Yes, and there is already a pretrained model trained on all Cell Tracking Challenge data, 2d + 3d.

Thanks @jytinevez.bsky.social for making the nice TrackMate integration

Here's the full repo github.com/weigertlab/t...

Give it a try following the tutorial made by @jytinevez.bsky.social imagej.net/plugins/trac...

Super cool!!! So many methods integrated is 🔥

So cool! Causal up until the penultimate layer, I bet the DiGradCam will look interesting. Also, as commonly known, if you can 3d print your neural network architecture you get to name it! GiuseppeNet ;) ?

I love that! A simple thing might be to spin out orthogonal to the major axis (of movement) in the few previous frames, and the sample could be rotated according to that. Not sure if our brains are ready to deal with that

Thanks @janfunkey.bsky.social and team for organizing this fun Hackathon for making open source software for science. Many of the other lit 🔥 cell tracking things we worked on are available at github.com/live-image-t....

Bonus: I added a 3D version, here is an example on the C. elegans dataset from the Cell Tracking Challenge.

With this visualisation one can intuitively compare different trackers

I originally made these when developing my tracking algorithm Trackastra www.ecva.net/papers/eccv_..., and have finally made them easy-to-produce for anyone at this year's @hhmijanelia.bsky.social Trackathon.

Bonus: Recently, I also successfully finished my PhD at EPFL 🥳
It was as an incredible journey, thanks once more to everyone that helped making it a success :)