Synthetic micrographs of bacteria (symbac) allows accurate segmentation of bacterial cells using deep neural networks

HIGHLIGHTS

• who: Georgeos Hardo from the Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, UK have published the research: Synthetic Micrographs of Bacteria (SyMBac) allows accurate segmentation of bacterial cells using deep neural networks, in the Journal: (JOURNAL)
• what: In Fig 1b, the authors show the overall process of generating synthetic training data for bacterial cells growing in microfluidic linear colonies, which is SyMBac`s primary use in this paper. The authors provide example notebooks of training deep-learning segmentation networks, such as DeLTA and Omnipose with SyMBac data, and notebooks for using one`s . . .
  

   

  

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