October 6, 2017 Dataset Open Access

Sara Moccia; Elena De Momi; Leonardo S. Mattos

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="DOI">10.5281/zenodo.1003200</identifier>
  <creators>
    <creator>
      <creatorName>Sara Moccia</creatorName>
      <affiliation>Politecncico di Milano, Istituto Italiano di Tecnologia</affiliation>
    </creator>
    <creator>
      <creatorName>Elena De Momi</creatorName>
      <affiliation>Politecncico di Milano</affiliation>
    </creator>
    <creator>
      <creatorName>Leonardo S. Mattos</creatorName>
      <affiliation>Istituto Italiano di Tecnologia</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Laryngeal dataset</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2017</publicationYear>
  <dates>
    <date dateType="Issued">2017-10-06</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1003200</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1003199</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by-nc/4.0/legalcode">Creative Commons Attribution Non Commercial 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The dataset in &lt;em&gt;&lt;strong&gt;laryngeal dataset.tar &lt;/strong&gt;&lt;/em&gt;contains 1320 patches of healthy and early-stage cancerous laryngeal tissues. The patches (100x100 pixels) were manually extracted from 33 narrow-band laryngoscopic images of 33 different patients affected by laryngeal spinocellular carcinoma (diagnosed after histopathological examination).&lt;/p&gt;

&lt;p&gt;Specifically, four tissue classes were considered (330 patches/tissue class): He (healthy tissue), Hbv (tissue with hypertrophic vessels), Le (tissue with leukoplakia) and IPCL (tissue with intrapapillary capillary loops).&lt;/p&gt;

&lt;p&gt;The dataset was created for testing the method proposed in &lt;em&gt;Moccia, Sara, et al. "Confident texture-based laryngeal tissue classification for early stage diagnosis support." JOURNAL OF MEDICAL IMAGING 4.03 (2017): 1-10.&lt;/em&gt;&lt;/p&gt;

&lt;p&gt;The folder&lt;em&gt; &lt;strong&gt;laryngeal dataset.tar&lt;/strong&gt; &lt;/em&gt;contains 3 subfolders (FOLD 1, FOLD 2, FOLD 3), which are the 3 folds used for cross-validation purpose in the tissue classification performance assessment.&lt;/p&gt;

&lt;p&gt;Each subfolder contains 4 folders relative to the four tissue classes, i.e., Le, He, Hbv, IPCL.&lt;/p&gt;

&lt;p&gt;----------------------------------------------------------------------------------------------------------------------------------------------------------&lt;/p&gt;

&lt;p&gt;If you want to use the dataset, please cite &lt;em&gt;Moccia, Sara, et al. "Confident texture-based laryngeal tissue classification for early stage diagnosis support." JOURNAL OF MEDICAL IMAGING 4.03 (2017): 1-10.&lt;/em&gt;&lt;/p&gt;

&lt;p&gt; &lt;/p&gt;

&lt;p&gt; &lt;/p&gt;

&lt;p&gt; &lt;/p&gt;</description>
  </descriptions>
</resource>