June 16, 2025 Software Open Access

Gupta, Shuvam

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  <identifier identifierType="DOI">10.14278/rodare.3808</identifier>
  <creators>
    <creator>
      <creatorName>Gupta, Shuvam</creatorName>
      <givenName>Shuvam</givenName>
      <familyName>Gupta</familyName>
    </creator>
  </creators>
  <titles>
    <title>mspacman</title>
  </titles>
  <publisher>Rodare</publisher>
  <publicationYear>2025</publicationYear>
  <subjects>
    <subject>Particle characterization</subject>
    <subject>3D analyses</subject>
    <subject>Mineralogy</subject>
    <subject>Open-source software</subject>
    <subject>CT</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2025-06-16</date>
  </dates>
  <resourceType resourceTypeGeneral="Software"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/3808</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-41479</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-41477</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.3807</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/rodare</relatedIdentifier>
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  <version>1.0.0</version>
  <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>
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  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;mspacman is an open-source Python package for 3D particle characterization in CT images. It is specifically developed to address partial volume blur (PVB). The software models PVB using a linear mixing approach to individual particles&amp;#39; grey value histograms. It supports samples with up to 11 mineral phases and can quantify particles containing up to 5 distinct phases. mspacman semi-automates the entire analysis pipeline. This includes image upload, geometrical and intensity properties extraction, histogram computation, phase quantification, and bootstrapped uncertainty estimation. The package provides a scalable framework for high-resolution mineral characterization.&lt;/p&gt;</description>
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