Published October 5, 2021 | Version v1
Dataset Open

DeepBacs – Bacillus subtilis fluorescence segmentation dataset

  • 1. Centre for Bacterial Cell Biology, Biosciences Institute, Newcastle University, NE2 4AX UK

Description

Training and test images of live B. subtilis cells expressing FtsZ-GFP for the task of segmentation.

Additional information can be found on this github wiki.

The example shows the fluorescence widefield image of live B. subtilis cells expressing FtsZ-GFP and the manually annotated segmentation mask.

 

Data type: Paired fluorescence and segmented mask images

Microscopy data type: 2D widefield images (fluorescence) 

Microscope: Custom-built 100x inverted microscope bearing a 100x TIRF objective (Nikon CFI Apochromat TIRF 100XC Oil); images were captured on a Prime BSI sCMOS camera (Teledyne Photometrics)

Cell type: B. subtilis strain SH130 grown under agarose pads

File format: .tiff (8-bit) or .png (8-bit)

For segmented masks, binary masks are used for training of CARE/U-Net models, 8-bit .tif ROI maps for training of StarDist models and .png images for training of pix2pix models

Image size: 1024 x 1024 px² (Pixel size: 65 nm)

Image preprocessing: Images were denoised using PureDenoise and resulting 32-bit images were converted into 8-bit images after normalizing to 1% and 99.98% percentiles. Images were manually annotated using the Labkit Fiji plugin

 

Author(s): Mia Conduit1,2, Séamus Holden1,3

Contact email: Seamus.Holden@newcastle.ac.uk

 

Affiliation:

1) Centre for Bacterial Cell Biology, Biosciences Institute, Newcastle University, NE2 4AX UK

2) ORCID: 0000-0002-7169-907X

 

 Associated publications: Whitley et al., 2021, Nature Communications, https://doi.org/10.15252/embj.201696235

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A_Segmentation_B.subtilis_inset.png

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