Segmentation of microtubules from electron tomograms
Microtubules are a part of the cytoskeleton of cells. They are tube-like polymeres that stabilize the cell but also play an important role in cell division. In particular the spindle - the microtubule assembly formed during cell division - is subject to intense research. One of the most important methods for looking at microtubule distribution in cells is using electron tomography. Here thick (300nm) sections of cells are prepared for electron microscopy and imaged on a CCD camera. Inverse radon transform algorithms are then used to reconstruct 3D information. One of the main bottle necks in the analysis of the microtubule network is then the construction of an exact model of the microtubules from the acquired data. This requires laborious manual modeling of microtubules. The aim of this project is to utilize image processing techniques to significantly accelerate the modeling process of microtubules in the sections and thus reduce manual operator time and collect data in a way that is less biased by human observation. Further information is available in the detailed project description.
Max Planck Institute of Molecular Cell Biology and Genetics, Microtubules and cell division, Hyman Lab, Dresden (Anthony Hyman, Jean-Marc Verbavatz)
TU Dresden, Structural Cell Biology (Thomas Müller-Reichert)
European Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg (Erin Tranfield)
Boulder Laboratory for 3D Electron Microscopy of Cells (Eileen O'Toole, David Mastronarde, Richard McIntosh)
Max Planck Institute of Molecular Cell Biology and Genetics (01/2009–06/2012)
- Britta Weber, Garrett Greenan, Steffen Prohaska, Daniel Baum, Hans-Christian Hege, Thomas Müller-Reichert, Anthony A. Hyman, Jean-Marc Verbavatz. Automated tracing of microtubules in electron tomograms of plastic embedded samples of Caenorhabditis elegans embryos. Journal of Structural Biology, 178(2):129 – 138, 2012. (Software available for download)
- Alexander Rigort, David Günther, Reiner Hegerl, Daniel Baum, Britta Weber, Steffen Prohaska, Ohad Medalia, Wolfgang Baumeister, and Hans-Christian Hege. Automated segmentation of electron tomograms for a quantitative description of actin filament networks. J Struct Biol, 178:135–144, Sep 2011. 10.1016/j.jsb.2011.08.012. (Software available for download)
- Thomas Torsney-Weir, Ahmed Saad, Torsten Möller, Britta Weber, Hans-Christian Hege, Jean-Marc Verbavatz, Steven Bergner. Tuner: Principled parameter finding for image segmentation algorithms using visual response surface exploration. IEEE Trans. Vis. Comput. Graph. 17:12, pp. 1892-1901, December 2011, DOI:10.1109/TVCG.2011.248.
- Vincent Jasper Dercksen, Britta Weber, David Günther, Marcel Oberlaender, Steffen Prohaska, Hans-Christian Hege. Automatic alignment of stacks of filament data. Proc. IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, IEEE press, pp. 971-974, Boston, MA, USA, DOI:10.1109/ISBI.2009.5193216