Ben Gallusser
Deep Learning, Computer Vision, Biology
- 🚀⭐️ Trackastra update 🚀⭐️ We just released a new model that uses pre-trained image features from Meta’s SAM2 model. This improves performance on many datasets, most notably for bacteria tracking. To give it a try, simply install with the new optional dep `etultra` github.com/weigertlab/t...
- We push the SOTA in bacteria tracking once more, the remaining errors are almost cut in half 🎉 This work was spearheaded by the super-talented Cyril Achard in @maweigert.bsky.social's group 👏 For more on transformer-based tracking with pre-trained features, check github.com/C-Achard/Tra...
- Reposted by Ben GallusserWe moved the AI@MBL course "Deep Learning for Microscopy Image Analysis" to HHMI Janelia (@hhmijanelia.bsky.social). Join us for two weeks of intense lectures, exercise, and hands-on project work! Course dates: June 4-18 2026 Application by: January 15 2026 www.janelia.org/you-janelia/...
- 📢 Apply now for the first DL@Janelia Bootcamp (June 4–18, 2026)! 2 weeks of hands-on deep learning for microscopy: train models on your own data, Python needed (no ML experience), housing + meals included, no registration fee 📍 Janelia Research Campus, VA 🗓️ Apply by Jan 15, 2026 🔗 shorturl.at/j4sgY
- Trackastra is part of the brand-new TrackMate v8. It is the first deep-learning-based ("AI") drop-in replacement for TrackMate's regular LAP-Track algorithm. Tracks out of the box for many types of datasets (bacteria, fluorescent nuclei, phase contrast cell culture etc), zero parameters to tune 🤖
- Give it a try following the tutorial made by @jytinevez.bsky.social imagej.net/plugins/trac...
- Here's the full repo github.com/weigertlab/t...
- Thanks @jytinevez.bsky.social for making the nice TrackMate integration
- Reposted by Ben GallusserPreprint - Excited to present WHOLISTIC, which extends the concept of whole-brain functional imaging to the entire body. Pioneering work by incredibly talented Virginia Ruetten @vmsruetten.bsky.social, this platform reveals whole-organism cellular dynamics in vivo. www.biorxiv.org/content/10.1...
- Reposted by Ben Gallusser[Not loaded yet]
- Cell tracking is never perfect, and it's important to understand the types of errors your solution contains. Here is my stab at this: Divisualisations in @napari.org. github.com/bentaculum/d... You spin tracks out upwards from the playing video. Green edges are correct, FP in magenta, FN in cyan.
- I originally made these when developing my tracking algorithm Trackastra www.ecva.net/papers/eccv_..., and have finally made them easy-to-produce for anyone at this year's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.
- With this visualisation one can intuitively compare different trackers
-
View full threadThanks @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....
- Looking for a great PhD position? I had the pleasure of doing my doctoral research in Martin’s group - wholeheartedly recommended :)
- Do you like developing new AI vision methods for microscopy image analysis? You love theory & implementation? 1 week left to apply for a fully funded PhD position in our lab in Dresden 🇩🇪! Topics: object detection/tracking, multimodal models & more. DM/email for details! #PhD #AcademicJobs #GPUsgoBrr
- Reposted by Ben GallusserSpotiflow, our deep learning based spot detection method for microscopy, is now published in @natmethods.nature.com! Since the pre-print, we have added many features, notably native 3D detection! @maweigert.bsky.social @gioelelamanno.bsky.social @epfl-brainmind.bsky.social Paper: rdcu.be/epIB7 (1/N)
- Reposted by Ben Gallusser[Not loaded yet]
