Twinnetworkdataset014

doi:doi:10.48606/72

Twinnetworkdataset014

Other: The data comprises bright-field time-lapse images of zebrafish embryos acquired in multiple batches within multi-well plates using an Acquifer Imaging Machine. Embryos from incrosses of Tg(sebox:EGFP) zebrafish strains were used for imaging. Imaging started with embryos between 1.5-2.5 hpf and ended with embryos between 26.5-27.5 hpf. Images of embryos were acquired at 600 acquisition time points with a time interval of 150 s between each acquisition time point. Individual embryo segments were identified and extracted using a trained neural network for object detection. Within this experiment folder, data are organized by microscope position and embryo number.

BibTex:

@dataset{Toulany_Nikan_2023,
    abstract = {Other: The data comprises bright-field time-lapse images of zebrafish embryos acquired in multiple batches within multi-well plates using an Acquifer Imaging Machine. Embryos from incrosses of Tg(sebox:EGFP) zebrafish strains were used for imaging. Imaging started with embryos between 1.5-2.5 hpf and ended with embryos between 26.5-27.5 hpf. Images of embryos were acquired at 600 acquisition time points with a time interval of 150 s between each acquisition time point. Individual embryo segments were identified and extracted using a trained neural network for object detection. Within this experiment folder, data are organized by microscope position and embryo number.},
    author = {Toulany, Nikan},
    doi = {10.48606/72},
    institution = {RADAR},
    keyword = {'Twin Network', 'TwinNet', 'computational biology', 'deep learning', 'developmental biology', 'embryogenesis', 'zebrafish'},
    title = {Twinnetworkdataset014},
    url = {https://service.tib.eu/ldmservice/vdataset/rdr-doi-10-48606-72},
    year = {2023}
}