place lol. I'm just waiting to have at least ten or so members, because it's a problem-solution oriented community, so we need someone to come in and drop a problem so people can offer solutions. I'm very inexperienced in these things, so I have no idea how to promote this place to grow it, any ideas?

I want this place to succeed and grow, so let's get active!

Kinda sad, I'm the only one here lol. But given the beginning of the downfall of Reddit, I thought I'd migrate here and make a community about my interests. I hope whoever joins spreads the word and we can make this a lively, informative, and helpful community for all image analysts out there. I mostly work with FIJI (ImageJ) and ilastik, and I hope all the new joiners have other expertise that can diversify this community more and more.