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Reposted by Austin E. Y. T. Lefebvre

Alfred Millett-Sikking @amsikking.bsky.social · 20/07/2026

Ultrafast 3D imaging just got faster! Introducing: "Instant dual-view Snouty (iDV-Snouty) light-sheet microscopy" -> Double the data rate of a Snouty microscope by adding a 2nd view! Use the extra view for a variety of imaging modes! Article here: amsikking.github.io/idv-snouty_l...

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 06/05/2025

I’m hiring for a microscopy image analysis role at Calico! www.calicolabs.com/careers/?gh_... We’re looking for someone at ~recent PhD lvl who has previous experience with biological samples and analyzing microscopy datasets. Feel free to reach out with any questions!

calicolabs.com

Careers - Calico

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Reposted by Austin E. Y. T. Lefebvre

Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

Analyzing organelles is HARD. They're complex, but critical to understanding biology. Current tools are manual, organelle-specific, or can't handle large 3D datasets. With an easy install and a click of a button, Nellie solves ALL these problems! nature.com/articles/s41... 🧵2/N

nature.com

Nellie: automated organelle segmentation, tracking and hierarchical feature extraction in 2D/3D live-cell microscopy - Nature Methods

Nellie is a comprehensive automated pipeline for studying the structure and intracellular dynamics of diverse organelles that offers accurate segmentation, tracking and feature extraction on both 2D a...

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 10/03/2025

This is definitely my favorite response yet haha, my favorite movie of the year!

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 10/03/2025

Already some cool applications for Nellie: If you're used to MitoGraph data and want some of the same outputs from Nellie, check out Gav's Python code.

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 06/03/2025

Thanks for the post! Hope everyone finds it useful. And don’t hesitate to reach out if you have any questions or issues!

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Reposted by Austin E. Y. T. Lefebvre

Nature Methods @natmethods.nature.com · 06/03/2025

From Lefebvre and colleagues, Nellie is a comprehensive automated pipeline for studying the structure and intracellular dynamics of diverse organelles that offers accurate segmentation, tracking and feature extraction on both 2D and 3D data. www.nature.com/articles/s41...

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 03/03/2025

Great collection. Thanks for including Nellie!!

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Reposted by Austin E. Y. T. Lefebvre

Rita Strack @ritastrack.bsky.social · 28/02/2025

We spend a lot of time thinking about segmenting cells, but organelles represent a similarly important challenge that is tricky due to their diversity in shapes and sizes. Please check out Nellie, a generalist tool for segmenting AND TRACKING organelles!

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

Try and share Nellie today! We've included some sample data if you want to explore what Nellie can do. Code: github.com/aelefebv/nel... Paper: nature.com/articles/s41... And please share your results with us! We're excited to see how you'll use it in your research. 🧵Fin/N

github.com

GitHub - aelefebv/nellie: Nellie: Automated organelle segmentation, tracking, and hierarchical feature extraction in 2D/3D live-cell microscopy

Nellie: Automated organelle segmentation, tracking, and hierarchical feature extraction in 2D/3D live-cell microscopy - aelefebv/nellie

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

We also compare Nellie to existing state of the art methods for both segmentation and tracking across imaging resolution, structure widths, and structure lengths, as well as the pipeline's speed on different sized images 🧵14/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

Now we can generate flow fields and get cool metrics, like if fields are diverging from (fission?) or converging to (fusion?) a point, or whether a branch is rotating along its long axis (?? dancing?). All of this, and much much more, linked to our organellar hierarchy. 🧵13/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

From these beacons, we can use a distance and cost-weighted interpolation to generate tracks for any coordinate within our organelles! Even at a sub-voxel level. We can use this to link voxels (and thus objects) between temporal frames too. 🧵12/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

We generate internal motion capture markers (think Hollywood) and pattern match these markers between frames to create beacons that point the way for the actual tracking. This means that we don't have to rely on finicky segmentations or skeletons for tracking. 🧵11/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

Then Nellie breaks down the organelles into connected components, and uses its skeleton to break it down even further into branches, which break down into individual nodes, which are variable-range containers for surrounding voxels. A big hierarchical organelle tree. 🧵10/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

So how does Nellie actually work? First Nellie figures out your image's metadata. Then it applies an automated structural-enhancement regime (modified Frangi filter + others) to make those organelles pop. 🧵9/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

Before deep-diving into Nellie, shout out my co-authors: @gavsturm.bsky.social , for help on all the paper, experiments, and testing, and to the other co-authors @kayleyhake.bsky.social, Ben, Emily, Magdalena, and Molly. And of course @ritastrack.bsky.social for being a great editor! 🧵8/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

And just for fun, here's me walking around, masked by Meta's Segment Anything Model and tracked via Nellie's tracking pipeline 🧵7/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

We used Nellie to unmix multiple organelles from a single fluorescence channel with high accuracy using just their morphology and motility patterns with a standard (random forest) classifier. More fluorescence channels for your experiments! 🧵6/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

We also analyzed the intracellular ER highways using Nellie's outputs, allowing us to understand organellar rearrangements using its topology from the perspective of graph theory 🧵5/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

Inspired by Google Deepmind's weather forecasting model GraphCast, we also developed an organelle graph autoencoder using Nellie's outputs to analyze mitochondrial networks' responses to ionomycin treatment, revealing complex dynamics invisible to traditional analysis 🧵4/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

Nellie is FULLY automated with NO parameters to tune, and works on ALL structures - from mitochondria to ER to microtubules and beyond (credit to @andrewgyork.bsky.social and @amsikking.bsky.social 's Snouty SOLS microscope for the data, and @alisterburt.bsky.social for the Animation plugin) 🧵3/N

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

nature.com

Nellie: automated organelle segmentation, tracking and hierarchical feature extraction in 2D/3D live-cell microscopy - Nature Methods

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Austin E. Y. T. Lefebvre @austin-lefebvre.bsky.social · 27/02/2025

Do you LOVE organelles?? Well I am THRILLED to announce that Nellie has been published in @naturemethods.bsky.social! Nellie a fully automated pipeline for organelle segmentation, tracking, and hierarchical feature extraction in 2D, 3D, timelapse, multichannel live-cell microscopy 🧵1/N

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Reposted by Austin E. Y. T. Lefebvre

Juan C. Landoni @jclandoni.bsky.social · 23/12/2024

Stoked to share TWO preprints on mitochondrial pearling! 🎉 We uncover how spontaneous #mitochondria pearling drives #mtDNA nucleoid distribution (doi.org/10.1101/2024...), and @gavsturm.bsky.social et al. dissect the biophysics behind it (doi.org/10.1101/2024...). Details below! 🔬🧵🧪

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