March 15, 2024 Dataset Open Access

Starke, Sebastian; Kieslich, Aaron Markus; Palkowitsch, Martina; Hennings, Fabian; Troost, Esther Gera Cornelia; Krause, Mechthild; Bensberg, Jona; Hahn, Christian; Heinzelmann, Feline; Bäumer, Christian; Lühr, Armin; Timmermann, Beate; Löck, Steffen

DataCite XML Export

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  <identifier identifierType="DOI">10.14278/rodare.2764</identifier>
  <creators>
    <creator>
      <creatorName>Starke, Sebastian</creatorName>
      <givenName>Sebastian</givenName>
      <familyName>Starke</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-5007-1868</nameIdentifier>
    </creator>
    <creator>
      <creatorName>Kieslich, Aaron Markus</creatorName>
      <givenName>Aaron Markus</givenName>
      <familyName>Kieslich</familyName>
    </creator>
    <creator>
      <creatorName>Palkowitsch, Martina</creatorName>
      <givenName>Martina</givenName>
      <familyName>Palkowitsch</familyName>
    </creator>
    <creator>
      <creatorName>Hennings, Fabian</creatorName>
      <givenName>Fabian</givenName>
      <familyName>Hennings</familyName>
    </creator>
    <creator>
      <creatorName>Troost, Esther Gera Cornelia</creatorName>
      <givenName>Esther Gera Cornelia</givenName>
      <familyName>Troost</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-9550-9050</nameIdentifier>
    </creator>
    <creator>
      <creatorName>Krause, Mechthild</creatorName>
      <givenName>Mechthild</givenName>
      <familyName>Krause</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-1776-9556</nameIdentifier>
    </creator>
    <creator>
      <creatorName>Bensberg, Jona</creatorName>
      <givenName>Jona</givenName>
      <familyName>Bensberg</familyName>
    </creator>
    <creator>
      <creatorName>Hahn, Christian</creatorName>
      <givenName>Christian</givenName>
      <familyName>Hahn</familyName>
    </creator>
    <creator>
      <creatorName>Heinzelmann, Feline</creatorName>
      <givenName>Feline</givenName>
      <familyName>Heinzelmann</familyName>
    </creator>
    <creator>
      <creatorName>Bäumer, Christian</creatorName>
      <givenName>Christian</givenName>
      <familyName>Bäumer</familyName>
    </creator>
    <creator>
      <creatorName>Lühr, Armin</creatorName>
      <givenName>Armin</givenName>
      <familyName>Lühr</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-9450-6859</nameIdentifier>
    </creator>
    <creator>
      <creatorName>Timmermann, Beate</creatorName>
      <givenName>Beate</givenName>
      <familyName>Timmermann</familyName>
    </creator>
    <creator>
      <creatorName>Löck, Steffen</creatorName>
      <givenName>Steffen</givenName>
      <familyName>Löck</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-7017-3738</nameIdentifier>
    </creator>
  </creators>
  <titles>
    <title>Data publication: A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy</title>
  </titles>
  <publisher>Rodare</publisher>
  <publicationYear>2024</publicationYear>
  <subjects>
    <subject>proton-beam therapy</subject>
    <subject>relative biological effectiveness</subject>
    <subject>linear energy transfer</subject>
    <subject>NTCP models</subject>
    <subject>deep learning</subject>
    <subject>brain tumor</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2024-03-15</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/2764</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-38860</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-38858</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.2763</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/rodare</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This repository contains the outputs and result data of our deep-learning-based experiments for the approximation of Monte-Carlo-simulated linear energy transfer distributions, which build the foundation for the corresponding article.&lt;/p&gt;

&lt;p&gt;The Pytorch checkpoint of our finally chosen SegResNet architecture trained on the UPTD dose distributions is located at dd_pbs/Dose-LETd/clip_let_below_0.04/segresnet/all_trainvalid_data/training/lightning_logs/version_6358843/checkpoints/last.ckpt.&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;

&lt;p&gt;Moreover, we provide an exemplary data sample from a water phantom for trying our analysis pipeline.&lt;/p&gt;</description>
  </descriptions>
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