@misc{ClasenPaarProhaska, author = {Clasen, Malte and Paar, Philip and Prohaska, Steffen}, title = {Level of Detail for Trees Using Clustered Ellipsoids}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-14251}, number = {11-41}, abstract = {We present a level of detail method for trees based on ellipsoids and lines. We leverage the Expectation Maximization algorithm with a Gaussian Mixture Model to create a hierarchy of high-quality leaf clusterings, while the branches are simplified using agglomerative bottom-up clustering to preserve the connectivity. The simplification runs in a preprocessing step and requires no human interaction. For a fly by over and through a scene of 10k trees, our method renders on average at 40 ms/frame, up to 6 times faster than billboard clouds with comparable artifacts.}, language = {en} } @misc{WeberTranfieldHoeoegetal., author = {Weber, Britta and Tranfield, Erin M. and H{\"o}{\"o}g, Johanna L. and Baum, Daniel and Antony, Claude and Hyman, Tony and Verbavatz, Jean-Marc and Prohaska, Steffen}, title = {Automated stitching of microtubule centerlines across serial electron tomograms}, issn = {1438-0064}, doi = {10.1371/journal.pone.0113222}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-52958}, abstract = {Tracing microtubule centerlines in serial section electron tomography requires microtubules to be stitched across sections, that is lines from different sections need to be aligned, endpoints need to be matched at section boundaries to establish a correspondence between neighboring sections, and corresponding lines need to be connected across multiple sections. We present computational methods for these tasks: 1) An initial alignment is computed using a distance compatibility graph. 2) A fine alignment is then computed with a probabilistic variant of the iterative closest points algorithm, which we extended to handle the orientation of lines by introducing a periodic random variable to the probabilistic formulation. 3) Endpoint correspondence is established by formulating a matching problem in terms of a Markov random field and computing the best matching with belief propagation. Belief propagation is not generally guaranteed to converge to a minimum. We show how convergence can be achieved, nonetheless, with minimal manual input. In addition to stitching microtubule centerlines, the correspondence is also applied to transform and merge the electron tomograms. We applied the proposed methods to samples from the mitotic spindle in C. elegans, the meiotic spindle in X. laevis, and sub-pellicular microtubule arrays in T. brucei. The methods were able to stitch microtubules across section boundaries in good agreement with experts' opinions for the spindle samples. Results, however, were not satisfactory for the microtubule arrays. For certain experiments, such as an analysis of the spindle, the proposed methods can replace manual expert tracing and thus enable the analysis of microtubules over long distances with reasonable manual effort.}, language = {en} }