@misc{PaetschBaumEbelletal., author = {Paetsch, Olaf and Baum, Daniel and Ebell, Gino and Ehrig, Karsten and Heyn, Andreas and Meinel, Dietmar and Prohaska, Steffen}, title = {Korrosionsverfolgung in 3D-computertomographischen Aufnahmen von Stahlbetonproben}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-50912}, abstract = {Kurzfassung. Durch die Alkalit{\"a}t des Betons wird Betonstahl dauerhaft vor Korrosion gesch{\"u}tzt. Infolge von Chlorideintrag kann dieser Schutz nicht l{\"a}nger aufrechterhalten werden und f{\"u}hrt zu Lochkorrosion. Die zerst{\"o}rungsfreie Pr{\"u}fung von Stahlbetonproben mit 3D-CT bietet die M{\"o}glichkeit, eine Probe mehrfach gezielt vorzusch{\"a}digen und den Korrosionsfortschritt zu untersuchen. Zur Quantifizierung des Sch{\"a}digungsgrades m{\"u}ssen die bei dieser Untersuchung anfallenden großen Bilddaten mit Bildverarbeitungsmethoden ausgewertet werden. Ein wesentlicher Schritt dabei ist die Segmentierung der Bilddaten, bei der zwischen Korrosionsprodukt (Rost), Betonstahl (BSt), Beton, Rissen, Poren und Umgebung unterschieden werden muss. Diese Segmentierung bildet die Grundlage f{\"u}r statistische Untersuchungen des Sch{\"a}digungsfortschritts. Hierbei sind die {\"A}nderung der BSt-Geometrie, die Zunahme von Korrosionsprodukten und deren Ver{\"a}nderung {\"u}ber die Zeit sowie ihrer r{\"a}umlichen Verteilung in der Probe von Interesse. Aufgrund der Gr{\"o}ße der CT-Bilddaten ist eine manuelle Segmentierung nicht durchf{\"u}hrbar, so dass automatische Verfahren unabdingbar sind. Dabei ist insbesondere die Segmentierung der Korrosionsprodukte in den Bilddaten ein schwieriges Problem. Allein aufgrund der Grauwerte ist eine Zuordnung nahezu unm{\"o}glich, denn die Grauwerte von Beton und Korrosionsprodukt unterscheiden sich kaum. Eine formbasierte Suche ist nicht offensichtlich, da die Korrosionsprodukte in Beton diffuse Formen haben. Allerdings l{\"a}sst sich Vorwissen {\"u}ber die Ausbreitung der Korrosionsprodukte nutzen. Sie bilden sich in r{\"a}umlicher N{\"a}he des BSt (in Bereichen vorheriger Volumenabnahme des BSt), entlang von Rissen sowie in Porenr{\"a}umen, die direkt am BSt und in dessen Nahbereich liegen. Davon ausgehend wird vor der Korrosionsprodukterkennung zun{\"a}chst eine BSt-Volumen-, Riss- und Porenerkennung durchgef{\"u}hrt. Dieser in der Arbeit n{\"a}her beschriebene Schritt erlaubt es, halbautomatisch Startpunkte (Seed Points) f{\"u}r die Korrosionsprodukterkennung zu finden. Weiterhin werden verschiedene in der Bildverarbeitung bekannte Algorithmen auf ihre Eignung untersucht werden.}, language = {de} } @misc{RedemannWeberMoelleretal., author = {Redemann, Stefanie and Weber, Britta and M{\"o}ller, Marit and Verbavatz, Jean-Marc and Hyman, Anthony and Baum, Daniel and Prohaska, Steffen and M{\"u}ller-Reichert, Thomas}, title = {The Segmentation of Microtubules in Electron Tomograms Using Amira}, series = {Mitosis: Methods and Protocols}, journal = {Mitosis: Methods and Protocols}, publisher = {Springer}, doi = {10.1007/978-1-4939-0329-0_12}, pages = {261 -- 278}, language = {en} } @misc{KnoetelSeidelProhaskaetal., author = {Kn{\"o}tel, David and Seidel, Ronald and Prohaska, Steffen and Dean, Mason N. and Baum, Daniel}, title = {Automated Segmentation of Complex Patterns in Biological Tissues: Lessons from Stingray Tessellated Cartilage}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-65785}, abstract = {Introduction - Many biological structures show recurring tiling patterns on one structural level or the other. Current image acquisition techniques are able to resolve those tiling patterns to allow quantitative analyses. The resulting image data, however, may contain an enormous number of elements. This renders manual image analysis infeasible, in particular when statistical analysis is to be conducted, requiring a larger number of image data to be analyzed. As a consequence, the analysis process needs to be automated to a large degree. In this paper, we describe a multi-step image segmentation pipeline for the automated segmentation of the calcified cartilage into individual tesserae from computed tomography images of skeletal elements of stingrays. Methods - Besides applying state-of-the-art algorithms like anisotropic diffusion smoothing, local thresholding for foreground segmentation, distance map calculation, and hierarchical watershed, we exploit a graph-based representation for fast correction of the segmentation. In addition, we propose a new distance map that is computed only in the plane that locally best approximates the calcified cartilage. This distance map drastically improves the separation of individual tesserae. We apply our segmentation pipeline to hyomandibulae from three individuals of the round stingray (Urobatis halleri), varying both in age and size. Results - Each of the hyomandibula datasets contains approximately 3000 tesserae. To evaluate the quality of the automated segmentation, four expert users manually generated ground truth segmentations of small parts of one hyomandibula. These ground truth segmentations allowed us to compare the segmentation quality w.r.t. individual tesserae. Additionally, to investigate the segmentation quality of whole skeletal elements, landmarks were manually placed on all tesserae and their positions were then compared to the segmented tesserae. With the proposed segmentation pipeline, we sped up the processing of a single skeletal element from days or weeks to a few hours.}, language = {en} } @inproceedings{KlindtProhaskaBaumetal.2012, author = {Klindt, Marco and Prohaska, Steffen and Baum, Daniel and Hege, Hans-Christian}, title = {Conveying Archaeological Contexts to Museum Visitors: Case Study Pergamon Exhibition}, series = {VAST12: The 13th International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage - Short Papers}, booktitle = {VAST12: The 13th International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage - Short Papers}, editor = {Arnold, David and Kaminski, Jaime and Niccolucci, Franco and Stork, Andre}, publisher = {Eurographics Association}, address = {Brighton, UK}, doi = {10.2312/PE/VAST/VAST12S/025-028}, pages = {25 -- 28}, year = {2012}, language = {en} } @inproceedings{KlindtBaumProhaskaetal.2012, author = {Klindt, Marco and Baum, Daniel and Prohaska, Steffen and Hege, Hans-Christian}, title = {iCon.text - a customizable iPad app for kiosk applications in museum exhibitions}, series = {EVA 2012 Berlin}, booktitle = {EVA 2012 Berlin}, publisher = {Gesellschaft zur F{\"o}rderung angewandter Informatik e.V.}, address = {Volmerstraße 3, 12489 Berlin}, pages = {150 -- 155}, year = {2012}, language = {en} } @article{RigortGuentherHegerletal.2012, author = {Rigort, Alexander and G{\"u}nther, David and Hegerl, Reiner and Baum, Daniel and Weber, Britta and Prohaska, Steffen and Medalia, Ohad and Baumeister, Wolfgang and Hege, Hans-Christian}, title = {Automated segmentation of electron tomograms for a quantitative description of actin filament networks}, series = {Journal of Structural Biology}, volume = {177}, journal = {Journal of Structural Biology}, doi = {10.1016/j.jsb.2011.08.012}, pages = {135 -- 144}, year = {2012}, language = {en} } @inproceedings{HombergBaumProhaskaetal.2012, author = {Homberg, Ulrike and Baum, Daniel and Prohaska, Steffen and Kalbe, Ute and Witt, Karl Josef}, title = {Automatic Extraction and Analysis of Realistic Pore Structures from µCT Data for Pore Space Characterization of Graded Soil}, series = {Proceedings of the 6th International Conference on Scour and Erosion (ICSE-6)}, booktitle = {Proceedings of the 6th International Conference on Scour and Erosion (ICSE-6)}, pages = {345 -- 352}, year = {2012}, language = {en} } @article{WeberGreenanProhaskaetal.2012, author = {Weber, Britta and Greenan, Garrett and Prohaska, Steffen and Baum, Daniel and Hege, Hans-Christian and M{\"u}ller-Reichert, Thomas and Hyman, Anthony and Verbavatz, Jean-Marc}, title = {Automated tracing of microtubules in electron tomograms of plastic embedded samples of Caenorhabditis elegans embryos}, series = {Journal of Structural Biology}, volume = {178}, journal = {Journal of Structural Biology}, number = {2}, doi = {10.1016/j.jsb.2011.12.004}, pages = {129 -- 138}, year = {2012}, language = {en} } @article{LindowBaumProhaskaetal.2010, author = {Lindow, Norbert and Baum, Daniel and Prohaska, Steffen and Hege, Hans-Christian}, title = {Accelerated Visualization of Dynamic Molecular Surfaces}, series = {Comput. Graph. Forum}, volume = {29}, journal = {Comput. Graph. Forum}, doi = {10.1111/j.1467-8659.2009.01693.x}, pages = {943 -- 952}, year = {2010}, language = {en} } @misc{HombergBaumWiebeletal.2014, author = {Homberg, Ulrike and Baum, Daniel and Wiebel, Alexander and Prohaska, Steffen and Hege, Hans-Christian}, title = {Definition, Extraction, and Validation of Pore Structures in Porous Materials}, series = {Topological Methods in Data Analysis and Visualization III}, journal = {Topological Methods in Data Analysis and Visualization III}, editor = {Bremer, Peer-Timo and Hotz, Ingrid and Pascucci, Valerio and Peikert, Ronald}, publisher = {Springer}, doi = {10.1007/978-3-319-04099-8_15}, pages = {235 -- 248}, year = {2014}, language = {en} }