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@INPROCEEDINGS{Paul:1033892,
      author       = {Paul, Richard D. and Seiffarth, Johannes and Scharr, Hanno
                      and Nöh, Katharina},
      title        = {{R}obust {A}pproximate {C}haracterization of
                      {S}ingle-{C}ell {H}eterogeneity in {M}icrobial {G}rowth},
      publisher    = {IEEE},
      reportid     = {FZJ-2024-06730},
      isbn         = {979-8-3503-1333-8},
      pages        = {1-5},
      year         = {2024},
      abstract     = {Live-cell microscopy allows to go beyond measuring average
                      features of cellular populations to observe, quantify and
                      explain biological heterogeneity. Deep Learning-based
                      instance segmentation and cell tracking form the gold
                      standard analysis tools to process the microscopy data
                      collected, but tracking in particular suffers severely from
                      low temporal resolution. In this work, we show that
                      approximating cell cycle time distributions in microbial
                      colonies of C. glutamicum is possible without performing
                      tracking, even at low temporal resolution. To this end, we
                      infer the parameters of a stochastic multi-stage birth
                      process model using the Bayesian Synthetic Likelihood method
                      at varying temporal resolutions by subsampling microscopy
                      sequences, for which ground truth tracking is available. Our
                      results indicate, that the proposed approach yields high
                      quality approximations even at very low temporal resolution,
                      where tracking fails to yield reasonable results.},
      month         = {May},
      date          = {2024-05-27},
      organization  = {2024 IEEE International Symposium on
                       Biomedical Imaging (ISBI), Athens
                       (Greece), 27 May 2024 - 30 May 2024},
      cin          = {IAS-8 / IBG-1},
      cid          = {I:(DE-Juel1)IAS-8-20210421 / I:(DE-Juel1)IBG-1-20101118},
      pnm          = {2171 - Biological and environmental resources for
                      sustainable use (POF4-217) / 5112 - Cross-Domain Algorithms,
                      Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-2171 / G:(DE-HGF)POF4-5112},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      UT           = {WOS:001305705100163},
      doi          = {10.1109/ISBI56570.2024.10635267},
      url          = {https://juser.fz-juelich.de/record/1033892},
}