TY - GEN A1 - Paetsch, Olaf A1 - Baum, Daniel A1 - Ebell, Gino A1 - Ehrig, Karsten A1 - Heyn, Andreas A1 - Meinel, Dietmar A1 - Prohaska, Steffen T1 - Korrosionsverfolgung in 3D-computertomographischen Aufnahmen von Stahlbetonproben N2 - Kurzfassung. Durch die Alkalität des Betons wird Betonstahl dauerhaft vor Korrosion geschützt. Infolge von Chlorideintrag kann dieser Schutz nicht länger aufrechterhalten werden und führt zu Lochkorrosion. Die zerstörungsfreie Prüfung von Stahlbetonproben mit 3D-CT bietet die Möglichkeit, eine Probe mehrfach gezielt vorzuschädigen und den Korrosionsfortschritt zu untersuchen. Zur Quantifizierung des Schädigungsgrades müssen 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 für statistische Untersuchungen des Schädigungsfortschritts. Hierbei sind die Änderung der BSt-Geometrie, die Zunahme von Korrosionsprodukten und deren Veränderung über die Zeit sowie ihrer räumlichen Verteilung in der Probe von Interesse. Aufgrund der Größe der CT-Bilddaten ist eine manuelle Segmentierung nicht durchführbar, 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 unmöglich, 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 lässt sich Vorwissen über die Ausbreitung der Korrosionsprodukte nutzen. Sie bilden sich in räumlicher Nähe des BSt (in Bereichen vorheriger Volumenabnahme des BSt), entlang von Rissen sowie in Porenräumen, die direkt am BSt und in dessen Nahbereich liegen. Davon ausgehend wird vor der Korrosionsprodukterkennung zunächst eine BSt-Volumen-, Riss- und Porenerkennung durchgeführt. Dieser in der Arbeit näher beschriebene Schritt erlaubt es, halbautomatisch Startpunkte (Seed Points) für die Korrosionsprodukterkennung zu finden. Weiterhin werden verschiedene in der Bildverarbeitung bekannte Algorithmen auf ihre Eignung untersucht werden. T3 - ZIB-Report - 14-24 KW - Beton KW - Korrosionserkennung KW - Bildverarbeitung KW - Computertomografie KW - concrete KW - corrosiondetection KW - image processing KW - computed tomography Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-50912 SN - 1438-0064 ER - TY - JOUR A1 - Lindow, Norbert A1 - Baum, Daniel A1 - Hege, Hans-Christian T1 - Ligand Excluded Surface: A New Type of Molecular Surface JF - IEEE Transactions on Visualization and Computer Graphics N2 - The most popular molecular surface in molecular visualization is the solvent excluded surface (SES). It provides information about the accessibility of a biomolecule for a solvent molecule that is geometrically approximated by a sphere. During a period of almost four decades, the SES has served for many purposes – including visualization, analysis of molecular interactions and the study of cavities in molecular structures. However, if one is interested in the surface that is accessible to a molecule whose shape differs significantly from a sphere, a different concept is necessary. To address this problem, we generalize the definition of the SES by replacing the probe sphere with the full geometry of the ligand defined by the arrangement of its van der Waals spheres. We call the new surface ligand excluded surface (LES) and present an efficient, grid-based algorithm for its computation. Furthermore, we show that this algorithm can also be used to compute molecular cavities that could host the ligand molecule. We provide a detailed description of its implementation on CPU and GPU. Furthermore, we present a performance and convergence analysis and compare the LES for several molecules, using as ligands either water or small organic molecules. Y1 - 2014 U6 - https://doi.org/10.1109/TVCG.2014.2346404 VL - 20 IS - 12 SP - 2486 EP - 2495 ER - TY - GEN A1 - Lindow, Norbert A1 - Baum, Daniel A1 - Hege, Hans-Christian T1 - Ligand Excluded Surface: A New Type of Molecular Surface N2 - The most popular molecular surface in molecular visualization is the solvent excluded surface (SES). It provides information about the accessibility of a biomolecule for a solvent molecule that is geometrically approximated by a sphere. During a period of almost four decades, the SES has served for many purposes – including visualization, analysis of molecular interactions and the study of cavities in molecular structures. However, if one is interested in the surface that is accessible to a molecule whose shape differs significantly from a sphere, a different concept is necessary. To address this problem, we generalize the definition of the SES by replacing the probe sphere with the full geometry of the ligand defined by the arrangement of its van der Waals spheres. We call the new surface ligand excluded surface (LES) and present an efficient, grid-based algorithm for its computation. Furthermore, we show that this algorithm can also be used to compute molecular cavities that could host the ligand molecule. We provide a detailed description of its implementation on CPU and GPU. Furthermore, we present a performance and convergence analysis and compare the LES for several molecules, using as ligands either water or small organic molecules. T3 - ZIB-Report - 14-27 Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-51194 SN - 1438-0064 ER - TY - GEN A1 - Redemann, Stefanie A1 - Weber, Britta A1 - Möller, Marit A1 - Verbavatz, Jean-Marc A1 - Hyman, Anthony A1 - Baum, Daniel A1 - Prohaska, Steffen A1 - Müller-Reichert, Thomas T1 - The Segmentation of Microtubules in Electron Tomograms Using Amira T2 - Mitosis: Methods and Protocols Y1 - 2014 U6 - https://doi.org/10.1007/978-1-4939-0329-0_12 SP - 261 EP - 278 PB - Springer ER - TY - GEN A1 - Knötel, David A1 - Seidel, Ronald A1 - Prohaska, Steffen A1 - Dean, Mason N. A1 - Baum, Daniel T1 - Automated Segmentation of Complex Patterns in Biological Tissues: Lessons from Stingray Tessellated Cartilage N2 - 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. T3 - ZIB-Report - 17-62 KW - micro-CT KW - image segmentation KW - 2D distance map KW - hierarchical watershed KW - stingray KW - tesserae KW - biological tilings KW - Amira Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-65785 SN - 1438-0064 ER - TY - CHAP A1 - Klindt, Marco A1 - Prohaska, Steffen A1 - Baum, Daniel A1 - Hege, Hans-Christian ED - Arnold, David ED - Kaminski, Jaime ED - Niccolucci, Franco ED - Stork, Andre T1 - Conveying Archaeological Contexts to Museum Visitors: Case Study Pergamon Exhibition T2 - VAST12: The 13th International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage - Short Papers Y1 - 2012 UR - http://diglib.eg.org/EG/DL/PE/VAST/VAST12S/025-028.pdf U6 - https://doi.org/10.2312/PE/VAST/VAST12S/025-028 SP - 25 EP - 28 PB - Eurographics Association CY - Brighton, UK ER - TY - CHAP A1 - Klindt, Marco A1 - Baum, Daniel A1 - Prohaska, Steffen A1 - Hege, Hans-Christian T1 - iCon.text – a customizable iPad app for kiosk applications in museum exhibitions T2 - EVA 2012 Berlin Y1 - 2012 SP - 150 EP - 155 PB - Gesellschaft zur Förderung angewandter Informatik e.V. CY - Volmerstraße 3, 12489 Berlin ER - TY - CHAP A1 - Lindow, Norbert A1 - Baum, Daniel A1 - Bondar, Ana-Nicoleta A1 - Hege, Hans-Christian T1 - Dynamic Channels in Biomolecular Systems: Path Analysis and Visualization T2 - Proceedings of IEEE Symposium on Biological Data Visualization (biovis’12) Y1 - 2012 U6 - https://doi.org/10.1109/BioVis.2012.6378599 SP - 99 EP - 106 ER - TY - CHAP A1 - Schmidt-Ehrenberg, Johannes A1 - Baum, Daniel A1 - Hege, Hans-Christian ED - J. Moorhead, Robert ED - Gross, Markus ED - I. Joy, Kenneth T1 - Visualizing Dynamic Molecular Conformations T2 - Proceedings of IEEE Visualization 2002 Y1 - 2002 U6 - https://doi.org/10.1109/VISUAL.2002.1183780 SP - 235 EP - 242 PB - IEEE Computer Society Press CY - Boston MA, USA ER - TY - JOUR A1 - Rigort, Alexander A1 - Günther, David A1 - Hegerl, Reiner A1 - Baum, Daniel A1 - Weber, Britta A1 - Prohaska, Steffen A1 - Medalia, Ohad A1 - Baumeister, Wolfgang A1 - Hege, Hans-Christian T1 - Automated segmentation of electron tomograms for a quantitative description of actin filament networks JF - Journal of Structural Biology Y1 - 2012 U6 - https://doi.org/10.1016/j.jsb.2011.08.012 VL - 177 SP - 135 EP - 144 ER -