Abstract
Fluorescence microscopy is an essential tool to examine hostpathogen interactions such as the influence of Fascin on cell-cell contacts between infected and uninfected cells. Manual analysis of fluorescence microscopy images is prone to errors leading to inter- and intra-observer variability. To increase reproducibility and objectivity, automated and semi-automated image processing methods are required. For a reliable segmentation of touching and overlapping cells, we propose an active contours algorithm extended by an energy term based on an active shape model. The algorithm is evaluated on confocal cell image data labeled by a human expert.
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References
Meijering E. Cell segmentation: 50 years down the road [life sciences]. IEEE Signal Processing Mag. 2012;29(5):140–5.
Wiesmann V, Franz D, Held C, et al. Review of free software tools for image analysis of fluorescence cell micrographs. J Microsc. 2015;257(1):39–53.
Kress AK, Kalmer M, Rowan AG, et al. The tumor marker fascin is strongly induced by the tax oncoprotein of HTLV-1 through NF-κB signals. Blood. 2011;117(13):3609–12.
Kishore M, Arnaud G, Paul C, et al. An Optimized N-Dimensional Hough Filter for Detecting Spherical Image Objects; 2015. Available from: http://hdl.handle.net/10380/3129.
Kass M, Witkin A, Terzopoulos D. Snakes: active contour models. Int J Computer Vis. 1988;1(4):321–31.
Cootes TF, Taylor CJ, Cooper DH, et al. Active shape models: their training and application. Comput Vis Image Underst. 1995;61(1):38–59.
Held C, Nattkemper T, Palmisano R, et al. Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis. J Pathol Inf. 2013;4(Suppl).
Wiesmann V, Reimer D, Franz D, et al. Automated high-throughput analysis of B cell spreading on immobilized antibodies with whole slide imaging. Curr Dir Biomed Eng. 2015;1(1):224–7.
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Wiesmann, V., Groß, C., Franz, D., Thoma-Kreß, A., Wittenberg, T. (2016). Combining Active Contours and Active Shapes for Segmentation of Fluorescently Stained Cells. In: Tolxdorff, T., Deserno, T., Handels, H., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2016. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49465-3_23
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DOI: https://doi.org/10.1007/978-3-662-49465-3_23
Publisher Name: Springer Vieweg, Berlin, Heidelberg
Print ISBN: 978-3-662-49464-6
Online ISBN: 978-3-662-49465-3
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