The goal of SATOMI is to accelerate the time-to-insight for microbial single-cell analysis. Live-cell imaging unlocks fascinating insights into living bacteria, and, coupled with microfluidic lab-on-chip systems, offers several unique possibilities for microbial research: 

  1. non-invasive monitoring of the dynamic growth of bacterial populations,
  2. studying the evolution of spatio-temporal characteristics of cells and bacterial colonies over long time periods,
  3. the derivation of distributions of ancestral relationships between cells in a populations, and
  4. high-throughput data collection under precise control of the environment. 

Modern set-ups, as those developed and operated at Forschungszentrum Jülich (FZJ), allow the observation of hundreds of cultivation sites in parallel over long observation periods (days to weeks) with an image acquisition every few minutes and several optical configurations. The reliable analysis of the acquired time-lapse images is essential for extracting quantitative single-cell metrics and turning them into biological discovery. Therefore, highly accurate cell segmentation and cell tracking methods are required. The developed SATOMI tools are available at github:



microbeSEG dataset (1.0) [Data set]
Scherr, T.; Seiffarth, J.; Wollenhaupt, B.; Neumann, O.; Schilling, M.; Kohlheyer, D.; Scharr, H.; Mikut, R.; Nöh, K.
2022, April 28. doi:10.5281/zenodo.6497715
microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation
Scherr, T.; Seiffarth, J.; Wollenhaupt, B.; Neumann, O.; Schilling, M. P.; Kohlheyer, D.; Scharr, H.; Nöh, K.; Mikut, R.
2022. (A. Imran, Ed.) PLOS ONE, 17 (11), e0277601. doi:10.1371/journal.pone.0277601
ObiWan-Microbi and microbeSEG: Deep Learning Tools for Microbial Image Analysis
Neumann, O.; Seiffarth, J.; Scherr, T.; Wollenhaupt, B.; Scharr, H.; Kohlheyer, D.; Nöh, K.; Mikut, R.
2022, May 31. Helmholtz Imaging Conference (HIP 2022), Berlin, Germany, May 31–June 1, 2022