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/

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/

Check our yet another "Protocol for automated analysis of biological images using #Python code" https://sciencedirect.com/science/article/pii/S2666166726000213
-Steps for the analysis of confocal images through Python
-Guidance on the usage of machine learning for #cellsegmentation
-Troubleshooting of common issues

Ko Sugawara shows how training with sparse annotations can produce practical models for cell image segmentation. Strategic selection of annotated cells boosts performance! @ELEPHANT_track @NEUBIAS_ Symposium 🧪🔍 #DeepLearning #BioimageAnalysis #CellSegmentation