Annotated pixels from brightfield images from yeast cell in microfluidic traps - Training and Test sets - DetecDiv (id02)

This dataset has been generated by manual segmentation from timelapse images of yeast cells dividing using the DetecDiv software (see below).

It contains ~1950 raw images (folder "images") associated with their mask (folder "labels") with 3 classes of pixels according to their value on the mask image, "1. background", "2. mother", "3. other".

A splitSets.mat indicates which images have been used for training or for testing.

It is related to the trained network doi.org/10.5281/zenodo.5553851 from the software DetecDiv: github.com/gcharvin/DetecDiv

biorxiv.org/content/10.1101/2021.10.05.463175v1

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Data type: 2D microscopy images (brightfield) (.tif) + mask image (.tif)

Microscopy data type: Brightfield images

Imaging: 20x 0.45 NA brightfield, 6.5µm*6.5µm sCMOS

Cell type: Budding yeast wild type cell (BY4742)

File format: .tif (16-bit RGB, 1 color per z-stack) + .mat

Image size: Brightfield: 60x60x1 (Pixel size: x,y: 325 nm) // Mask: 60x60x1 (Pixel size: x,y: 325 nm), 3 pixel values (one per class).

Author(s): Théo, ASPERT

Contact email: theo.aspert@gmail.com

Affiliation: IGBMC, Université de Strasbourg

Funding bodies: This work was supported by the Agence Nationale pour la Recherche, the grant ANR-10-LABX-0030-INRT, a French State fund managed by the Agence Nationale de la Recherche under the frame program Investissements d'Avenir ANR-10-IDEX-0002-02.