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Data for - Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics

Seiffarth, Johannes; Blöbaum, Luisa; Löffler, Katharina ORCID iD icon 1; Scherr, Tim ORCID iD icon 1; Grünberger, Alexander ORCID iD icon; Scharr, Hanno; Mikut, Ralf ORCID iD icon 1; Nöh, Katharina
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)

Abstract:

Large-scale Corynebacterium glutamicum data set with Segmentation and Tracking Annotation


We provide five time-lapse sequences with manually corrected segmentation and tracking annotations of growing C. glutamicum cultivations. The dataset contains more than 1.4 million cell observations in 29k cell tracks and 14k cell divisions. We provide videos of the annotations (videos.zip) and the dataset in Cell Tracking Challenge format (ctc_format.zip). In the videos, cell contours are rendered in yellow, cell links between frames are colored red and cell divisions, and their links are colored in blue.


Data Acquisition


Corynebacterium glutamicum ATCC 13032 was cultivated in BHI-medium at 30°C in this study. From and overnight preculture, the main culture was inoculated the next day with a starting OD600 of 0.05 and grown at 120 rpm to a OD600 of 0.25. A chip was fabricated, according to (Täuber et al., 2020), and fixed to the microscope’s holder. The main culture cells were transferred to monolayer growth chambers (height = 720 nm) on the microfluidic chip. Flow through the microfluidic device was mediated by pressure driven pumps with a pressure of 100 mbar on the medium reservoir.
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Originalveröffentlichung
DOI: 10.5281/zenodo.7260136
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Forschungsdaten
Publikationsjahr 2022
Identifikator KITopen-ID: 1000183586
HGF-Programm 47.14.02 (POF IV, LK 01) Information Storage and Processing in the Cell Nucleus
Lizenz Creative Commons Namensnennung 4.0 International
Schlagwörter tracking, microbial tracking, cell tracking, live-cell imaging, cell tracking challenge, cell segmentation
Art der Forschungsdaten Dataset
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