<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>4292</id>
    <completedYear>2023</completedYear>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>526</pageFirst>
    <pageLast>542</pageLast>
    <pageNumber>17</pageNumber>
    <edition/>
    <issue>3 (3)</issue>
    <volume>2023</volume>
    <type>article</type>
    <publisherName>MDPI</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-12-19</completedDate>
    <publishedDate>2023-07-05</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Improvement in Disease Diagnosis in Computed Tomography Images by Correlating Organ Volumes with Disease Occurrences in Humans</title>
    <abstract language="eng">In this paper, we investigate the influence of different disease groups on the size of different 1 anatomical structures. To this end, we first modify and improve an existing anatomical segmentation 2 model. Then, we use this model to segment 104 anatomical structures from computed tomography 3 (CT) scans and compute their volumes from the segmentation. After correlating the results with each 4 other, we find no new significant correlations. After correlating the volume data with known diseases 5 for each case, we find two weak correlations, one of which has not been described before and for 6 which we present a possible explanation.</abstract>
    <parentTitle language="eng">BioMedInformatics</parentTitle>
    <identifier type="doi">10.3390/biomedinformatics3030036</identifier>
    <identifier type="urn">urn:nbn:de:hbz:1010-opus4-42927</identifier>
    <identifier type="issn">2673-7426</identifier>
    <licence>Creative Commons - Namensnennung</licence>
    <author>Timo van Meegdenburg</author>
    <author>Jens Kleesiek</author>
    <author>Jan Egger</author>
    <author>Sören Perrey</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Segmentation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Correlation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Diseases</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Convolutional Neural Networks</value>
    </subject>
    <collection role="open_access" number="">open_access</collection>
    <collection role="institutes" number="">Institut für biologische und chemische Informatik</collection>
    <thesisPublisher>Westfälische Hochschule Gelsenkirchen Bocholt Recklinghausen</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-w-hs/files/4292/Meegdenburg_Improvement_2023.pdf</file>
  </doc>
</export-example>
