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  <doc>
    <id>4205</id>
    <completedYear>2014</completedYear>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>3</pageFirst>
    <pageLast>15</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Top Challenges in the Visualization of Engineering Tensor Fields</title>
    <parentTitle language="eng">Visualization and Processing of Tensors and Higher-Order Descriptors for Multi-Field Data</parentTitle>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Mario Hlawitschka</author>
    <editor>Carl-Frederic Westin</editor>
    <author>Ingrid Hotz</author>
    <editor>Bernhard Burgeth</editor>
    <author>Andrea Kratz</author>
    <editor>Anna Vilanova</editor>
    <author>G. Elisabeta Marai</author>
    <author>Rodrigo Moreno</author>
    <author>Gerik Scheuermann</author>
    <author>Markus Stommel</author>
    <author>Alexander Wiebel</author>
    <author>Eugene Zhang</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="visalgo">Visual Data Analysis in Science and Engineering</collection>
    <collection role="institutes" number="vissys">Image Analysis in Biology and Materials Science</collection>
    <collection role="persons" number="kratz">Kratz, Andrea</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>6909</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>722</pageFirst>
    <pageLast>732</pageLast>
    <pageNumber/>
    <edition/>
    <issue>7</issue>
    <volume>30</volume>
    <type>article</type>
    <publisherName>CAGD</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2013-10-01</completedDate>
    <publishedDate>2013-10-01</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">De Casteljau's Algotithm on Manifolds</title>
    <abstract language="eng">This paper proposes a generalization of the ordinary de Casteljau algorithm to manifold-valued data including an important special case which uses the exponential map of a symmetric space or Riemannian manifold. We investigate some basic properties of the corresponding Bézier curves and present applications to curve design on polyhedra and implicit surfaces as well as motion of rigid body and positive definite matrices. Moreover, we apply our approach to construct canal and developable surfaces.</abstract>
    <parentTitle language="eng">Computer Aided Geometric Design</parentTitle>
    <identifier type="doi">10.1016/j.cagd.2013.06.002</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-69096</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SourceTitle">Computer Aided Geometric Design</enrichment>
    <enrichment key="AcceptedDate">2013-10-01</enrichment>
    <submitter>Esfandiar Nava-Yazdani</submitter>
    <author>Esfandiar Nava-Yazdani</author>
    <author>Konrad Polthier</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="persons" number="navayazdani">Navayazdani, Esfandiar</collection>
    <collection role="projects" number="ECMath-CH15">ECMath-CH15</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/6909/1-s2.0-S0167839613000551-main.pdf</file>
  </doc>
  <doc>
    <id>6938</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Crack Morphology in a Columnar Thermal Barrier Coating System</title>
    <abstract language="eng">Ceramic layers are used as thermal barrier coatings (TBCs) on metallic substrates. During thermal transients, the thermal expansion mismatch between coating and substrate drives failure of the TBC mainly by interfacial cracking.&#13;
&#13;
Laser Shock Adhesion Test (LASAT) provides stresses at the ceramic/metal interface enabling controlled interfacial cracking. For achieving a clear understanding of the influence of local morphology on interfacial toughness, this study aims at characterizing the 3D morphology of a crack at the interface between metal and an EB-PVD TBC having a columnar structure. Cracks were produced by LASAT and documented further in SE and BSE image stacks collected simultaneously during subsequent slice and view operations using a focus ion beam (FIB) and a scanning electron microscope (FIB slice &amp; view). The segmented 3D data gives clear understanding of the columnar structure of the ceramic and of the interaction between the crack and the TBC microstructure.</abstract>
    <identifier type="urn">urn:nbn:de:0297-zib-69385</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Anne Dennstedt</author>
    <submitter>Tim Hasler</submitter>
    <author>Fabrice Gaslain</author>
    <author>Marion Bartsch</author>
    <author>Vincent Guipont</author>
    <author>Vincent Maurel</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="ITS">IT-Service</collection>
    <collection role="projects" number="no-project">no-project</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/6938/3DMS2018_AnneDennstedt.pdf</file>
  </doc>
  <doc>
    <id>3700</id>
    <completedYear>2010</completedYear>
    <publishedYear>2010</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>45</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>5</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Opportunities and challenges for digital morphology</title>
    <parentTitle language="eng">Biology Direct</parentTitle>
    <identifier type="doi">10.1186/1745-6150-5-45</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Alexander Ziegler</author>
    <author>Malte Ogurreck</author>
    <author>Thomas Steinke</author>
    <author>Felix Beckmann</author>
    <author>Steffen Prohaska</author>
    <author>Andreas Ziegler</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="vas">Distributed Algorithms and Supercomputing</collection>
    <collection role="institutes" number="vissys">Image Analysis in Biology and Materials Science</collection>
    <collection role="persons" number="prohaska">Prohaska, Steffen</collection>
    <collection role="persons" number="steinke">Steinke, Thomas</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>8540</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>5</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Nonlinear Hierarchical Model for Longitudinal Data on Manifolds</title>
    <abstract language="eng">Large longitudinal studies provide lots of valuable information, especially in medical applications. A problem which must be taken care of in order to utilize their full potential is that of correlation between intra-subject measurements taken at different times. For data in Euclidean space this can be done with hierarchical models, that is, models that consider intra-subject and between-subject variability in two different stages. Nevertheless, data from medical studies often takes values in nonlinear manifolds. Here, as a first step, geodesic hierarchical models have been developed that generalize the linear ansatz by assuming that time-induced intra-subject variations occur along a generalized straight line in the manifold. However, this is often not the case (e.g., periodic motion or processes with saturation). We propose a hierarchical model for manifold-valued data that extends this to include trends along higher-order curves, namely Bézier splines in the manifold.&#13;
To this end, we present a principled way of comparing shape trends in terms of a functional-based Riemannian metric.&#13;
Remarkably, this metric allows efficient, yet simple computations by virtue of a variational time discretization requiring only the solution of regression problems. &#13;
We validate our model on longitudinal data from the osteoarthritis initiative, including classification of disease progression.</abstract>
    <parentTitle language="eng">2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)</parentTitle>
    <identifier type="arxiv">2202.01180</identifier>
    <identifier type="doi">10.1109/ISBI52829.2022.9761465</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">2022-01-07</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Martin Hanik</author>
    <submitter>Christoph von Tycowicz</submitter>
    <author>Hans-Christian Hege</author>
    <author>Christoph von Tycowicz</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="persons" number="hege">Hege, Hans-Christian</collection>
    <collection role="persons" number="vontycowicz">Tycowicz, Christoph von</collection>
    <collection role="persons" number="hanik">Hanik, Martin</collection>
    <collection role="projects" number="MathPlus-EF2-3">MathPlus-EF2-3</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
</export-example>
