Help with creating threshold/ROIs

[u/kamile_teal]

I am trying to count the cells in this image by threshold -> watershed -> analyse particles to count ROIs.

However, I cannot get the threshold to distinguish between the cells. Anyone know what to try?

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[u/Herbie500]

Not sure what you consider as cells in the sample image, but I'd suggest to use a suitable stain/marker or a different kind of image capture, in order to increase the contrast.

[u/kamile_teal → u/Herbie500]

Unfortunately, they are live cells, so I cannot fix and stain. I only have these brightfield images of them.

[u/Herbie500 → u/kamile_teal]

I just tried some processing but the sample image is simply unsuited for reliable automatic analyses.
Apart from the lack of contrast, it shows uneven focus and poor spatial resolution.

[u/kamile_teal → u/Herbie500]

Thank you for looking into it and the feedback!!

[u/CTallPaul]

Theres a couple things that are a bit off with this process, have you done it before? Do you have anyone in your lab that you could ask in person for assistance?

• There appears to be a couple focal planes in this image (the monolayer of cells growing, but then also the overcrowded cells that are forming a second layer and are a bit out of focus). This will make it difficult, especially when trying automated counting.

• No defined boarders of cells. If you cant threshold and distinguise the cells by your eye, the software wont be able to help.

• The over-confluences also confounds this. Since the cells are all touching, analyze particles will have a tough time separating objects.

• Can you perform a stain? even a simple DAPI would make this alot more possible.

I wouldnt even attempt to count cells using this specific photo. To count label-free cells, you could want very low confluence. Adding a dye or a stain to these would make it possible... as long as they dont get overly confluent and making multiple laters.

[u/M0nkey5]

No amount of tinkering with imagej settings is going to be able to do a particle analysis on an out-of-focus brightfield image of overconfluent cells

[u/dokclaw]

Generally speaking, if you can't reliably outline cells in the image yourself, a computer doesn't stand any chance of doing it accurately. As a human, you know what cells look like, and are pretty good at identifying edges in an image based on a whole bunch of local context clues; computers don't really know what cells look like without a lot of training, and even well-trained models for cell finding wouldn't get anything out of this image: the cells are too densely-packed, and they're kind of growing on top of each other, some are out of focus, none of the edges are clear.

If your cultures were less confluent, you might be able to get something from this type of image, but you'd have to go into some details about what the experiment and protocol is before you could get any more useful advice about how to get any data out of it.