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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">109</journal-id>
      <journal-id journal-id-type="index">urn:lsid:arphahub.com:pub:3dc5f44e-8666-58db-bc76-a455210e8891</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">JUCS - Journal of Universal Computer Science</journal-title>
        <abbrev-journal-title xml:lang="en">jucs</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">0948-695X</issn>
      <issn pub-type="epub">0948-6968</issn>
      <publisher>
        <publisher-name>Journal of Universal Computer Science</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.3217/jucs-014-14-2427</article-id>
      <article-id pub-id-type="publisher-id">29151</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group subj-group-type="scientific_subject">
          <subject>G.1.8 - Partial Differential Equations</subject>
          <subject>I.4.6 - Segmentation</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>A Novel Multi-Layer Level Set Method for Image Segmentation</article-title>
      </title-group>
      <contrib-group content-type="authors">
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Wang</surname>
            <given-names>Xiao-Feng</given-names>
          </name>
          <email xlink:type="simple">xfwang@iim.ac.cn</email>
          <xref ref-type="aff" rid="A1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Huang</surname>
            <given-names>De-Shuang</given-names>
          </name>
          <xref ref-type="aff" rid="A2">2</xref>
        </contrib>
      </contrib-group>
      <aff id="A1">
        <label>1</label>
        <addr-line content-type="verbatim">Chinese Academy of Sciences, Hefei, China</addr-line>
        <institution>Chinese Academy of Sciences</institution>
        <addr-line content-type="city">Hefei</addr-line>
        <country>China</country>
      </aff>
      <aff id="A2">
        <label>2</label>
        <addr-line content-type="verbatim">Chinese Academy of Sciences, Beijing, China</addr-line>
        <institution>Chinese Academy of Sciences</institution>
        <addr-line content-type="city">Beijing</addr-line>
        <country>China</country>
      </aff>
      <author-notes>
        <fn fn-type="corresp">
          <p>Corresponding author: Xiao-Feng Wang (<email xlink:type="simple">xfwang@iim.ac.cn</email>).</p>
        </fn>
        <fn fn-type="edited-by">
          <p>Academic editor: </p>
        </fn>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2008</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>28</day>
        <month>07</month>
        <year>2008</year>
      </pub-date>
      <volume>14</volume>
      <issue>14</issue>
      <fpage>2428</fpage>
      <lpage>2452</lpage>
      <uri content-type="arpha" xlink:href="http://openbiodiv.net/832FAE8B-AE0B-5515-9975-28818185B3CE">832FAE8B-AE0B-5515-9975-28818185B3CE</uri>
      <uri content-type="zenodo_dep_id" xlink:href="https://zenodo.org/record/7000416">7000416</uri>
      <permissions>
        <copyright-statement>Xiao-Feng Wang, De-Shuang Huang</copyright-statement>
        <license license-type="creative-commons-attribution" xlink:href="" xlink:type="simple">
          <license-p>This article is freely available under the J.UCS Open Content License.</license-p>
        </license>
      </permissions>
      <abstract>
        <label>Abstract</label>
        <p>In this paper, a new multi-layer level set method is proposed for multi-phase image segmentation. The proposed method is based on the conception of image layer and improved numerical solution of bimodal Chan-Vese model. One level set function is employed for curve evolution with a hierarchical form in sequential image layers. In addition, new initialization method and more efficient computational method for signed distance function are introduced. Moreover, the evolving curve can automatically stop on true boundaries in single image layer according to a termination criterion which is based on the length change of evolving curve. Specially, an adaptive improvement scheme is designed to speed up curve evolution process in a queue of sequential image layers, and the detection of background image layer is used to confirm the termination of the whole multi-layer level set evolution procedure. Finally, numerical experiments on some synthetic and real images have demonstrated the efficiency and robustness of our method. And the comparisons with multi-phase Chan-Vese method also show that our method has a less time-consuming computation and much faster convergence.</p>
      </abstract>
    </article-meta>
  </front>
</article>
