1 Ocak 2018 Dergi makalesi Açık Erişim

Doganay, Emine; Kara, Sada; Ozcelik, Hatice Kutbay; Kart, Levent

DataCite XML

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/33693</identifier>
  <creators>
    <creator>
      <creatorName>Doganay, Emine</creatorName>
      <givenName>Emine</givenName>
      <familyName>Doganay</familyName>
      <affiliation>Fatih Univ, Biomed Inst Engn, Buyukcekmece Campuss, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Kara, Sada</creatorName>
      <givenName>Sada</givenName>
      <familyName>Kara</familyName>
      <affiliation>Fatih Univ, Biomed Inst Engn, Buyukcekmece Campuss, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Ozcelik, Hatice Kutbay</creatorName>
      <givenName>Hatice Kutbay</givenName>
      <familyName>Ozcelik</familyName>
      <affiliation>Yedikule Pulmonol &amp; Thorac Surg Hosp, Pulmonol Dept, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Kart, Levent</creatorName>
      <givenName>Levent</givenName>
      <familyName>Kart</familyName>
      <affiliation>Fatih Univ, Med Fac, Pulm Dept, Buyukcekmece Campuss, Istanbul, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>A Hybrid Lung Segmentation Algorithm Based On Histogram-Based Fuzzy C-Means Clustering</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2018</publicationYear>
  <dates>
    <date dateType="Issued">2018-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/33693</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1080/21681163.2017.1332531</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">The lung is an essential organ and is dark in Computed Tomography (CT) images because of air. Lung segmentation and correct lung region separation is a prerequisite for the development of computer-aided diagnostic algorithms and disease treatment planning. However, this remains a nontrivial problem because of lung anatomical structures. Here, we addressed this problem and proposed a reliable and robust solution that is based on a histogram-based fuzzy C-means (FCM) algorithm and morphological mathematical algorithms. There were 1632 high resolution CT slices with 1 mm thickness used from asthma patients with low dose; right and left lungs were classified using the proposed algorithm. We extracted right lung regions with 96.05% accuracy and left lung regions at 96.32%. The computation time is 1.3 s per slice.</description>
  </descriptions>
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