Ooh that's awesome! Great to hear the new version improved your segmentations :)

📣Huge thanks to Simon, Hanyi, @lifeonthewedge.bsky.social, @florentwaltz.bsky.social, @wojwie.bsky.social, @kevinyamauchi.bsky.social, @alisterburt.bsky.social, Ye, Antonio, Sebastian, Fabian, @ja-schnabel.bsky.social and especially @cellarchlab.com & @tingyingpeng.bsky.social for incredible support

🤝 Feedback
If you feel like trying one of our modules or even the full pipeline, please let us know how it goes. We are happy for any feedback and would love to improve MemBrain v2 even further to make it as helpful for the community as possible.
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🔑 Usability
We focused on making MemBrain v2 smooth to work with: MemBrain-seg works with a single command line, while MemBrain-pick enables data-efficient training. We facilitate the transition between modules with several Napari functionalities like the 3D lasso to crop areas of interest.
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⚖️ MemBrain-stats
This module analyzes the spatial organization of particles on membranes. It takes the outputs of MemBrain-seg and MemBrain-pick to compute metrics like particle concentrations and geodesic nearest neighbor distances.
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⛏️MemBrain-pick
If you’re interested in localizing membrane-associated particles, please give MemBrain-pick a try. It enables efficient training of a model to localize particles on membranes and works with the Surforama plugin for interactive annotation in Napari.
🔗 github.com/cellcanvas/s...
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🎨 MemBrain-seg
This module allows out-of-the-box segmentation of membranes with just a single command line.
It’s based on a U-Net architecture, trained with a diverse dataset to enable generalization to many settings.

🔗 github.com/teamtomo/mem...
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