BIA Unit

The BioImage Analysis Unit designs innovative computational methods to address challenging biological questions through rigorous quantitative approaches #Icy

[BIA Unit @BiaUnit]

Dear all,
we and many others from the bioimaging community have moved to Bluesky!
You can now find and follow us @biaunit.bsky.social
See you soon & Happy New Year !!

[Arrate Munoz Barrutia @ArrateMunoz]

THE CELL TRACKING CHALLENGE

2nd Call for Cell Linking Submissions

Deadline: Dec 1st, 2024

More info: https://t.co/WnWaWCzLDv

[GDR ImaBio @GDR_ImaBio]

It starts today !
https://t.co/gsRI5Ots29

#RencontresImabio2024

@CNRS @UGrenobleAlpes

[Arrate Munoz Barrutia @ArrateMunoz]

Watch out! Two of them are published in the latest issue of @naturemethods
🚀Omega: https://t.co/mpXvGdleLa
🤖https://t.co/qmoeoe9Ucc chatbot: https://t.co/jR4qbLNHTU
Warming up! ☀️☀️☀️

[BIA Unit @BiaUnit]

👉See more: https://t.co/KSrLr5bFmL

[BIA Unit @BiaUnit]

🔬 Here are confocal micrographs of amoebae loaded on Fibronectin-coated glass or non-coated glass and labelled for F-actin 💡
👉 We show that E. histolytica adopts a fan-shape morphology on a Fibronectin substrate ‼️
https://t.co/KSrLr5bFmL

[BIA Unit @BiaUnit]

Now available on Scientific Reports https://t.co/YlaiUdT65J

[BIA Unit @BiaUnit]

Hanson A, Reme R, Telerman N, Yamamoto W, Olivo-Marin JC, Lagache T, & Yuste R.

Automatic monitoring of whole-body neural activity in behaving Hydra. bioRxiv, 2023-09.

An open-source platform to monitor neurons’activity in behaving Hydra.

#Hydra #Byotrack #TraseIn #Python #Icy

[Nature Methods @naturemethods]

Out last week from the Tinevez and Olivo-Marin labs! JDLL: a library to run deep learning models on Java bioimage informatics platforms. This is sure to streamline deployment of DL models in bioimaging. https://t.co/KCQLTSBpLE

[Jean-Yves Tinevez @jytinevez]

Super proud of this work and it was done with awesome colleagues. Let's now put this tool to good use!

[Arrate Munoz Barrutia @ArrateMunoz]

Thrilled to announce our latest paper, 'JDLL' is now published in @NatureMethods! A perfect start to the New Year 🥳 and a fantastic gift from the Reyes Magos! 🌟 Check it out here: https://t.co/CfB3xLvczX Happy Reading & Happy New Year to all! 📚🎆
@Icy_BioImaging @deepImageJ

[GDR ImaBio @GDR_ImaBio]

#MiFoBio2023

Diffusion en direct de GDR Imabio - CNRS https://t.co/ny5WzyHqPj via @YouTube

[Carlos García @carlosg91018370]

https://t.co/oNomhtoa8b

[Carlos García @carlosg91018370]

Coming soon to @Icy_BioImaging ...
Run #stardist on your images without code using the https://t.co/y8Hq4GqnAr models.💥💥
Thanks to #JDLL and #appose, we're bringing the power of Deep Learning and Python to the easy-to-use Java world.
Much more is coming!

[Jean-Yves Tinevez @jytinevez]

@Icy_BioImaging (Taken from the BioEngine website.)

[BIA Unit @BiaUnit]

Tracking Intermittent Particles with Self-Learned Visual Features.

R Reme, V Piriou, A Hanson ...

2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 1-5

Using visual features for single-particle tracking in fluorescence imaging.

#Hydra #Byotrack #Python #icy

[BIA Unit @BiaUnit]

Hanson A, Reme R, Telerman N, Yamamoto W, Olivo-Marin JC, Lagache T, & Yuste R.

Automatic monitoring of whole-body neural activity in behaving Hydra. bioRxiv, 2023-09.

An open-source platform to monitor neurons’activity in behaving Hydra.

#Hydra #Byotrack #TraseIn #Python #Icy

[BIA Unit @BiaUnit]

@dpmelters L

[Cell Biology & Infection @BCI_Pasteur]

🔜Next @BCI_Pasteur seminar this Tuesday

Aydogan Ozcan @InnovateUCLA from @UCLAengineering

Deep Learning-enabled Computational Microscopy and Diffractive Imaging

Invited by @BiaUnit

[Icy @Icy_BioImaging]

Following Jean-Yves’ inspiring testimonial @jytinevez, I’m pleased to share some backstory chapters of the JDLL project! While the idea had been brewing in our minds for quite some time, it truly gained momentum during my UC3M Chair of Excellence stay at Arrate's lab @ArrateMunoz in Madrid in fall 2021. It was a stimulating period as Estibaliz @gomez_mariscal had just read her PhD thesis, and their remarkable deepImageJ @deepImageJ paper had been published in Nature Methods, acting as a catalyst for the Icy team to channel their time and energy into deepIcy. We were fortunate that Carlos @carlosg91018370, a talented developer with a wealth of experience in deepImageJ, was both available and keen on pushing the boundaries of Java libraries for deep learning in bioimaging. Collaborating with Stéphane, they embarked on a complete redesign of the initial deepIcy @deepIcy_IP prototype that would become JDLL, incorporating cutting-edge advancements in Java/Python interfaces and more. Now, the rest of the story is in your hands, as we present you with the tools to shape the future of deep learning for bioimaging data analysis. Be creative and have fun!

Jean-Christophe

[Jean-Yves Tinevez @jytinevez]

Quick personal story thread about this work -

A few years ago we were working with Jean-Christophe on a prototype of Icy3. We wanted to get closer to the ImageJ ecosystem, and in particular join the community effort in making Deep-Learning easily accessible to biologists.