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
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <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/oncoray</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"><p>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.</p> <p>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.</p> <p>&nbsp;</p> <p>Moreover, we provide an exemplary data sample from a water phantom for trying our analysis pipeline.</p></description> </descriptions> </resource>
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