Anzeige
Erschienen in:
2017 | OriginalPaper | Buchkapitel
Systematic Analysis of Jurkat T-Cell Deformation in Fluorescence Microscopy Data
verfasst von : Sven-Thomas Antoni, Omar M. F. Ismail, Daniel Schetelig, Björn-Philipp Diercks, René Werner, Insa M. A. Wolf, Andreas H. Guse, Alexander Schlaefer
Erschienen in: Bildverarbeitung für die Medizin 2017
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In the adaptive immune system, Calcium (Ca2+) is acting as a fundamental on-switch. Fluorescence microscopy is used to study the underlying mechanisms. However, living cells introduce motion and for the analysis of (sub-)cellular Ca2+ activity a precise motion analysis is necessary. We present an image based workflow to detect and analyze cell motion. We evaluate our approach on Jurkat T-cells using cell motion as observed from actual time series of cell images. Results indicate, that our method is able to detect deformation with an error of 0.2222 ± 0.086μm which is in the range of the image resolution, showing that accurate cell deformation detection is possible and feasible.