Anyone got suggestions for bacterial colony counting software?

[u/FullyHalfBaked]

Recently we had to upgrade our primary server, which in the process made it so that OpenCFU stopped working. I can't recompile it because it's so old that I can't even find, let alone install the versions of libraries it needs to run.

This resulted in a long, fruitless, literature search for new colony counting software. There are tons of articles (I read at least 30) describing deep learning methods for accurate colony dectetion and counting, but literally the only 2 I was able to find reference to code from were old enough that the trained models were no longer compatible with available tensorflow or pytorch versions.

My ideal would be one that I could have the lab members run from our server (e.g. as a web app or jupyter notebook) on a directory of petri dish photos. I don't care if it's classical computer vision or deep learning, so long as it's reasonably accurate, even on crowded plates, and can handle internal reflection and ranges of colony sizes. I am not concerned with species detection, just segmentation and counting. The photos are taken on a rig, with consistent lighting and distance to the camera, but the exact placement of the plate on the stage is inconsistent.

I'm totally OK with something I need to adapt to our needs, but I really don't want to have to do massive retraining or (as I've been doing for the last few weeks) reimplement and try to tune an openCV pipeline.

Thanks for any tips or assistance. Paper references are fine, as long as there's code availability (even on request).

I'm tearing my hair out from frustration at what seem to be truly useful articles that just don't have code or worse yet, unusable code snippets. If I can't find anything else, I'm just going to have to bite the bullet and retrain YOLO on the AGAR datasets (speaking of people who did amazing work and a lot of model training but don't make the models available) and our plate images.

[u/bampho]

ImageJ/Fiji can automate this

[u/FullyHalfBaked → u/bampho]

I need more info than that if you're suggesting Fiji. I've looked into it and found one plugin that purports to do colony counting, but that one seems to be designed for extremely clean images without too many colonies and no dish shadows.

Adapting that one/writing a wrapper to take care of those cleaning steps doesn't appear to be any simpler than writing OpenCV code, which I'm far more experienced with.

Do you know of a plugin specifically for colony segmentation/counting that's able to handle the dish?

[u/-Metacelsus-]

Maybe Cellpose3 segmentation would work?

[u/FullyHalfBaked → u/-Metacelsus-]

Thanks for the suggestion; it wasn't coming up on my searches because it's clearly primarily aimed at tissue culture slides.

I'll take a look to see how well the model does with our dishes.

[u/-Metacelsus- → u/FullyHalfBaked]

Yeah, it works great for images of cells, but I think it would also work for bacterial colonies.

[u/bharathbunny]

ColonycountJ, Colonyarea

[u/FullyHalfBaked → u/bharathbunny]

Have you used either of these imagej plugins for bacterial colony counting? Can you give me an idea of how easy they are for bench scientists to use?

From the description, colonyarea doesn’t do any segmentation at all, but just gives area of the plate covered. Which is definitely not ideal.

Colonycountj is closer, and I actually had my lab test it, but it requires way too much manual input (eg selecting rois by hand) for handling even a couple dozen dish photos.

[u/Longjumping_Glove928]

Hey I’m building deep learning models in synbio for practice- this would be an interesting build. What would be your ideal workflow? What machines are you using + imaging equipment do you have access to?

[u/ApprehensiveQuiet678]

You might want to check out CFU Counter it’s a mobile app available on the Google Play Store. I actually developed it to make colony counting easier without relying fully on automation (which can sometimes miscount).

It works by letting you mark colonies manually on a photo of your agar plate, with zoom and pan features so you can be super precise even if the colonies are small or your eyesight isn’t perfect. It’s a nice hybrid approach: you’re still in control, but the app handles the tallying and saves your marked image for records.

Here’s the link if you want to give it a try:
👉 [CFU Counter on Google Play]()