Gregor Koehler

🌟 Join us to explore RETFound, a Foundation Model for Ophthalmology, as featured in Nature, with Prof. @pearsekeane. Discover its impact on diverse clinical tasks. 🤖👁️ #AIinHealthcare #FoundationModels #HeidelbergAI 🔗 Details & Registration: heidelberg.ai/2024/02/06/pea…

🌐 Join us for a Special Talk on AI and Infectious Disease Outbreak Prediction with Prof. Joacim Rocklöv, leading Germany's first AI lab in this field. Discover how AI can revolutionize disease surveillance and prediction! 🔗 Details & Registration: heidelberg.ai/2024/01/31/joa…

WACV 2024 has started! Really enjoyed the keynote by @dimadamen on egocentric video understanding. Those datasets seem really cool & worth exploring!

Thanks a ton for awarding me the @PyTorch superhero award at the conference! It really made my day, and it was great seeing so many community members in real life. You all are amazing!

📢 Exciting News! 🎉 I'm thrilled to announce that I'll be presenting my paper "MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation" at #MICCAI2023. Join my oral presentation on Wednesday at 8:15 AM and the poster session at 9:30 AM (Poster W-05-080)

💼 Packing for #ICCV2023 to present the M2T paper :) See you in Paris?

TotalSegmentator v2 is here: - 33 new classes - up to 32x faster runtime on CPU - improved label quality - larger training dataset (n=1559) - uses nnU-Net v2 Details: github.com/wasserth/Total…

Missed our latest heidelberg.ai talk on "Learning dynamical laws from data" by @k__niki? Now you can (re)watch the talk: youtu.be/zevj234NsBM Thanks again Niki for this really nice talk!

🏆Congrats to Luca Deininger for receiving an award for the best oral presentation at this year's "14. Annual Scientific Symposium on Ultrahigh Field Magnetic Resonance"!🌟 #mri #machinelearning #segmentation

We published our dataset (doi.org/10.5281/zenodo…) making it the largest openly available dataset of child brain MRIs aging 0 to 36 months.

3/3 #MICCAI 2023 paper in early accept: “Transformer-driven Scaling of ConvNets for Medical Image Segmentation”. Check out the preprint here: arxiv.org/abs/2303.09975

Here comes @MICCAI_Society 2023 early acceptance paper 1/3 on "Shape-based pose estimation for automatic standard views of the knee". Check out the preprint here: arxiv.org/abs/2305.16717

Was in Germany yesterday to talk about compression and eat pretzels 🥨 Thanks to fraiburg.ai and @jkhfranke for hosting this, it was very exciting!

This is HUGE. Google's new medical LLM, Med-PaLM 2, scored 86.5% on the medical exam MedQA 🤯 Not only that, but a panel of 15 human doctors preferred Med-PaLM 2's answers over real doctor answers across 1066 standardized questions. Does this mean that doctors are going to be replaced? No. But I am a believer that AI combined with human knowledge and experience would make the most powerful duo.

Still in a good mood while our future is currently being decided on by the @helmholtz_image reviewers next door😅.

Shoutout to the legend who answers literally every single PyTorch question out there!

Excited to present some of our work @NeurIPSConf this week. Today at #MedNeurIPS, @TimRaedsch will talk about the importance of labeling instructions (arxiv.org/abs/2207.09899), and @annika_reinke1 will present #MetricsReloaded (arxiv.org/abs/2206.01653).

Markus Bujotzek & Daniel Walther from MIC took part at @CodeWeekEU at @TECHNOSEUM and explained AI to kids and what it has to do with medical image computing - also adults were curious and asked a lot of questions! 🙂 #CodeWeek #YoungScientist

New paper is out with participation from MIC @maierhein @KlausKades @GregorKoe @DataScienceDKFZ

What a performance! 🤯 @DKFZ_CAMI_lab & MIC cycled a total of 9.029,4 km for @STADTRADELN, more than half of entire @DKFZ. 5 people from our labs are in Top10 - kudos to all for this achievement. Keep up the spirit, for cancer prevention and a better climate! #Health #saveco2