Constantin Pape

How can we use foundation models such as (micro)SAM to improve electron microscopy segmentation? Check out our preprint! We found substantial improvements for nucleus, mito, and neurite-segmentation using initialization and semi-supervised learning with foundation models.

This research will help us to build better tools for interactive microscopy analysis --- stay tuned for more! For more details: arxiv.org/abs/2603.19802 Thanks to Caro for driving this work and all other co-authors!

We compare foundation models (SAM and DINO variants) with classical features from ilastik and supervised learning. The FM features outperform classical approaches. Attentive probing is better than RF, but too slow for interactive use. See example results in the fig.

Segmenting cells in microscopy is much easier these days thanks to foundation models. Can we use these models for other tasks, e.g. cell classification? See our latest work! We find big improvements for object and pixel classification compared to classical approaches.

Want to learn about the latest trends and developments in bioimage analysis? Join us for the GLOBIAS workshop in Dortmund this November! I will be hosting a session on foundation models / AI. globias.org/activities/glo…

Learn more here: arxiv.org/abs/2606.21605 Thanks to Marei for leading this work!

How can we use foundation models such as (micro)SAM to improve electron microscopy segmentation? Check out our preprint! We found substantial improvements for nucleus, mito, and neurite-segmentation using initialization and semi-supervised learning with foundation models.

We are so behind in Europe that our fanfic version of AI 2027 drops a year later and is only Europe 2031.

Did it actually answer someone what a mitochondrion is 😱😱😱

i need someone at @OpenAI and @AnthropicAI to teach the models that while prototyping, backwards compatibility is just a bad idea

Sorry to break the news, but the job of twitter hypeman was automated a few years ago already.

🔬 Imaging Seminar on Vision Foundation Models for Microscopy with Prof. Constantin Pape (@cppape) from University of Göttingen 📅 Mar 30, 17:00 👉 Registration: lnkd.in/ej6iCuPA 💡 EPFL PhDs: Imaging Lunch w/ Prof. Pape 📅 Mar 31, 10:00 👉 lnkd.in/exemA5hW

Looking for a PhD position at the intersection of AI, imaging, and gene therapy? Apply for this position in my lab: tinyurl.com/2a2v6tvx Part of sfb1690.uni-goettingen.de that studies hearing, vision, and more. Plus, you can create pretty pictures like the one below :).

🚀 Today we’re releasing FlashOptim: better implementations of Adam, SGD, etc, that compute the same updates but save tons of memory. You can use it right now via `pip install flashoptim`. 🚀 arxiv.org/abs/2602.23349 A bunch of cool ideas make this possible: [1/n]

I'm looking for a Swiss department to host me for an SNSF StG. I research how gene expression evolves and emerges by combining wet lab + computational work in a variety of model systems. More: timothyfuqua.com If your department might be a match, let’s chat!

Retweeting as an AC: Please sumbit your CVPR reviews ;)

The #CVPR2026 review deadline is fast approaching: January 12, 2026. If you face any difficulties, contact your Area Chair NOW! Approach your reviews the way you would expect your own to be handled, and consult the reviewer guidelines here: cvpr.thecvf.com/Conferences/20…

OK can you guys please dedicate even half the energy you collectively use critiquing Empire of AI to also critique the massive work of harmful pseudoscience by Yud and Soares that was also a NYT Bestseller

This work was an excellent collaboration with the group of Tobias Moser, building on the cutting edge light-sheet microscopy of the Huisken lab. Special thanks to Lennart, Aleyna, Elisabeth, and Martin! If you want to use CochleaNet, check out github.com/computational-…

We comprehensively evaluate our method and use it to analyze intact mouse and gerbil cochleae, including SGN sub-types, and to validate (opto-)genetic therapies preclinically (see screenshot). CochleaNet is also applicable to lower-resolution data from commercial systems.

Preprint alert! CochleaNet, our framework for analyzing cochlear light-sheet data. It consists of three networks to segment spiral ganglion neurons, inner hair cells, and detect synapses. Rendering of a full cochlea below, find the preprint at doi.org/10.1101/2025.1…