A framework for automated cell tracking in phase contrast microscopic videos based on normal velocities

Moeller M, Burger M, Dieterich P, Schwab A (2014)

Publication Language: English

Publication Type: Journal article

Publication year: 2014

Journal

Journal of Visual Communication and Image Representation Elsevier

Book Volume: 25

Pages Range: 396-409

Issue: 2

DOI: 10.1016/j.jvcir.2013.12.002

Abstract

This paper introduces a novel framework for the automated tracking of cells, with a particular focus on the challenging situation of phase contrast microscopic videos. Our framework is based on a topology preserving variational segmentation approach applied to normal velocity components obtained from optical flow computations, which appears to yield robust tracking and automated extraction of cell trajectories. In order to obtain improved trackings of local shape features we discuss an additional correction step based on active contours and the image Laplacian which we optimize for an example class of transformed renal epithelial (MDCK-F) cells. We also test the framework for human melanoma cells and murine neutrophil granulocytes that were seeded on different types of extracellular matrices. The results are validated with manual tracking results. © 2013 Elsevier Ltd. All rights reserved.

Authors with CRIS profile

Martin Burger

Involved external institutions

Technische Universität Dresden DE Germany (DE) Westfälische Wilhelms-Universität (WWU) Münster DE Germany (DE)

How to cite

APA:

Moeller, M., Burger, M., Dieterich, P., & Schwab, A. (2014). A framework for automated cell tracking in phase contrast microscopic videos based on normal velocities. Journal of Visual Communication and Image Representation, 25, 396-409. https://doi.org/10.1016/j.jvcir.2013.12.002

MLA:

Moeller, Michael, et al. "A framework for automated cell tracking in phase contrast microscopic videos based on normal velocities." Journal of Visual Communication and Image Representation 25 (2014): 396-409.

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