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Segmentation and Track-Analysis in Time-Lapse Imaging of Bacteria
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.ORCID iD: 0000-0002-5329-575X
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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, 174-184 p.Article in journal (Refereed) PublishedText
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.

Place, publisher, year, edition, pages
IEEE Communications Society, 2016. Vol. 10, no 1, 174-184 p.
Keyword [en]
E. coli, microscopy, segmentation, time-lapse, tracking
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-183199DOI: 10.1109/JSTSP.2015.2491304ISI: 000369495900015ScopusID: 2-s2.0-84962911002OAI: oai:DiVA.org:kth-183199DiVA: diva2:908899
Funder
Swedish Research Council, 2012-4968EU, European Research Council, 616047
Note

QC 20160303

Available from: 2016-03-03 Created: 2016-03-03 Last updated: 2016-03-03Bibliographically approved

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Magnusson, Klas E. G.Elf, Johan
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ACCESS Linnaeus CentreSignal Processing
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