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  <doc>
    <id>4189</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2013-07-30</completedDate>
    <publishedDate>2013-07-30</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Fast Generation of Virtual X-ray Images from Deformable Tetrahedral Meshes</title>
    <abstract language="eng">We propose a novel GPU-based approach to render virtual X-ray projections of deformable tetrahedral meshes. These meshes represent the shape and the internal density distribution of a particular anatomical structure and are derived from statistical shape and intensity models (SSIMs). We apply our method to improve the geometric reconstruction of 3D anatomy (e.g.\ pelvic bone) from 2D X-ray images. For that purpose, shape and density of a tetrahedral mesh are varied and virtual X-ray projections are generated within an optimization process until the similarity between the computed virtual X-ray and the respective anatomy depicted in a given clinical X-ray is maximized. The OpenGL implementation presented in this work deforms and projects tetrahedral meshes of high resolution (200.000+ tetrahedra) at interactive rates. It generates virtual X-rays that accurately depict the density distribution of an anatomy of interest. Compared to existing methods that accumulate X-ray attenuation in deformable meshes, our novel approach significantly boosts the deformation/projection performance. The proposed projection algorithm scales better with respect to mesh resolution and complexity of the density distribution, and the combined deformation and projection on the GPU scales better with respect to the number of deformation parameters. The gain in performance allows for a larger number of cycles in the optimization process. Consequently, it reduces the risk of being stuck in a local optimum. We believe that our approach contributes in orthopedic surgery, where 3D anatomy information needs to be extracted from 2D X-rays to support surgeons in better planning joint replacements.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-41896</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SourceTitle">appeared in IEEE Transactions on Visualization and Computer Graphics</enrichment>
    <submitter>Moritz Ehlke</submitter>
    <author>Moritz Ehlke</author>
    <author>Heiko Ramm</author>
    <author>Hans Lamecker</author>
    <author>Hans-Christian Hege</author>
    <author>Stefan Zachow</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-38</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>digitally reconstructed radiographs</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>volume rendering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mesh deformation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>statistical shape and intensity models</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>image registration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>GPU acceleration</value>
    </subject>
    <collection role="ccs" number="I.">Computing Methodologies</collection>
    <collection role="msc" number="68-XX">COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)</collection>
    <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="medplan">Therapy Planning</collection>
    <collection role="persons" number="ehlke">Ehlke, Moritz</collection>
    <collection role="persons" number="hege">Hege, Hans-Christian</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="BSRT-3DFromXray">BSRT-3DFromXray</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4189/Report-13-38.pdf</file>
  </doc>
  <doc>
    <id>1658</id>
    <completedYear/>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2012-11-20</completedDate>
    <publishedDate>2012-11-20</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Efficient projection and deformation of volumetric intensity models for accurate simulation of X-ray images</title>
    <abstract language="eng">We present an efficient GPU-based method to generate virtual X-ray images from tetrahedral meshes which are&#13;
associated with attenuation values. In addition, a novel approach is proposed that performs the model deformation&#13;
on the GPU. The tetrahedral grids are derived from volumetric statistical shape and intensity models (SSIMs) and describe anatomical structures. Our research targets at reconstructing 3D anatomical shapes by comparing virtual X-ray images generated using our novel approach with clinical data while varying the shape and density of the SSIM in an optimization process. We assume that a deformed SSIM adequately represents an anatomy of interest when the similarity between the virtual and the clinical X-ray image is maximized. The OpenGL implementation presented here generates accurate (virtual) X-ray images at interactive rates, thus qualifying it for its use in the reconstruction process.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-16580</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SourceTitle">Presented at the 12th Annual Meeting of CAOS-International (CAOS)</enrichment>
    <author>Moritz Ehlke</author>
    <submitter>Moritz Ehlke</submitter>
    <author>Heiko Ramm</author>
    <author>Hans Lamecker</author>
    <author>Stefan Zachow</author>
    <series>
      <title>ZIB-Report</title>
      <number>12-40</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Digitally Reconstructed Radiograph (DRR), Anatomy Reconstruction, Statistical Shape and Intensity Model (SSIM), GPU acceleration</value>
    </subject>
    <collection role="ccs" number="I.">Computing Methodologies</collection>
    <collection role="msc" number="97-XX">MATHEMATICS EDUCATION</collection>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="persons" number="ehlke">Ehlke, Moritz</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="BSRT-3DFromXray">BSRT-3DFromXray</collection>
    <collection role="projects" number="MATHEON-F2">MATHEON-F2</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1658/Report-12-40-final.pdf</file>
  </doc>
  <doc>
    <id>4249</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2013-09-18</completedDate>
    <publishedDate>2013-09-18</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Visual Support for Positioning Hearing Implants</title>
    <abstract language="eng">We present a software planning tool that provides intuitive visual feedback for finding suitable positions of hearing implants in the human temporal bone. After an automatic reconstruction of the temporal bone anatomy the tool pre-positions the implant and allows the user to adjust its position interactively with simple 2D dragging and rotation operations on the bone's surface. During this procedure, visual elements like warning labels on the implant or color encoded bone density information on the bone geometry provide guidance for the determination of a suitable fit.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-42495</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SourceTitle">appeared in Proceedings of the 12th annual meeting of the CURAC society</enrichment>
    <author>Heiko Ramm</author>
    <submitter>Heiko Ramm</submitter>
    <author>Oscar Salvador Morillo Victoria</author>
    <author>Ingo Todt</author>
    <author>Hartmut Schirmacher</author>
    <author>Arneborg Ernst</author>
    <author>Stefan Zachow</author>
    <author>Hans Lamecker</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-53</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>bone anchored hearing implant</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>surgery planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>segmentation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>visualization</value>
    </subject>
    <collection role="ccs" number="J.">Computer Applications</collection>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="BoneBridge">BoneBridge</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4249/ZIB-Report 13-35 Visual support for the positioning of hearing implants.pdf</file>
  </doc>
  <doc>
    <id>7241</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Validation of a Statistical Shape Model for Acetabular Bone Defect Analysis</title>
    <abstract language="eng">Acetabular bone defects are still challenging to quantify. Numerous classification schemes have been proposed to categorize the diverse kinds of defects. However, these classification schemes are mainly descriptive and hence it remains difficult to apply them in pre-clinical testing, implant development and pre-operative planning. By reconstructing the native situation of a defect pelvis using a Statistical Shape Model (SSM), a more quantitative analysis of the bone defects could be performed. The aim of this study is to develop such a SSM and to validate its accuracy using relevant clinical scenarios and parameters.</abstract>
    <parentTitle language="eng">ISTA 2018 London Abstract Book</parentTitle>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">accepted for publication</enrichment>
    <enrichment key="AcceptedDate">2018-07-17</enrichment>
    <author>G. Hettich</author>
    <submitter>Hans Lamecker</submitter>
    <author>R. A. Schierjott</author>
    <author>C. Schilling</author>
    <author>A. Maas</author>
    <author>Heiko Ramm</author>
    <author>Matthias Bindernagel</author>
    <author>Hans Lamecker</author>
    <author>T. M. Grupp</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="projects" number="MODAL-MedLab">MODAL-MedLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>4403</id>
    <completedYear>2013</completedYear>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>116</pageFirst>
    <pageLast>120</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Visual Support for Positioning Hearing Implants</title>
    <parentTitle language="eng">Proceedings of the 12th annual meeting of the CURAC society</parentTitle>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-42495</enrichment>
    <author>Heiko Ramm</author>
    <editor>Wolfgang Freysinger</editor>
    <author>Oscar Salvador Victoria Morillo</author>
    <author>Ingo Todt</author>
    <author>Hartmut Schirmacher</author>
    <author>Arneborg Ernst</author>
    <author>Stefan Zachow</author>
    <author>Hans Lamecker</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="BoneBridge">BoneBridge</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>7747</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>10</issue>
    <volume>3755</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-02-28</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Characterization of the Airflow within an Average Geometry of the Healthy Human Nasal Cavity</title>
    <abstract language="eng">This study’s objective was the generation of a standardized geometry of the healthy nasal cavity.&#13;
An average geometry of the healthy nasal cavity was generated using a statistical shape model based on 25 symptom-free subjects. Airflow within the average geometry and these geometries was calculated using fluid simulations. Integral measures of the nasal resistance, wall shear stresses (WSS) and velocities were calculated as well as cross-sectional areas (CSA). Furthermore, individual WSS and static pressure distributions were mapped onto the average geometry.&#13;
The average geometry featured an overall more regular shape that resulted in less resistance, reduced wall shear stresses and velocities compared to the median of the 25 geometries. Spatial distributions of WSS and pressure of average geometry agreed well compared to the average distributions of all individual geometries. The minimal CSA of the average geometry was larger than the median of all individual geometries (83.4 vs. 74.7 mm²).&#13;
The airflow observed within the average geometry of the healthy nasal cavity did not equal the average airflow of the individual geometries. While differences observed for integral measures were notable, the calculated values for the average geometry lay within the distributions of the individual parameters. Spatially resolved parameters differed less prominently.</abstract>
    <parentTitle language="eng">Scientific Reports</parentTitle>
    <identifier type="doi">10.1038/s41598-020-60755-3</identifier>
    <identifier type="url">https://rdcu.be/b2irD</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">17.02.2020</enrichment>
    <author>Jan Brüning</author>
    <submitter>Stefan Zachow</submitter>
    <author>Thomas Hildebrandt</author>
    <author>Werner Heppt</author>
    <author>Nora Schmidt</author>
    <author>Hans Lamecker</author>
    <author>Angelika Szengel</author>
    <author>Natalja Amiridze</author>
    <author>Heiko Ramm</author>
    <author>Matthias Bindernagel</author>
    <author>Stefan Zachow</author>
    <author>Leonid Goubergrits</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="Rhino-CFD">Rhino-CFD</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>7982</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>16</pageFirst>
    <pageLast>27</pageLast>
    <pageNumber/>
    <edition>1</edition>
    <issue/>
    <volume>12439</volume>
    <type>article</type>
    <publisherName>Springer International Publishing</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-12-04</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Automated Virtual Reconstruction of Large Skull Defects using Statistical Shape Models and Generative Adversarial Networks</title>
    <abstract language="eng">We present an automated method for extrapolating missing&#13;
regions in label data of the skull in an anatomically plausible manner. The ultimate goal is to design patient-speci� c cranial implants for correcting large, arbitrarily shaped defects of the skull that can, for example, result from trauma of the head. Our approach utilizes a 3D statistical shape model (SSM) of the skull and a 2D generative adversarial network (GAN) that is trained in an unsupervised fashion from samples of healthy patients alone. By � tting the SSM to given input labels containing the skull defect, a First approximation of the healthy state of the patient is obtained. The GAN is then applied to further correct and smooth the output of the SSM in an anatomically plausible manner. Finally, the defect region is extracted using morphological operations and subtraction between the extrapolated healthy state of the patient and the defective input labels. The method is trained and evaluated based on data from the MICCAI 2020 AutoImplant challenge. It produces state-of-the art results on regularly&#13;
shaped cut-outs that were present in the training and testing data of the challenge. Furthermore, due to unsupervised nature of the approach, the method generalizes well to previously unseen defects of varying shapes that were only present in the hidden test dataset.</abstract>
    <parentTitle language="eng">Towards the Automatization of Cranial Implant Design in Cranioplasty</parentTitle>
    <subTitle language="eng">First Challenge, AutoImplant 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings</subTitle>
    <identifier type="doi">10.1007/978-3-030-64327-0_3</identifier>
    <note>Best Paper Award</note>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">2020-09-21</enrichment>
    <author>Pedro Pimentel</author>
    <submitter>Stefan Zachow</submitter>
    <editor>Jianning Li</editor>
    <author>Angelika Szengel</author>
    <editor>Jan Egger</editor>
    <author>Moritz Ehlke</author>
    <author>Hans Lamecker</author>
    <author>Stefan Zachow</author>
    <author>Laura Estacio</author>
    <author>Christian Doenitz</author>
    <author>Heiko Ramm</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="ehlke">Ehlke, Moritz</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="Cranio">Cranio</collection>
    <collection role="projects" number="MODAL-MedLab">MODAL-MedLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>8090</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
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    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images</title>
    <parentTitle language="eng">arXiv</parentTitle>
    <identifier type="arxiv">2001.09193</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="FulltextUrl">https://arxiv.org/pdf/2001.09193.pdf</enrichment>
    <submitter>Tamaz Amiranashvili</submitter>
    <author>Anjany Sekuboyina</author>
    <author>Amirhossein Bayat</author>
    <author>Malek E. Husseini</author>
    <author>Maximilian Löffler</author>
    <author>Hongwei Li</author>
    <author>Giles Tetteh</author>
    <author>Jan Kukačka</author>
    <author>Christian Payer</author>
    <author>Darko Štern</author>
    <author>Martin Urschler</author>
    <author>Maodong Chen</author>
    <author>Dalong Cheng</author>
    <author>Nikolas Lessmann</author>
    <author>Yujin Hu</author>
    <author>Tianfu Wang</author>
    <author>Dong Yang</author>
    <author>Daguang Xu</author>
    <author>Felix Ambellan</author>
    <author>Tamaz Amiranashvili</author>
    <author>Moritz Ehlke</author>
    <author>Hans Lamecker</author>
    <author>Sebastian Lehnert</author>
    <author>Marilia Lirio</author>
    <author>Nicolás Pérez de Olaguer</author>
    <author>Heiko Ramm</author>
    <author>Manish Sahu</author>
    <author>Alexander Tack</author>
    <author>Stefan Zachow</author>
    <author>Tao Jiang</author>
    <author>Xinjun Ma</author>
    <author>Christoph Angerman</author>
    <author>Xin Wang</author>
    <author>Qingyue Wei</author>
    <author>Kevin Brown</author>
    <author>Matthias Wolf</author>
    <author>Alexandre Kirszenberg</author>
    <author>Élodie Puybareau</author>
    <author>Alexander Valentinitsch</author>
    <author>Markus Rempfler</author>
    <author>Björn H. Menze</author>
    <author>Jan S. Kirschke</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="ehlke">Ehlke, Moritz</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="MODAL-MedLab">MODAL-MedLab</collection>
    <collection role="persons" number="ambellan">Ambellan, Felix</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="projects" number="MathPlus-TrU-1">MathPlus-TrU-1</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>3592</id>
    <completedYear>2013</completedYear>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2673</pageFirst>
    <pageLast>2682</pageLast>
    <pageNumber/>
    <edition/>
    <issue>12</issue>
    <volume>19</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Fast Generation of Virtual X-ray Images for Reconstruction of 3D Anatomy</title>
    <parentTitle language="eng">IEEE Transactions on Visualization and Computer Graphics</parentTitle>
    <identifier type="doi">10.1109/TVCG.2013.159</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-35928</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-41896</enrichment>
    <enrichment key="FulltextUrl">http://www.zib.de/visual-publications/sources/src-2013/Ehlke-Ramm-Lamecker-Hege-Zachow-Fast_Virtual_Xrays_3D_Recon-VIS13.pdf</enrichment>
    <author>Moritz Ehlke</author>
    <author>Heiko Ramm</author>
    <author>Hans Lamecker</author>
    <author>Hans-Christian Hege</author>
    <author>Stefan Zachow</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="medplan">Therapy Planning</collection>
    <collection role="persons" number="ehlke">Ehlke, Moritz</collection>
    <collection role="persons" number="hege">Hege, Hans-Christian</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="BSRT-3DFromXray">BSRT-3DFromXray</collection>
    <collection role="projects" number="Trauma">Trauma</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>3618</id>
    <completedYear>2012</completedYear>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>210</issue>
    <volume/>
    <type>poster</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Analysis of inter-individual anatomical shape variations of joint structures</title>
    <parentTitle language="eng">Proc. Int. Society of Computer Assisted Orthopaedic Surgery (CAOS)</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <author>Matthias Bindernagel</author>
    <author>Dagmar Kainmüller</author>
    <author>Heiko Ramm</author>
    <author>Hans Lamecker</author>
    <author>Stefan Zachow</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>3623</id>
    <completedYear>2012</completedYear>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>poster</type>
    <publisherName/>
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    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Efficient projection and deformation of volumetric shape and intensity models for accurate simulation of X-ray images</title>
    <parentTitle language="eng">Eurographics Workshop on Visual Computing for Biomedicine (NVIDIA best poster award)</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <author>Moritz Ehlke</author>
    <author>Heiko Ramm</author>
    <author>Hans Lamecker</author>
    <author>Stefan Zachow</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="ehlke">Ehlke, Moritz</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="BSRT-3DFromXray">BSRT-3DFromXray</collection>
    <collection role="projects" number="MATHEON-F2">MATHEON-F2</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>3625</id>
    <completedYear>2012</completedYear>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>101</pageFirst>
    <pageLast>111</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>7599</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Feature-Preserving, Multi-Material Mesh Generation using Hierarchical Oracles</title>
    <parentTitle language="eng">Proc. MICCAI Workshop on Mesh Processing in Medical Image Analysis (MeshMed)</parentTitle>
    <enrichment key="Series">Lecture Notes in Computer Science</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Max Kahnt</author>
    <editor>Joshua A. Levine</editor>
    <author>Heiko Ramm</author>
    <editor>Rasmus R. Paulsen</editor>
    <author>Hans Lamecker</author>
    <editor>Yongjie Zhang</editor>
    <author>Stefan Zachow</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="EU-FP7-MXL">EU-FP7-MXL</collection>
    <collection role="projects" number="MATHEON-F2">MATHEON-F2</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>5124</id>
    <completedYear>2014</completedYear>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>439</pageFirst>
    <pageLast>442</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>62</volume>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Entwicklung eines CT-Daten-basierten Vibrant-Bonebridge-Viewers</title>
    <abstract language="deu">Die Positionierung des B-FMT der Vibrant Bonebridge kann aufgrund der anatomischen Verhältnisse des Mastoids und der Größe des Aktuators ohne eine vorherige Beurteilung der individuellen Computertomographie (CT) des Felsenbeins problematisch sein. Die Entwicklung eines einfach zu bedienenden Viewers, welcher eine Positionierung des B-FMT im Felsenbeinmodell ermöglicht und hier auf individuelle potenzielle anatomische Konflikte hinweist sowie Lösungsmöglichkeiten anbietet, kann ein hilfreiches Werkzeug zur präoperativen Positionierung sein.&#13;
&#13;
Ziel der Arbeit war die Definition von Anforderungen und die Anfertigung eines Prototyps eines Vibrant-Bonebridge-Viewers.&#13;
&#13;
Auf der Basis einer ZIBAmira-Software-Version und der Inklusion eines B-FMT-Modells unter Erstellung eines Felsenbeinmodells, welches die intuitive Beurteilung von Konflikten ermöglicht, erfolgte die Erstellung des Prototyps eines Vibrant-Bonebridge-Viewers.Ergebnisse. Die Segmentierungszeit der individuellen DICOM-Daten („digital imaging and communications in medicine“) beträgt etwa 5 min. Eine Positionierung im individuellen 3-D-Felsenbeinmodell ermöglicht die quantitative und qualitative Beurteilung von Konflikten (Sinus sigmoideus, mittlere Schädelgrube) und das Aufsuchen einer bevorzugten Position. Das Anheben des B-FMT mittels virtueller Unterlegscheiben kann simuliert werden.&#13;
&#13;
Der erstellte Vibrant-Bonebridge-Viewer ermöglicht verlässlich eine Simulation der B-FMT-Positionierung. Die klinische Anwendbarkeit muss evaluiert werden.</abstract>
    <parentTitle language="deu">HNO</parentTitle>
    <identifier type="doi">10.1007/s00106-014-2851-3</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Ingo Todt</author>
    <submitter>Stefan Zachow</submitter>
    <author>Hans Lamecker</author>
    <author>Heiko Ramm</author>
    <author>Henning Frenzel</author>
    <author>Barbara Wollenberg</author>
    <author>Thomas Beleites</author>
    <author>Thomas Zahnert</author>
    <author>Jan Peter Thomas</author>
    <author>Stefan Dazert</author>
    <author>Arneborg Ernst</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="projects" number="BoneBridge">BoneBridge</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>5127</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>72</pageFirst>
    <pageLast>74</pageLast>
    <pageNumber/>
    <edition/>
    <issue>S1</issue>
    <volume>15</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A computed tomographic data-based vibrant bonebridge visualization tool</title>
    <abstract language="eng">Information about the temporal bone size and variations of anatomical structures are crucial for a safe positioning of the Vibrant Bonebridge B-FMT. A radiological based preoperative planning of the surgical procedure decreases the surgical time and minimizes the risk of complications.&#13;
&#13;
We developed a software tool, which allows a catch up of foreign DICOM data based CT temporal bone scans. The individual CT scan is transmitted into a 3D reconstructed pattern of the temporal bone. In this 3D reconstruction the individually favored position of the B- FMT should be found.&#13;
&#13;
The software allows a determination of a safe B-FMT position by identifying the individual relation of middle fossa, jugular bulb and external auditory canal. Skull thickness and screw length are contained parameters for the surgical planning.&#13;
&#13;
An easy to handle software tool allows a radiologically data based safe and fast surgical positioning of the B-FMT.</abstract>
    <parentTitle language="eng">Cochlear Implants International</parentTitle>
    <identifier type="doi">10.1179/1467010014Z.000000000155</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Ingo Todt</author>
    <submitter>Stefan Zachow</submitter>
    <author>Hans Lamecker</author>
    <author>Heiko Ramm</author>
    <author>Arneborg Ernst</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="projects" number="BoneBridge">BoneBridge</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>4982</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2014-05-05</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Robust Measurement of Natural Acetabular Orientation from AP Radiographs using Articulated 3D Shape and Intensity Models</title>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-49824</identifier>
    <enrichment key="SourceTitle">Presented at the 14th Annual Meeting of CAOS-International (CAOS)</enrichment>
    <author>Moritz Ehlke</author>
    <submitter>Moritz Ehlke</submitter>
    <author>Thomas Frenzel</author>
    <author>Heiko Ramm</author>
    <author>Hans Lamecker</author>
    <author>Mohsen Akbari Shandiz</author>
    <author>Carolyn Anglin</author>
    <author>Stefan Zachow</author>
    <series>
      <title>ZIB-Report</title>
      <number>14-12</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>articulated shape and intensity models</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>3D reconstruction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>acetabular orientation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>image registration</value>
    </subject>
    <collection role="ccs" number="">Health</collection>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="ehlke">Ehlke, Moritz</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="BSRT-3DFromXray">BSRT-3DFromXray</collection>
    <collection role="projects" number="ECMath-CH8">ECMath-CH8</collection>
    <collection role="projects" number="JointKinematics">JointKinematics</collection>
    <collection role="projects" number="PelViz">PelViz</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4982/zib-report-14-12.pdf</file>
  </doc>
  <doc>
    <id>8225</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2329</pageFirst>
    <pageLast>2342</pageLast>
    <pageNumber/>
    <edition/>
    <issue>9</issue>
    <volume>40</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2021-09-09</completedDate>
    <publishedDate>2021-05-03</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">AutoImplant 2020 - First MICCAI Challenge on Automatic Cranial Implant Design</title>
    <abstract language="eng">The aim of this paper is to provide a comprehensive overview of the MICCAI 2020 AutoImplant Challenge. The approaches and publications submitted and accepted within the challenge will be summarized and reported, highlighting common algorithmic trends and algorithmic diversity. Furthermore, the evaluation results will be presented, compared and discussed in regard to the challenge aim: seeking for low cost, fast and fully automated solutions for cranial implant design. Based on feedback from collaborating neurosurgeons, this paper concludes by stating open issues and post-challenge requirements for intra-operative use.</abstract>
    <parentTitle language="eng">IEEE Transactions on Medical Imaging</parentTitle>
    <identifier type="doi">10.1109/TMI.2021.3077047</identifier>
    <identifier type="issn">0278-0062</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">2021-04-28</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Jianning Li</author>
    <submitter>Stefan Zachow</submitter>
    <author>Pedro Pimentel</author>
    <author>Angelika Szengel</author>
    <author>Moritz Ehlke</author>
    <author>Hans Lamecker</author>
    <author>Stefan Zachow</author>
    <author>Laura Estacio</author>
    <author>Christian Doenitz</author>
    <author>Heiko Ramm</author>
    <author>Haochen Shi</author>
    <author>Xiaojun Chen</author>
    <author>Franco Matzkin</author>
    <author>Virginia Newcombe</author>
    <author>Enzo Ferrante</author>
    <author>Yuan Jin</author>
    <author>David G. Ellis</author>
    <author>Michele R. Aizenberg</author>
    <author>Oldrich Kodym</author>
    <author>Michal Spanel</author>
    <author>Adam Herout</author>
    <author>James G. Mainprize</author>
    <author>Zachary Fishman</author>
    <author>Michael R. Hardisty</author>
    <author>Amirhossein Bayat</author>
    <author>Suprosanna Shit</author>
    <author>Bomin Wang</author>
    <author>Zhi Liu</author>
    <author>Matthias Eder</author>
    <author>Antonio Pepe</author>
    <author>Christina Gsaxner</author>
    <author>Victor Alves</author>
    <author>Ulrike Zefferer</author>
    <author>Cord von Campe</author>
    <author>Karin Pistracher</author>
    <author>Ute Schäfer</author>
    <author>Dieter Schmalstieg</author>
    <author>Bjoern H. Menze</author>
    <author>Ben Glocker</author>
    <author>Jan Egger</author>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="Cranio">Cranio</collection>
    <collection role="projects" number="MODAL-MedLab">MODAL-MedLab</collection>
    <collection role="projects" number="Modal-Seg">Modal-Seg</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="MfLMS">Mathematics for Life and Materials Science</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>8339</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>73</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images</title>
    <abstract language="eng">Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms tackling the labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel level by a human-machine hybrid algorithm (https://osf.io/nqjyw/, https://osf.io/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the results of this evaluation and further investigate the performance variation at the vertebra level, scan level, and different fields of view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top-performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The VerSe content and code can be accessed at: https://github.com/anjany/verse.</abstract>
    <parentTitle language="eng">Medical Image Analysis</parentTitle>
    <identifier type="doi">10.1016/j.media.2021.102166</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">06.07.2021</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Anjany Sekuboyina</author>
    <submitter>Tamaz Amiranashvili</submitter>
    <author>Malek E. Husseini</author>
    <author>Amirhossein Bayat</author>
    <author>Maximilian Löffler</author>
    <author>Hans Liebl</author>
    <author>Hongwei Li</author>
    <author>Giles Tetteh</author>
    <author>Jan Kukačka</author>
    <author>Christian Payer</author>
    <author>Darko Štern</author>
    <author>Martin Urschler</author>
    <author>Maodong Chen</author>
    <author>Dalong Cheng</author>
    <author>Nikolas Lessmann</author>
    <author>Yujin Hu</author>
    <author>Tianfu Wang</author>
    <author>Dong Yang</author>
    <author>Daguang Xu</author>
    <author>Felix Ambellan</author>
    <author>Tamaz Amiranashvili</author>
    <author>Moritz Ehlke</author>
    <author>Hans Lamecker</author>
    <author>Sebastian Lehnert</author>
    <author>Marilia Lirio</author>
    <author>Nicolás Pérez de Olaguer</author>
    <author>Heiko Ramm</author>
    <author>Manish Sahu</author>
    <author>Alexander Tack</author>
    <author>Stefan Zachow</author>
    <author>Tao Jiang</author>
    <author>Xinjun Ma</author>
    <author>Christoph Angerman</author>
    <author>Xin Wang</author>
    <author>Kevin Brown</author>
    <author>Alexandre Kirszenberg</author>
    <author>Élodie Puybareau</author>
    <author>Di Chen</author>
    <author>Yiwei Bai</author>
    <author>Brandon H. Rapazzo</author>
    <author>Timyoas Yeah</author>
    <author>Amber Zhang</author>
    <author>Shangliang Xu</author>
    <author>Feng Hou</author>
    <author>Zhiqiang He</author>
    <author>Chan Zeng</author>
    <author>Zheng Xiangshang</author>
    <author>Xu Liming</author>
    <author>Tucker J. Netherton</author>
    <author>Raymond P. Mumme</author>
    <author>Laurence E. Court</author>
    <author>Zixun Huang</author>
    <author>Chenhang He</author>
    <author>Li-Wen Wang</author>
    <author>Sai Ho Ling</author>
    <author>Lê Duy Huynh</author>
    <author>Nicolas Boutry</author>
    <author>Roman Jakubicek</author>
    <author>Jiri Chmelik</author>
    <author>Supriti Mulay</author>
    <author>Mohanasankar Sivaprakasam</author>
    <author>Johannes C. Paetzold</author>
    <author>Suprosanna Shit</author>
    <author>Ivan Ezhov</author>
    <author>Benedikt Wiestler</author>
    <author>Ben Glocker</author>
    <author>Alexander Valentinitsch</author>
    <author>Markus Rempfler</author>
    <author>Björn H. Menze</author>
    <author>Jan S. Kirschke</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="MODAL-MedLab">MODAL-MedLab</collection>
    <collection role="persons" number="ambellan">Ambellan, Felix</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="projects" number="MathPlus-TrU-1">MathPlus-TrU-1</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
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