Constantin Pape
@cppape.bsky.social
Group leader @ Uni Göttingen for Computational Cell Analytics. Working on AI for biology and medicine with a focus on microscopy image analysis with deep learning.
https://user.informatik.uni-goettingen.de/~pape41/
https://user.informatik.uni-goettingen.de/~pape41/
This work was an excellent contribution with the group of Tobias Moser, building on the cutting edge light-sheet microscopy of @huiskenlab.bsky.social. Special thanks to Lennart, Aleyna, Elisabeth, and Martin!
If you want to use CochleaNet, check out github.com/computationa...
If you want to use CochleaNet, check out github.com/computationa...
GitHub - computational-cell-analytics/cochlea-net: Deep learning-based image analysis for cochleae imaged in light-sheet microscopy
Deep learning-based image analysis for cochleae imaged in light-sheet microscopy - computational-cell-analytics/cochlea-net
github.com
November 18, 2025 at 7:59 AM
This work was an excellent contribution with the group of Tobias Moser, building on the cutting edge light-sheet microscopy of @huiskenlab.bsky.social. Special thanks to Lennart, Aleyna, Elisabeth, and Martin!
If you want to use CochleaNet, check out github.com/computationa...
If you want to use CochleaNet, check out github.com/computationa...
We comprehensively evaluate our method and then use it to analyze the morphlogy of 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.
November 18, 2025 at 7:59 AM
We comprehensively evaluate our method and then use it to analyze the morphlogy of 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 (recently published: doi.org/10.1038/s415...). After preprocessing,we segment and analyze the data with CochleaNet, using the three dedicated networks trained on newly annotated data.
November 18, 2025 at 7:59 AM
Cochleae were cleared, stained and imaged with a high-resolution light-sheet microscope (recently published: doi.org/10.1038/s415...). After preprocessing,we segment and analyze the data with CochleaNet, using the three dedicated networks trained on newly annotated data.
Hope my counter meme convinces you ;)
November 11, 2025 at 6:13 AM
Hope my counter meme convinces you ;)
Once again, I beg you to understand that SINGLE-CHANNEL FLUORESCENCE MICROSCOPY IMAGES DON'T HAVE A COLOR!
November 9, 2025 at 3:13 PM
Once again, I beg you to understand that SINGLE-CHANNEL FLUORESCENCE MICROSCOPY IMAGES DON'T HAVE A COLOR!
And it was published a few weeks ago already, but I was too busy to announce it 😅. Thanks to all co-authors, in particular Sarah and Fidi who did a great job in putting this together. Let us know if you want to try it on your data and run into any issues.
October 17, 2025 at 11:09 AM
And it was published a few weeks ago already, but I was too busy to announce it 😅. Thanks to all co-authors, in particular Sarah and Fidi who did a great job in putting this together. Let us know if you want to try it on your data and run into any issues.
The segmentation functionality and other analysis modes, for example for vesicle pool assignments and distance measurements as shown in the screenshot, are available in a napari plugin. Check out github.com/computationa... for details.
October 17, 2025 at 11:09 AM
The segmentation functionality and other analysis modes, for example for vesicle pool assignments and distance measurements as shown in the screenshot, are available in a napari plugin. Check out github.com/computationa... for details.