Zusammenfassung
Single cell tracking emerged as one of the fundamental experimental techniques over the past years in basic life science research. Though a large number of automated tracking methods has been introduced, they are still lacking the accuracy to reliably track complete cellular genealogies over many generations. Manual tracking on the other hand is tedious and slow. Semi-automated approaches to cell tracking are a good compromise to obtain comprehensive information in feasible amounts of time. In this work, we investigate the efficacy of different interaction paradigms for manual correction and processing of precomputed tracking results and present a respective tool that implements those strategies.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Literatur
Eilken HM, Nishikawa SI, Schroeder T. Continuous single-cell imaging of blood generation from haemogenic endothelium. Nature. 2009;457(7231):896–900.
Rieger MA, Hoppe PS, Smejkal BM, et al. Hematopoietic cytokines can instruct lineage choice. Science (New York). 2009;325(5937):217–8.
Schindelin J, Arganda-Carreras I, Frise E, et al. Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012;9(7):676–82.
Schneider CA, Rasband WS, Eliceiri KW. NIH image to ImageJ: 25 years of image analysis. Nat Methods. 2012; p. 671–5.
Schroeder T. Long-term single-cell imaging of mammalian stem cells. Nat Methods. 2011;8(4 s):S30–5.
de Chaumont F, Dallongeville S, Chenouard N, et al. Icy: an open bioimage informatics platform for extended reproducible research. Nat Methods. 2012;9(7):690–6.
Klein J, Leupold S, Biegler I, et al. TLM-Tracker: software for cell segmentation, tracking and lineage analysis in time-lapse microscopy movies. Bioinformatics. 2012;28(17):2276–7.
Rapoport DH, Becker T, Madany Mamlouk A, et al. A novel validation algorithm allows for automated cell tracking and the extraction of biologically meaningful parameters. PLoS ONE. 2011;6(11):e27315.
Burek P, Herre H, Roeder I, et al. Towards a cellular genealogy ontology. IMISE Reports. 2010;2:59–63.
Poli R, Healy M, Kameas A, editors. Theory and Applications of Ontology: Computer Applications. Dordrecht: Springer Netherlands; 2010.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Scherf, N. et al. (2013). Assisting the Machine Paradigms for Human-Machine Interaction in Single Cell Tracking. In: Meinzer, HP., Deserno, T., Handels, H., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2013. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36480-8_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-36480-8_22
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36479-2
Online ISBN: 978-3-642-36480-8
eBook Packages: Computer Science and Engineering (German Language)