February 16, 2023 Software Open Access

Lizzi Francesca; Postuma Ian; Cabini Raffaella; Brero Francesca; Fantacci M. Evelina; Lascialfari Alessandro; Oliva Piernicola; Retico Alessandra

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  <identifier identifierType="DOI">10.15161/oar.it/76937</identifier>
  <creators>
    <creator>
      <creatorName>Lizzi Francesca</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-0900-0421</nameIdentifier>
      <affiliation>Istituto Nazionale di Fisica Nucleare</affiliation>
    </creator>
    <creator>
      <creatorName>Postuma Ian</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-9678-9277</nameIdentifier>
      <affiliation>Istituto Nazionale di Fisica Nucleare</affiliation>
    </creator>
    <creator>
      <creatorName>Cabini Raffaella</creatorName>
      <affiliation>Università di Pavia</affiliation>
    </creator>
    <creator>
      <creatorName>Brero Francesca</creatorName>
      <affiliation>Istituto Nazionale di Fisica Nucleare</affiliation>
    </creator>
    <creator>
      <creatorName>Fantacci M. Evelina</creatorName>
      <affiliation>Università di Pisa</affiliation>
    </creator>
    <creator>
      <creatorName>Lascialfari Alessandro</creatorName>
      <affiliation>Università di Pavia</affiliation>
    </creator>
    <creator>
      <creatorName>Oliva Piernicola</creatorName>
      <affiliation>Università di Sassasi</affiliation>
    </creator>
    <creator>
      <creatorName>Retico Alessandra</creatorName>
      <affiliation>Istituto Nazionale di Fisica Nucleare</affiliation>
    </creator>
  </creators>
  <titles>
    <title>LungQuant</title>
  </titles>
  <publisher>INFN Open Access Repository</publisher>
  <publicationYear>2023</publicationYear>
  <subjects>
    <subject>Computed Tomography (CT)</subject>
    <subject>AI</subject>
    <subject>Segmentation</subject>
    <subject>COVID-19</subject>
    <subject>Lung</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2023-02-16</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Software"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://www.openaccessrepository.it/record/76937</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsNewVersionOf">10.1007/s11548-021-02501-2</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.15161/oar.it/76936</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://www.openaccessrepository.it/communities/infn</relatedIdentifier>
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  <version>2.5</version>
  <rightsList>
    <rights rightsURI="https://opensource.org/licenses/EUPL-1.1">European Union Public License 1.1</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;LungQuant is a software for the quantification of lesions in CT scans of COVID-19 patients.&lt;/p&gt;

&lt;p&gt;Its functioning is based on a cascade of three Convolutional Neural Networks (CNN):&lt;/p&gt;

&lt;p&gt;1) the first one is used to produce a bounding box enclosing the lungs;&lt;/p&gt;

&lt;p&gt;2) the second CNN is used to segment the lungs;&lt;/p&gt;

&lt;p&gt;3) the third CNN is devoted to lesion segmentation.&lt;/p&gt;

&lt;p&gt;The system takes in input&amp;nbsp; Computed Tomography (CT) scans in nifti format.&lt;/p&gt;

&lt;p&gt;The system returns in output: the lungs and lesion masks and other information that can be useful to describe the infection.&lt;/p&gt;</description>
  </descriptions>
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