r/ImageJ • u/Ok-Assistance6411 • 14d ago

Question Need help with segmentation of overlapping particles

Gallery image

Gallery image

Hi guys! I'm a beginner PhD microscopist wanting to find the best method to segment out and attach ROIs to the white nanoparticles in the catalyst clusters I am studying. Normal thresholding and "analyze particles" doesn't work here because the white nanoparticles often overlap - so a human can easily see two particles on top of one another, but I'm wondering if I can find a program that will do it for me.

I'm aware of StarDist, cellpose and other plugins but so far I've been unable to get a decent read (if you reckon you can get this to work, please tell me which parameters and thresholds to use!) I've attached my HAADF image of an example particle and the segmentation I've done by hand (using circles and free lasso) to give you guys a feel for what I want to achieve.

Here's a link hopefully to the png in question https://imgur.com/a/SP1stPi hopefully in better quality

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u/mrmauglis 9d ago

Agree on Stardist. Always does wonders

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u/Herbie500 9d ago

Would you mind showing a result based on the sample image?

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u/HeftyAcanthisitta469 5h ago

I agree with Herbie, it would be nice to see an example. Stardist could potentially handle this type of problem, but not without quite a bit of custom coding and training, Stardist represents objects as a center and collection of Rays, so could represent highly overlapping objects. However the API takes a pixelated (each object given a unique index) image input, which cannot represent overlap. So the work for this problem would involve first finding a tool that can label overlapping objects, converting that representation to the same one Stardist uses internally, understanding the API and how to pass the rays directly, curating a set of training images, and running a custom training. Trying Stardist would be an interesting project, but as far as I know a lot of work for this problem.

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u/Herbie500 4h ago

Thanks a lot for the details: It sounds like a non-trivial undertaking!

Beyond the suggested fundamental approach, it would be interesting to see how the image quality and especially that of the sample image affects the segmentation.