One month left 'til @iclr-conf.bsky.social, about time to launch our ✨@gram-org.bsky.social Competititon✨ The theme is geometry x AI4science with a dataset kindly provided by BeyondMath. Deadline: April 22, 2026 (AoE) 🔗 gram-competition.github.io

Thrilled to present our paper "Unintended Memorization of Sensitive Information in Fine-Tuned Language Models" at #EACL2026 in Rabat! 🇲🇦 w/ J. Marin Ruiz, G. Kaissis, P. Seidl, R. v. Eisenhart-Rothe, F. Hinterwimmer & @danielrueckert.bsky.social. Read here: arxiv.org/abs/2601.174...

Our latest paper on ML-based flow estimation ✨trained on 4D flow MRI✨ in the carotid arteries is now published (open-access) in Medical Image Analysis. 🔗 www.sciencedirect.com/science/arti...

January Thesis Highlights from AIM Lab 🎓 To celebrate their hard work, we want to showcase the excellent research our bachelor and master students produce! This month, Florian Braunmiller finished a great master thesis on Mixture-of-Experts (MoE) architectures for medical imaging. 1/n

🦄 Build Europe’s next AI unicorn - @sprind-de.bsky.social Next Frontier AI initiative backs bold ideas with €125M to create European frontier AI labs. Believe Europe should lead in AI? Join the challenge! 👉 next-frontier.ai

Great having Robbie Holland back for a visit at our lab! He’s at AIMI at Stanford University and gave a speech on auto-generated hypotheses in the context of AI4Science. Not only for the lab, but maybe more importantly for our lab‘s seminar on Multi-modal AI for Medicine (IN2107, IN45072). #AIMnews

🎄 Lab Christmas Party! 🎄 It's always great to use the holiday season as an opportunity to (re-)connect! We had a blast at our Christmas party with lots of laughs, pizza, and Glühwein 🍷 Wishing everyone a good end to this year and happiest of holidays to those who celebrate! ✨ #AIMsocial

Great being at #NeurIPS last week! Thankful for the good times in the sun and the people I met. If you’ve ever wondered whether model performance can be inferred directly from your training alone, check out our work! 1/2

It’s this time of the year again! #NeurIPS2025 If you are in San Diego, make sure to check out 2 works from our lab this week 📝📝 #AIMresearch 1/3

Huge congratulations to Paul Hager and Dr. med. Friederike Jungmann for winning the MDSI Best Paper Award in the Societal Impact category! 🏆🎊 See more details in the thread below! Photo's copyright: Andreas Heddergott/TUM #AIMResearch #AIMNews #MDSI #BestPaperAward

We celebrated the 5th anniversary of our research chair at @tum.de! 💙🥂 It's been an incredible journey of research and collaboration. Thank you to everyone who has made this possible. We are very much looking forward to the next years to come! #AIMAnniversary #AIMNews

Quick look back at an insightful day yesterday at the Bavarian Conference on AI in Medicine, where @paulhager.bsky.social , @luciehuang.bsky.social, Alina Dima, and Vasiliki Sideri-Lampretsa were representing us. Team, thank you for being such good ambassadors! 👏 #AIMNews #AIinMedicine

We are wrapping up our 5th-year anniversary paper series with ViTa by Yundi Zhang et al. (www.sciencedirect.com/science/arti...), a work that adresses: How to realize personalized cardiac healthcare that moves beyond a single task? #AIMResearch #AIMAnniversary #MultiModalLearning #CardiacMRI

Is it safe to use LLMs in the clinic today? This is the central question that @paulhager.bsky.social and Friederike Jungmann tackled in their 2024 study published in #NatureMedicine, which is our 5th-year anniversary's highlight paper this week. #AIMAnniversary #AIMResearch #LLM #Benchmark

Last week we had the pleaure of hosting Paul Kaftan (Institute of Medical System Biology, @uniulm.bsky.social) and Steven Jia (Institut de Neurosciences de la Timone, @univ-amu.fr) for talks on the incredible potential of Implicit Neural Representations (INRs) in medical imaging. #AIMnews #INRs

Huge and well-deserved congratulations to Dmitrii Usynin on successfully completing his doctoral journey in our lab! 🎊 Dima’s research has resulted in significant contributions to field of trustworthy artificial intelligence in particular for collaborative biomedical image analysis.

Throwback to 2022! 🕰️ Continuing with our 5th-year anniversary series, we're now revisiting a question we faced at that time: How fast can we reliably see the beating heart in MRI without sacrificing image quality? #AIMAnniversary #AIMResearch #NeuralImplicitRepresentation #CardiacMRI

We are thrilled to announce that Dr. Sevgi Gokce Kafali has been awarded the prestigious Alexander von Humboldt Postdoctoral Fellowship! 🎉 During her fellowship, she will focus on the "Assessment of Cardiac Health through Opportunistic Screening using MRI." Our warmest congratulations! #AIMNews

As our lab's 5th anniversary approaches 🥳, we're kicking off a month-long series of posts highlighting standout papers from our past five years at @tum.de. Join us as we revisit the incredible work that has shaped our journey! #AIMAnniversary #AIMResearch

Submit to our @euripsconf.bsky.social workshop : MedEurIPS - Medical Imaging meets EurIPS sites.google.com/view/medeurips @aasaferagen.bsky.social @benglocker.bsky.social @bernhardkainz.bsky.social @danielrueckert.bsky.social Ender Konukoglu @stsaftaris.bsky.social

The annual conference of the @miccaisociety.bsky.social is in 3 days! 🗓️ Our lab is excited to present 8 papers exploring advancements in AI for medical imaging 🧠🩻 Stop by our posters & presentations to learn more! ➡️ conferences.miccai.org/2025/ Overview of our papers in the thread below 🧵⤵️

🩻 Are you a student at @tum.de and interested in AI and medicine? Make sure to check out our courses for the upcoming winter semester! Practical: Applied Deep Learning in Medicine (IN2106, IN4314) Lecture: Artificial Intelligence in Medicine (IN2403) ...

🚀 Towards cardiac MRI foundation models: Comprehensive visual-tabular representations for whole-heart assessment and beyond. We introduce ViTa, a multi-view, multi-modal, multi-task model for cardiac MRI. 🧵 1/3

🔃 We're moving beyond traditional benchmarking for LLMs. 🚩 Meet Dynamic, Automatic & Systematic (DAS) Red-Teaming from Jiazhen Pan and Bailiang Jian together with great collaborators! #AIMresearch 🧵 1/4

🤔 Ever wondered what a ‘reference brain’ would look like for your own demographic group? @starcksophie.bsky.social and @siderilampretsa.bsky.social, together with some amazing colleagues, have developed a novel diffusion-based approach for this. But how does this work? #AIMresearch 1/3

I am happy to announce that I have started a postdoc position at @aim-lab.bsky.social and @munichcenterml.bsky.social, Technical University of Munich under the supervision of @danielrueckert.bsky.social. Looking forward to this new chapter 🥨🎓

Last week, we had the pleasure of hosting Prof. @clemensdlaska.bsky.social and part of his research team: Nadja Gruber (PhD), Angus Nicolson (PhD), and Riccardo Lunelli. Prof. Dlaska gave a talk on "Digital Cardiology: From Benchmarks to Bedside". #AIMnews #DigitalCardiology

Huge and well-deserved congratulations to Philip Müller on successfully completing his doctoral journey in our lab! 🎊 Philip’s dedication and innovative research have led to significant contributions in localized image-text learning for chest X-rays. scholar.google.com/citations?us...

As part of Daniel Rückert's team, our #PhDcandidate Vasiliki Sideri-Lampretsa uses #AI and high-performance #computing to analyze MRI & CT scans, tracking lung movement and detecting #diseasepatterns: go.tum.de/395577 #clinicalpractice 📷A.Eckert

As of yesterday, our research team gathered for a 4-day work retreat in Obertraun, Austria. It was a fantastic opportunity to connect through meaningful keynotes, strategy sessions, team-building activities, sports, and even a (legendary!) pub quiz. #WorkRetreat #StrategySessions #SocialActivities

We recently had the privilege of hosting George Kaissis as a guest speaker in our Multimodal Deep Learning lecture at @tum.de. George, currently at Google DeepMind, guided us from the first principles to the state of the art in AI video generation. #Teaching #MultimodalDeepLearning

Our PhD students, Alina D. and @luciehuang.bsky.social, are participating in #ICVSS2025. During the poster session, Alina presented her research on parametric shape models of 3D vessels learned from segmentations using differentiable voxelization (arxiv.org/pdf/2507.02576).

One year ago, @martinmenten.bsky.social established the AI for Vision group at our chair. 🎉 Supported by funding from the Emmy Noether Programme of the @dfg.de and the @munichcenterml.bsky.social , the group has since grown to six researchers! 1/2

Groundbreaking ceremony complete for the new Zentrum für Digitale Medizin und Gesundheit (#ZDMG)! This interdisciplinary research center is a major step in further strengthening digital medicine research & developing future clinical approaches @tum.de. 🎉

Pizza + Sunshine + Good Company = Optimal Setting for our lab‘s summer fest today! ☀️🍕 #VitaminD

Responsible medical AI demands patient-level privacy. Our recent #TPDP '25 paper extends Differential Privacy #DP beyond individual data points to protect entire patient profiles. 🧠 📄 Read the paper: tinyurl.com/k9fz456a 🎥 Watch the video: tinyurl.com/2jx528m5

Going to be at CVPR the next couple of days presenting our paper „A Tale of Two Classes: Adapting Supervised Contrastive Learning to Binary Imbalanced Datasets“. arxiv.org/abs/2503.17024 Always happy to meet anyone working on representation learning or tabular DL and medical data

Huge congratulations to Jiazhen on successfully completing his doctoral journey in our lab! 🎉 His work and dedication have resulted in great contributions to cardiac MRI reconstruction for faster and higher-quality imaging. Good luck on your future endeavors, JZ!

If you're at #IPMI in Greece 🇬🇷 right now, make sure to check out 2 works of our group tomorrow, Thursday! Alex and Laurin are discussing pitfalls in their research on topology-aware image segmentation... (1/2) arxiv.org/abs/2412.14619

We are incredibly proud of Prof @danielrueckert.bsky.social for being elected as Fellow of the Royal Society! Well deserved and a testament to your dedication to research 🎉

#ISMRM 2025 took place this week, and here is a brief recap of our PhD students' presentations. 1/n #CardiacMRI #ImplicitNeuralRepresentations #RepresentationLearning

We had the pleasure of hosting Thomas Hadler from Charité - Universitätsmedizin Berlin and Kirsten Maas from @tue.nl in our lab this week. Both gave insightful talks on their research.

Huge congratulations to Felix Meissen on successfully completing his doctoral journey in our lab! 🎉 His hard work and dedication have paid off and represented contributions to medical pathology detection using weak supervision in Machine Learning. We wish him all the best in his future projects.

Are you working with datasets that follow the Brain Imaging Data Structure (BIDS) naming convention? If so, you may want to try TPTBox, a toolbox developed by our PhD students Hendrik Möller and Robert Graf. It offers a wide variety of tools for working with NIfTI files. github.com/Hendrik-code...

Lisa Steinhelfer and Friederike Jungmann found that certain #cancertherapies can cause early #kidneydamage, detectable via #AI-analyzed #CTscans. This allows timely treatment adjustments: go.tum.de/787388 #cancertreatment #kidneyfunction 📷A.Eckert

#ICLR 2025 has concluded, and here is a brief recap of our PhD students' presentations. Alexander Berger and Laurin Lux presented their work on topology-preserving image segmentation, while Johannes Kaiser discussed his work on data attribution. For details, check out our previous two posts.

Data attribution is crucial for debugging models and detecting low quality data (spotting mislabeled samples, bias etc.). But many methods aren't mathematically sound and don’t scale. But how could we improve this for large models? 1/n

Topological accuracy in image segmentation is crucial for many tasks - such as blood flow or functional brain analysis. Yet, most models disregard this structural integrity during training, leading to potential inaccuracies in critical analyses. But how could we address this issue? 1/n

Looking for MRI spine segmentation? Try SPINEPS, a state-of-the-art framework for automatic spine segmentation by our PhD student, Hendrik Möller. It annotates 14 structures both semantically and instance-wise, simplifying downstream analysis. github.com/Hendrik-code...

Excited to share: “A Tale of Two Classes: Adapting Supervised Contrastive Learning to Binary Imbalanced Datasets” has been accepted to #CVPR2025! 🎉 Paper: lnkd.in/esKRqF5p Code: lnkd.in/eZFvDA5Q (Thread incoming 👇)