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Endoscopic Vision Challenge 2021

Stefanie Speidel; Lena Maier-Hein; Danail Stoyanov; Sebastian Bodenstedt; Martin Wagner; Beat Müller; Jonathan Chen; Benjamin Müller; Franziska Mathis-Ullrich; Paul Scheikl; Jorge Bernal; Aymeric Histache; Gloria Fernandes-Esparrach; Xavier Dray; Sophia Bano; Alessandro Casella; Francisco Vasconcelos; Sara Moccia; Chinedu Nwoye; Deepak Alapatt; Armine Vardazaryan; Nicolas Padoy; Arnaud Huaulme; Kanako Harada; Pierre Jannin; Aneeq Zia; Kiran Bhattacharyya; Xi Liu; Ziheng Wang; Anthony Jarc


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  <identifier identifierType="DOI">10.5281/zenodo.4572973</identifier>
  <creators>
    <creator>
      <creatorName>Stefanie Speidel</creatorName>
      <affiliation>National Center for Tumor Diseases (NCT): Dresden</affiliation>
    </creator>
    <creator>
      <creatorName>Lena Maier-Hein</creatorName>
      <affiliation>German Cancer Research Center (DKFZ)</affiliation>
    </creator>
    <creator>
      <creatorName>Danail Stoyanov</creatorName>
      <affiliation>Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) and Department of Computer Science, University College London, London, UK</affiliation>
    </creator>
    <creator>
      <creatorName>Sebastian Bodenstedt</creatorName>
      <affiliation>National Center for Tumor Diseases (NCT): Dresden</affiliation>
    </creator>
    <creator>
      <creatorName>Martin Wagner</creatorName>
      <affiliation>Heidelberg University Hospital</affiliation>
    </creator>
    <creator>
      <creatorName>Beat Müller</creatorName>
      <affiliation>Heidelberg University Hospital</affiliation>
    </creator>
    <creator>
      <creatorName>Jonathan Chen</creatorName>
      <affiliation>Heidelberg University Hospital</affiliation>
    </creator>
    <creator>
      <creatorName>Benjamin Müller</creatorName>
      <affiliation>Heidelberg University Hospital</affiliation>
    </creator>
    <creator>
      <creatorName>Franziska Mathis-Ullrich</creatorName>
      <affiliation>Karlsruhe Institute of Technology (KIT)</affiliation>
    </creator>
    <creator>
      <creatorName>Paul Scheikl</creatorName>
      <affiliation>Karlsruhe Institute of Technology (KIT)</affiliation>
    </creator>
    <creator>
      <creatorName>Jorge Bernal</creatorName>
      <affiliation>UAB, CVC, Barcelona, Spain</affiliation>
    </creator>
    <creator>
      <creatorName>Aymeric Histache</creatorName>
      <affiliation>ENSEA, ETIS, Cergy, France</affiliation>
    </creator>
    <creator>
      <creatorName>Gloria Fernandes-Esparrach</creatorName>
      <affiliation>Clinic Hospital Barcelona, Spain</affiliation>
    </creator>
    <creator>
      <creatorName>Xavier Dray</creatorName>
      <affiliation>Saint-Antoine Hospital, APHP, Paris, France</affiliation>
    </creator>
    <creator>
      <creatorName>Sophia Bano</creatorName>
      <affiliation>Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) and Department of Computer Science, University College London, London, UK</affiliation>
    </creator>
    <creator>
      <creatorName>Alessandro Casella</creatorName>
      <affiliation>Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy and Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy</affiliation>
    </creator>
    <creator>
      <creatorName>Francisco Vasconcelos</creatorName>
      <affiliation>Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) and Department of Computer Science, University College London, London, UK</affiliation>
    </creator>
    <creator>
      <creatorName>Sara Moccia</creatorName>
      <affiliation>Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy and Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy</affiliation>
    </creator>
    <creator>
      <creatorName>Chinedu Nwoye</creatorName>
      <affiliation>CAMMA Lab, University of Strasbourg &amp; IHU Strasbourg</affiliation>
    </creator>
    <creator>
      <creatorName>Deepak Alapatt</creatorName>
      <affiliation>CAMMA Lab, University of Strasbourg &amp; IHU Strasbourg</affiliation>
    </creator>
    <creator>
      <creatorName>Armine Vardazaryan</creatorName>
      <affiliation>CAMMA Lab, University of Strasbourg &amp; IHU Strasbourg</affiliation>
    </creator>
    <creator>
      <creatorName>Nicolas Padoy</creatorName>
      <affiliation>CAMMA Lab, University of Strasbourg &amp; IHU Strasbourg</affiliation>
    </creator>
    <creator>
      <creatorName>Arnaud Huaulme</creatorName>
      <affiliation>niv Rennes, INSERM, LTSI - UMR 1099, F35000, Rennes, France</affiliation>
    </creator>
    <creator>
      <creatorName>Kanako Harada</creatorName>
      <affiliation>Department of Mechanical Engineering, the University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan</affiliation>
    </creator>
    <creator>
      <creatorName>Pierre Jannin</creatorName>
      <affiliation>niv Rennes, INSERM, LTSI - UMR 1099, F35000, Rennes, France</affiliation>
    </creator>
    <creator>
      <creatorName>Aneeq Zia</creatorName>
      <affiliation>Intuitive Surgical</affiliation>
    </creator>
    <creator>
      <creatorName>Kiran Bhattacharyya</creatorName>
      <affiliation>Intuitive Surgical</affiliation>
    </creator>
    <creator>
      <creatorName>Xi Liu</creatorName>
      <affiliation>Intuitive Surgical</affiliation>
    </creator>
    <creator>
      <creatorName>Ziheng Wang</creatorName>
      <affiliation>Intuitive Surgical</affiliation>
    </creator>
    <creator>
      <creatorName>Anthony Jarc</creatorName>
      <affiliation>Intuitive Surgical</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Endoscopic Vision Challenge 2021</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <subjects>
    <subject>Surgical Vision</subject>
    <subject>Endoscopy, Classification</subject>
    <subject>Segmentation</subject>
    <subject>Detection</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2021-03-02</date>
  </dates>
  <resourceType resourceTypeGeneral="Other"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4572973</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4572972</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by-nd/4.0/legalcode">Creative Commons Attribution No Derivatives 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Minimally invasive surgery using cameras to observe the internal anatomy is the preferred approach to many surgical procedures. Furthermore, other surgical disciplines rely on microscopic images or use flexible endoscopes for diagnostic purposes. As a result, endoscopic and microscopic image processing as well as surgical vision are evolving as techniques needed to facilitate computer assisted interventions (CAI). Algorithms that have been reported for such images include 3D surface reconstruction, salient feature motion tracking, instrument detection or activity recognition. However, what is missing so far are common datasets for consistent evaluation and benchmarking of algorithms against each other.&lt;/p&gt;

&lt;p&gt;As a vision CAI challenge at MICCAI, our aim is to provide a formal framework for evaluating the current state of the art, gather researchers in the field and provide high quality data with protocols for validating endoscopic vision algorithms. EndoVis serves as an umbrella for different kinds of sub-challenges that tackle specific problems and applications in endoscopic/microsopic vision.&lt;/p&gt;</description>
  </descriptions>
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