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 https://t.co/UUVmhiNfYv

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

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.

Cochleae were cleared, stained and imaged with a high-resolution light-sheet microscope ( https://t.co/oMZYE6g9sf). After preprocessing,we segment and analyze the data with CochleaNet, using the three dedicated networks trained on newly annotated data.

Any arivis experts here that could help with opening an old .sis file? See

We are hiring the second cohort of EvoReSt PhD students. If you are interested in deep evolutionary questions, checkout: https://t.co/WrbZvDY09k Apply here: https://t.co/kT0XRhzpbX

I just published a video showing how to use Pixi and Napari-Easy-Augment-Batch-DL for reproducible deep learning segmentation. In this example, I use Pixi to set up a Python environment then launch Napari to explore and compare Cellpose3 and Micro-SAM.

Looking for an opportunity to work on cutting super-resolution microscopy and AI? There's still time to apply to the two positions!

4th paper with my brother @AbedShaib. Second on AI. A shared path with our PhD supervisor Ute, who supervised me during my PhD & now supervises him. Proud of this new publication in @NatureComms. A big thank u to our Editor @sgqcheng & our collaborators! https://t.co/RDER8U6kp3

Really excited to share this Perspective from John Danial covering how technology is moving the field of fluorescence microscopy toward structural biology.

The science cuts are affecting incredibly important research. I am very sorry for Uri and the academic landscape in the US in general.

Our goal is to develop methods to understand the dynamics of biomolecules, using the latest developments in super-resolution microscopy and AI-based image analysis. Apply here: https://t.co/UIsoAWNlPO https://t.co/kMm0KEYXHw

Are you looking for an exciting position at the intersection of super-resolution microscopy and AI? Then check out the PhD and PostDoc position we offer for a joint project with the Group of Stephan Hell at MPI Göttingen. Please RT, read on for links and details.

I shared my thoughts in a @NatureMedicine comment on the urgent need for more standardized benchmarks in #AI for biomedicine. https://t.co/p3NBfXEqGk

A thread of thoughts on radiance fields, from my keynote at 3DV: Radiance fields have had 3 distinct generations. First was NeRF: just posenc and a tiny MLP. This was slow to train but worked really well, and it was unusually compressed --- The NeRF was smaller than the images.

Media can actually boost your child's language learning! The secret? Simply talk to them about what they watched. Include natural language variability, just like in everyday conversations. Prof. Mani @nivedita_mani from @uniGoettingen shares interesting facts and tricks for

For the full documentation of micro-sam head to https://t.co/7NffPExb6c. Also a big shoutout to @AnwaiArchit for the work on this release.

3. The model selection now supports two additional models (Histopathology, Medical Imaging) and uses human readable names, see the screenshot below. For more on these models check out: https://t.co/T2WrapDKqk

2. We added preliminary support for automatic tracking via trackastra, developed by @martweig. See the video for an example result and check out https://t.co/ul41LQtklT for details.