DeepBacs – Escherichia coli bright field segmentation dataset

Training and test images of live E. coli cells imaged under bright field for the task of segmentation.

Additional information can be found on this github wiki.

The example shows a bright field image of live E. coli cells and the manually annotated segmentation mask.

Data type: Paired bright field and segmented mask images 

Microscopy data type: 2D bright field images recorded at 1 min interval

Microscope: Nikon Eclipse Ti-E equipped with an Apo TIRF 1.49NA 100x oil immersion objective

Cell type: E. coli MG1655 wild type strain (CGSC #6300).

File format: .tif (8-bit)

Image size: 1024 x 1024 px² (79 nm / pixel), 19/15 individual frames (training/test dataset)

1024 x 1024 px² (79 nm / pixel), 9 regions of interest with 80 frames @ 1 min time interval (live-cell time series)

Image preprocessing: Raw images were recorded in 16-bit mode (image size 512 x 512 px² @ 158 nm/px). Images were upscaled with a factor of 2 (no interpolation) to enable generation of higher-quality segmentation masks. Two sets of mask images are provided: RoiMaps for instance segmentation using e.g. StarDist or binary images for CARE or U-Net.

Author(s): Christoph Spahn^1,2, Mike Heilemann^1,3

Contact email: christoph.spahn@mpi-marburg.mpg.de

Affiliation(s): 

1) Institute of Physical and Theoretical Chemistry, Max-von-Laue Str. 7, Goethe-University Frankfurt, 60439 Frankfurt, Germany

2) ORCID: 0000-0001-9886-2263 

3) ORCID: 0000-0002-9821-3578