Austin E. Y. T. Lefebvre
@austin-lefebvre.bsky.social
210 followers 200 following 26 posts
Dr. Leafbeaver, DS at Calico. You can't spell imaging without "im aging" and boy am I. Organelle enthusiast. Creator of Nellie and Mitometer.
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austin-lefebvre.bsky.social
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

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austin-lefebvre.bsky.social
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!
Careers - Calico
www.calicolabs.com
Reposted by Austin E. Y. T. Lefebvre
austin-lefebvre.bsky.social
This is definitely my favorite response yet haha, my favorite movie of the year!
austin-lefebvre.bsky.social
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.
austin-lefebvre.bsky.social
Thanks for the post! Hope everyone finds it useful. And don’t hesitate to reach out if you have any questions or issues!
Reposted by Austin E. Y. T. Lefebvre
natmethods.nature.com
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...
austin-lefebvre.bsky.social
Great collection. Thanks for including Nellie!!
Reposted by Austin E. Y. T. Lefebvre
ritastrack.bsky.social
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!
austin-lefebvre.bsky.social
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

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austin-lefebvre.bsky.social
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

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austin-lefebvre.bsky.social
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.

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austin-lefebvre.bsky.social
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.

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austin-lefebvre.bsky.social
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.

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austin-lefebvre.bsky.social
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.

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austin-lefebvre.bsky.social
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.

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austin-lefebvre.bsky.social
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!

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austin-lefebvre.bsky.social
And just for fun, here's me walking around, masked by Meta's Segment Anything Model and tracked via Nellie's tracking pipeline

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austin-lefebvre.bsky.social
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!

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