TITAN: A Multimodal AI Model for Digital Pathology Slides Researchers at #HelmholtzMunich, in collaboration with Harvard Medical School & international partners, have developed #TITAN – a multimodal #AI model that analyzes and describes digital #pathology slides. 👉 t1p.de/sz1wt #FoundationModel

I wrote a paper with @lorenzlamm.bsky.social, @marionjasnin.bsky.social, @tingyingpeng.bsky.social, F. Eckardt and B. Schworm and got accepted at #NeurIPS2025 and fun fact: 90% of viewers are enby vegans! 🤟 So if u fit there, u might wanna check it out! Maybe also if you don't. We're allies here <3

Randomized-MLP Regularization Improves Domain Adaptation and Interpretability in DINOv2

Vision Transformers (ViTs), such as DINOv2, achieve strong performance across domains but often repurpose low-informative patch tokens in ways that reduce the interpretability of attention and feature...

arxiv.org

We’ve updated our powerful MemBrain-seg tool for CryoET membrane segmentation! Plus, we’re introducing two new tools: MemBrain-pick for particle picking and MemBrain-stats for statistical analysis. Feedback is warmly welcome!

Lorenz Lamm@lorenzlamm.bsky.social · last yr.

🦠🧠 MemBrain update! 🧠🦠 We’ve updated our preprint! It now covers the full MemBrain v2 pipeline for end-to-end membrane analysis in #CryoET: segmentation, particle picking, and spatial statistics. 🔗 Preprint: doi.org/10.1101/2024... 🔗 Code: github.com/CellArchLab/... 🧵(1/6) #TeamTomo