Kem4d ago

Just shipped v0.1.0 of CellSeg — an open-source Android app that runs Cellpose cell segmentation on-device

Free, MIT-licensed, no ads, no tracking. ~14 MB cyto3 ONNX model, runs fully offline after first download. Optional Cellpose-SAM cloud fallback via Hugging Face for harder cases

Written up the launch with the architecture, the licensing chapter, and an honest list of what v0.1.0 isn't yet:

https://kemal.yaylali.uk/cellseg-v0-1-0-is-out/

#bioinformatics #microscopy #cellpose #android #buildinpublic #opensource

Kemal4d ago

CellSeg v0.1.0 is out

Three months ago I started building an Android app to count cells. Today the first public build is up, and I'd like to introduce it properly. It's called CellSeg, and it does one stubborn small thing: it lets a bench scientist take a picture of a microscopy sample with their phone and get a cell count out of it in a few seconds, on the device, with no laptop and no cloud round-trip in the way. You can install it from cellseg.yaylali.uk. It's an open-source sideload APK — not on the Play […]

https://kemal.yaylali.uk/cellseg-v0-1-0-is-out/

Kemal5d ago

The bench problem that wouldn’t go away

CellSeg There's a thing that happens in a tissue culture lab that I've never quite gotten used to, even after years of doing it. You pull a sample from a flask or a bioreactor, you load it onto a counting chamber, you put your eye to the microscope, and then you spend the next several minutes squinting at a grid and clicking a tally counter. If you're being honest about it, the count you write down is half measurement, half judgement call. Were those two cells one cell that was dividing? Was […]

https://kemal.yaylali.uk/the-bench-problem-that-wouldnt-go-away/

Show threadFabrizio MusacchioJul 13, 2025

Tried the same with a more realistic 3D stack from the #ImageJ sample library.#Cellpose runs fast and segments very well out of the box.#CellSeg3D takes considerably longer and seems to segment decently, but I couldn’t get a proper instance #segmentation in the post-processing step (which is recommended as part of its workflow). However, #CellSeg3D looks very promising — just needs some more time and parameter exploration, I guess.

I’d recommend giving it a try 👌

Show threadFabrizio MusacchioJul 13, 2025
Tested #CellSeg3D and #Cellpose on their example c5image dataset. Both segmentations look reasonable out-of-the-box, without any deep parameter tuning. With some extra effort, one could likely push either further I guess. Overall, both tools perform quite well on this small sample data set.
Fabrizio MusacchioJul 11, 2025

✍️ New in #eLife: #CellSeg3D introduces #WNet3D, a self-supervised 3D #segmentation method for #microscopy data — no labels needed. Claims to outperform #Cellpose/#StarDist on 4 datasets. Includes #opensource plugin (#Napari) + full 3D annotated #cortex dataset. Will test it later.

🌍 https://elifesciences.org/articles/99848

#DeepLearning #Neuroscience

CellSeg3D, Self-supervised 3D cell segmentation for fluorescence microscopy

Self-supervised deep learning models can accurately perform 3D segmentation of cell nuclei in complex biological tissues, enabling scalable analysis in settings with limited or no ground truth annotations.

eLife
CSBJMay 27, 2025

🤖 How resilient are deep learning models to real-world imperfections in microscopy?

🔗 Practical guidelines for cell segmentation models under optical aberrations in microscopy. Computational and Structural Biotechnology Journal, DOI: https://doi.org/10.1016/j.csbj.2024.09.002

📚 CSBJ Quantum Biology and Biophotonics: https://www.csbj.org/qbio

#CellSegmentation #Microscopy #AIinBiology #OpticalAberrations #DeepLearning #BiomedicalAI #Cellpose #ComputationalBiology #PLCM

AI4LifeApr 26, 2024
After a day and a half of #ImageAnalysis in the cloud with #dask by the IDR team, Damian Dalle Nogare takes over a practical session to apply several #AI models for cell segmentation using #Cellpose
Carsen Stringer (she/her)Apr 8, 2024

Despite all their hype in AI, we found that Transformers do not outperform #Cellpose for cellular segmentation tasks: https://www.biorxiv.org/content/10.1101/2024.04.06.587952v1

#bioinformatics #biology #machinelearning

Carsen Stringer (she/her)Feb 14, 2024

#Cellpose 3! Not all images are perfect. Restore your images with Cellpose3 to get better segmentations, w/ @marius10p https://www.biorxiv.org/content/10.1101/2024.02.10.579780v1

(click to play gif)