1 Ocak 2017 Konferans bildirisi Açık Erişim

Badawi, Diaa; Akhan, Ece; Mallah, Ma'en; Uner, Aysegul; Cetin-Atalay, Rengul; Cetin, A. Enis

DataCite XML

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/50689</identifier>
  <creators>
    <creator>
      <creatorName>Badawi, Diaa</creatorName>
      <givenName>Diaa</givenName>
      <familyName>Badawi</familyName>
      <affiliation>Dept Elect &amp; Elect Engn, TR-06800 Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Akhan, Ece</creatorName>
      <givenName>Ece</givenName>
      <familyName>Akhan</familyName>
      <affiliation>ODTU, Grad Sch Informat, Canc Syst Biol Lab, TR-06800 Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Mallah, Ma'en</creatorName>
      <givenName>Ma'en</givenName>
      <familyName>Mallah</familyName>
      <affiliation>Dept Elect &amp; Elect Engn, TR-06800 Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Uner, Aysegul</creatorName>
      <givenName>Aysegul</givenName>
      <familyName>Uner</familyName>
      <affiliation>Hacettepe Univ, Fac Med, Dept Pathol, TR-06100 Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Cetin-Atalay, Rengul</creatorName>
      <givenName>Rengul</givenName>
      <familyName>Cetin-Atalay</familyName>
      <affiliation>ODTU, Grad Sch Informat, Canc Syst Biol Lab, TR-06800 Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Cetin, A. Enis</creatorName>
      <givenName>A. Enis</givenName>
      <familyName>Cetin</familyName>
    </creator>
  </creators>
  <titles>
    <title>Multiplication Free Neural Network For Cancer Stem Cell Detection In H&amp;E Stained Liver Images</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2017</publicationYear>
  <dates>
    <date dateType="Issued">2017-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/50689</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1117/12.2262338</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Markers such as CD13 and CD133 have been used to identify Cancer Stem Cells (CSC) in various tissue images. It is highly likely that CSC nuclei appear as brown in CD13 stained liver tissue images. We observe that there is a high correlation between the ratio of brown to blue colored nuclei in CD13 images and the ratio between the dark blue to blue colored nuclei in H&amp;amp;E stained liver images. Therefore, we recommend that a pathologist observing many dark blue nuclei in an H&amp;amp;E stained tissue image may also order CD13 staining to estimate the CSC ratio. In this paper, we describe a computer vision method based on a neural network estimating the ratio of dark blue to blue colored nuclei in an H&amp;amp;E stained liver tissue image. The neural network structure is based on a multiplication free operator using only additions and sign operations. Experimental results are presented.</description>
  </descriptions>
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