Journal article Closed Access

Variational segmentation of vector-valued images with gradient vector flow.

Jaouen, Vincent; González, Paulo; Stute, Simon; Guilloteau, Denis; Chalon, Sylvie; Buvat, Irène; Tauber, Clovis


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="URL">https://zenodo.org/record/16053</identifier>
  <creators>
    <creator>
      <creatorName>Jaouen, Vincent</creatorName>
      <givenName>Vincent</givenName>
      <familyName>Jaouen</familyName>
      <affiliation>Université François-Rabelais de Tours, INSERM U930 Imaging and Brain, Tours 37032, France</affiliation>
    </creator>
    <creator>
      <creatorName>González, Paulo</creatorName>
      <givenName>Paulo</givenName>
      <familyName>González</familyName>
      <affiliation>Université François-Rabelais de Tours, INSERM U930 Imaging and Brain, Tours 37032, France and Universidad Católica del Maule, Talca, Chile</affiliation>
    </creator>
    <creator>
      <creatorName>Stute, Simon</creatorName>
      <givenName>Simon</givenName>
      <familyName>Stute</familyName>
      <affiliation>Commissariat à l’énergie Atomique, Institut d’Imagerie Biomédicale, Service Hospitalier Frédéric Joliot, Orsay 91405, France</affiliation>
    </creator>
    <creator>
      <creatorName>Guilloteau, Denis</creatorName>
      <givenName>Denis</givenName>
      <familyName>Guilloteau</familyName>
      <affiliation>Université François-Rabelais de Tours, INSERM U930 Imaging and Brain, Tours 37032, France</affiliation>
    </creator>
    <creator>
      <creatorName>Chalon, Sylvie</creatorName>
      <givenName>Sylvie</givenName>
      <familyName>Chalon</familyName>
      <affiliation>Université François-Rabelais de Tours, INSERM U930 Imaging and Brain, Tours 37032, France</affiliation>
    </creator>
    <creator>
      <creatorName>Buvat, Irène</creatorName>
      <givenName>Irène</givenName>
      <familyName>Buvat</familyName>
      <affiliation>Commissariat à l’énergie Atomique, Institut d’Imagerie Biomédicale, Service Hospitalier Frédéric Joliot, Orsay 91405, France</affiliation>
    </creator>
    <creator>
      <creatorName>Tauber, Clovis</creatorName>
      <givenName>Clovis</givenName>
      <familyName>Tauber</familyName>
      <affiliation>Université François-Rabelais de Tours, INSERM U930 Imaging and Brain, Tours 37032, France</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Variational segmentation of vector-valued images with gradient vector flow.</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2014</publicationYear>
  <subjects>
    <subject>deformable models</subject>
    <subject>dynamic PET</subject>
    <subject>gradient vector flow</subject>
    <subject>structure tensor</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2014-09-04</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/16053</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1109/TIP.2014.2353854</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/inmind</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/ecfunded</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="info:eu-repo/semantics/closedAccess">Closed Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;In this paper, we extend the gradient vector flow&lt;/p&gt;

&lt;p&gt;field for robust variational segmentation of vector-valued images.&lt;/p&gt;

&lt;p&gt;Rather than using scalar edge information, we define a vectorial&lt;/p&gt;

&lt;p&gt;edge map derived from a weighted local structure tensor of&lt;/p&gt;

&lt;p&gt;the image that enables the diffusion of the gradient vectors in&lt;/p&gt;

&lt;p&gt;accurate directions through the 4D gradient vector flow equation.&lt;/p&gt;

&lt;p&gt;To reduce the contribution of noise in the structure tensor,&lt;/p&gt;

&lt;p&gt;image channels are weighted according to a blind estimator of&lt;/p&gt;

&lt;p&gt;contrast. The method is applied to biological volume delineation&lt;/p&gt;

&lt;p&gt;in dynamic PET imaging, and validated on realistic Monte Carlo&lt;/p&gt;

&lt;p&gt;simulations of numerical phantoms as well as on real images.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/FP7/278850/">278850</awardNumber>
      <awardTitle>Imaging of Neuroinflammation in Neurodegenerative Diseases</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
40
0
views
downloads
Views 40
Downloads 0
Data volume 0 Bytes
Unique views 38
Unique downloads 0

Share

Cite as