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2016 (English)In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 10, no 1, p. 174-184Article in journal (Refereed) Published
Abstract [en]
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.
Keywords
E. coli; microscopy; segmentation; time-lapse; tracking
National Category
Bioinformatics (Computational Biology)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-265457 (URN)10.1109/JSTSP.2015.2491304 (DOI)000369495900015 ()
Projects
eSSENCE
Funder
Swedish Research Council, 2012-4968EU, European Research Council, 616047eSSENCE - An eScience Collaboration
2016-01-212015-10-292018-01-10