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@ARTICLE{Seiffarth:917518,
      author       = {Seiffarth, Johannes and Scherr, Tim and Wollenhaupt,
                      Bastian and Neumann, Oliver and Scharr, Hanno and Kohlheyer,
                      Dietrich and Mikut, Ralf and Nöh, Katharina},
      title        = {{O}bi{W}an-{M}icrobi: {OMERO}-based integrated workflow for
                      annotating microbes in the cloud},
      journal      = {bioRxiv},
      reportid     = {FZJ-2023-00731},
      pages        = {4},
      year         = {2022},
      abstract     = {Reliable deep learning segmentation for microfluidic
                      live-cell imaging requires comprehensive ground truth data.
                      ObiWan-Microbi is a microservice platform combining the
                      strength of state-of-the-art technologies into a unique
                      integrated workflow for data management and efficient ground
                      truth generation for instance segmentation, empowering
                      collaborative semi-automated image annotation in the cloud.},
      cin          = {IBG-1 / IAS-8},
      cid          = {I:(DE-Juel1)IBG-1-20101118 / I:(DE-Juel1)IAS-8-20210421},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / 2171 - Biological and
                      environmental resources for sustainable use (POF4-217)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(DE-HGF)POF4-2171},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.1101/2022.08.01.502297},
      url          = {https://juser.fz-juelich.de/record/917518},
}