Segmentation and track-analysis in time-lapse imaging of bacteria
2016 (English)In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 10, no 1, 174-184 p.Article in journal (Refereed) Published
In this paper, we have developed tools to analyze prokaryotic cells growing in monolayers in a microfluidic device. Individual bacterial cells are identified using a novel curvature based approach and tracked over time for several generations. The resulting tracks are thereafter assessed and filtered based on track quality for subsequent analysis of bacterial growth rates. The proposed method performs comparable to the state-of-the-art methods for segmenting phase contrast and fluorescent images, and we show a 10-fold increase in analysis speed.
Place, publisher, year, edition, pages
2016. Vol. 10, no 1, 174-184 p.
E. coli; microscopy; segmentation; time-lapse; tracking
Bioinformatics (Computational Biology)
Research subject Computerized Image Processing
IdentifiersURN: urn:nbn:se:uu:diva-265457DOI: 10.1109/JSTSP.2015.2491304ISI: 000369495900015OAI: oai:DiVA.org:uu-265457DiVA: diva2:865757
FunderSwedish Research Council, 2012-4968EU, European Research Council, 616047eSSENCE - An eScience Collaboration