Published May 17, 2025 | Version v1
Dataset Open

4-channel STED Dataset

Description

Training and testing images associated with the article titled Unmixing Optical Signals from Undersampled Volumetric Measurements by Filtering the Pixel Latent Variables.

The FLIM-STED dataset consists of real microscopy images of fixed neurons from primary cell cultures and acute brain slices. Images of different combinations of four neuronal proteins tagged with fluorescent markers were acquired over large fields of view (width between 8 and 16 μm and height between 45 and 65 μm). The signal from each fluorescent marker was spectrally separated to obtain ground truth unmixed images with four independent channels. 

Pixel size for all images : 20 nm

Training dataset : 3 sets of 10 images with different combinations of 4 proteins.
Testing dataset : 3 sets of 4 images with the same combinations of 4 proteins as the training dataset.

Images 00.tif to 09.tif (training) and 00_test.tif to 03_test.tif (testing) : 
- Channel 1 (Confocal) : Microtubule Associated Protein (MAP2) labeled with ATTO 490LS
- Channel 2 (STED) : Post-Synaptic Density (PSD95) labeled with STAR635P
- Channel 3 (Confocal) : Presynaptic Vesicular Glutamate Transporter (VGLUT1) labeled with Alexa Fluor 488
- Channel 4 (STED) : RNA binding protein Fused in Sarcoma (FUS) labeled with Alexa Fluor 594

Images 10.tif to 19.tif (training) and 04_test.tif to 07_test.tif (testing) :
- Channel 1 (Confocal) : Green Fluorescent Protein (GFP) used as a cytosolic marker
- Channel 2 (Confocal) : Tubulin-Associated Unit (Tau) labeled with ATTO 490LS
- Channel 3 (STED) : Calcium/Calmodulin dependent protein kinase II beta (ꞵCaMKII) labeled with Alexa Fluor 594
- Channel 4 (STED) : F-Actin labeled with Phalloidin STAR635

Images 20.tif to 29.tif (training) and 08_test.tif to 11_test.tif (testing) :
- Channel 1 (Confocal) : Post-synaptic scaffolding protein gephyrin with STAR GREEN
- Channel 2 (STED) : VGLUT1 labeled with Atto490LS
- Channel 3 (STED) : Vesicular GABA transporter (VGAT) labeled with Alexa Fluor 594
- Channel 4 (STED) : PSD95 labeled with a nanobody tagged with Atto643



 

 

Files

00.tif

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Additional details

Funding

Natural Sciences and Engineering Research Council
RGPIN-06704-2019
Fonds de Recherche du Québec – Nature et Technologies
Team Grant 2021-PR-284335
Government of Canada
New Frontiers in Research Fund NFRFE-2020-00933
Canadian Institutes of Health Research
202109PJT-471107-NSB-CFBA-12805
Sentinelle Nord
U.S. National Science Foundation
Neuronex Initiative 2014862

Software

Repository URL
https://github.com/FLClab/LatentUnmixing
Programming language
Python
Development Status
Active