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  <doc>
    <id>167</id>
    <completedYear/>
    <publishedYear>2001</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2679</pageFirst>
    <pageLast>2691</pageLast>
    <pageNumber/>
    <edition/>
    <issue>11</issue>
    <volume>18</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Color Line Search for Illuminant Estimation in Real World Scenes</title>
    <abstract language="eng">The estimation of illuminant color is mandatory for many applications in the field of color image quantification. However, it is an unresolved problem if no additional heuristics or restrictive assumptions apply. Assuming uniformly colored and roundly shaped objects, Lee has presented a theory and a method for computing the scene-illuminant chromaticity from specular highlights [H. C. Lee, J. Opt. Soc. Am. A 3, 1694 (1986)]. However, Lee’s method, called image path search, is less robust to noise and is limited in the handling of microtextured surfaces. We introduce a novel approach to estimate the color of a single illuminant for noisy and microtextured images, which frequently occur in real-world scenes. Using dichromatic regions of different colored surfaces, our approach, named color line search, reverses Lee’s strategy of image path search. Reliable color lines are determined directly in the domain of the color diagrams by three steps. First, regions of interest are automatically detected around specular highlights, and local color diagrams are computed. Second, color lines are determined according to the dichromatic reflection model by Hough transform of the color diagrams. Third, a consistency check is applied by a corresponding path search in the image domain. Our method is evaluated on 40 natural images of fruit and vegetables. In comparison with those of Lee’s method, accuracy and stability are substantially improved. In addition, the color line search approach can easily be extended to scenes of objects with macrotextured surfaces.</abstract>
    <parentTitle language="eng">Journal of the Optical Society of America (JOSA) A</parentTitle>
    <identifier type="doi">10.1364/JOSAA.18.002679</identifier>
    <author>Thomas M. Lehmann</author>
    <author>Christoph Palm</author>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
  <doc>
    <id>159</id>
    <completedYear/>
    <publishedYear>2004</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>965</pageFirst>
    <pageLast>976</pageLast>
    <pageNumber/>
    <edition/>
    <issue>5</issue>
    <volume>37</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Color Texture Classification by Integrative Co-Occurrence Matrices</title>
    <abstract language="eng">Integrative Co-occurrence matrices are introduced as novel features for color texture classification. The extended Co-occurrence notation allows the comparison between integrative and parallel color texture concepts. The information profit of the new matrices is shown quantitatively using the Kolmogorov distance and by extensive classification experiments on two datasets. Applying them to the RGB and the LUV color space the combined color and intensity textures are studied and the existence of intensity independent pure color patterns is demonstrated. The results are compared with two baselines: gray-scale texture analysis and color histogram analysis. The novel features improve the classification results up to 20% and 32% for the first and second baseline, respectively.</abstract>
    <parentTitle language="eng">Pattern Recognition</parentTitle>
    <identifier type="doi">10.1016/j.patcog.2003.09.010</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <author>Christoph Palm</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Color texture</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Co-occurrence matrix</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Integrative features</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>KolmogKorov distance</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Image classification</value>
    </subject>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
  <doc>
    <id>154</id>
    <completedYear/>
    <publishedYear>2006</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>251</pageFirst>
    <pageLast>255</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Berlin</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Evaluierung von Registrierungsstrategien zur multimodalen 3D-Rekonstruktion von Rattenhirnschnitten</title>
    <abstract language="deu">In dieser Arbeit werden drei Strategien zur 3D Stapelung von multimodalen Schnittbildern vorgestellt. Die Strategien werden experimentell anhand von Dualtracer-Autoradiographien evaluiert. Dazu werden neue Maße zur Beschreibung der Konsistenz innerhalb einer Modalität und der Konsistenz der Modalitäten untereinander entwickelt, die auf bekannten Registrierungsmetriken basieren. Gerade bezüglich der Konsistenz der Modalitäten untereinander zeigen zwei Strategien die besten Resultate: (1) abwechselnde multimodale Registrierung (2) monomodale Rekonstruktion einer Modalität und multimodale 2D Registrierung der zweiten Modalität.</abstract>
    <parentTitle language="deu">Bildverarbeitung für die Medizin 2006</parentTitle>
    <identifier type="doi">10.1007/3-540-32137-3_51</identifier>
    <author>Christoph Palm</author>
    <author>Andrea Vieten</author>
    <author>Dagmar Bauer</author>
    <author>Uwe Pietrzyk</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Registrierung &lt;Bildverarbeitung&gt;</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Dreidimensionale Rekonstruktion</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Gehirn</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Schnittpräparat</value>
    </subject>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
  <doc>
    <id>158</id>
    <completedYear/>
    <publishedYear>2005</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1446</pageFirst>
    <pageLast>1447</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Fusion strategies in multi-modality imaging</title>
    <parentTitle language="eng">Medical Physics, Vol 2. Proceedings of the jointly held Congresses: ICMP 2005, 14th International Conference of Medical Physics of the International Organization for Medical Physics (IOMP), the European Federation of Organizations in Medical Physics (EFOMP) and the German Society of Medical Physics (DGMP) ; BMT 2005, 39th Annual Congress of the German Society for Biomedical Engineering (DGBMT) within VDE ; 14th - 17th September 2005, Nuremberg, Germany</parentTitle>
    <enrichment key="ConferenceStatement">14th International Conferece of IOMP, EFOMP and DGMP (ICMP 2005) and of 39th Annual Congress of DGBMT within VDE (BMT 2005)</enrichment>
    <enrichment key="OtherSeries">Biomedizinische Technik ; 50, Suppl. 1</enrichment>
    <author>Uwe Pietrzyk</author>
    <author>Christoph Palm</author>
    <author>Thomas Beyer</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Bildgebendes Verfahren</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Registrierung &lt;Bildverarbeitung&gt;</value>
    </subject>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
  <doc>
    <id>144</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>A115</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>46</volume>
    <type>conferencepresentation</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Template for MR-based attenuation correction for whole-body PET/MR imaging</title>
    <parentTitle language="deu">Nuklearmedizin</parentTitle>
    <author>Markus Weigert</author>
    <author>Christoph Palm</author>
    <author>Harald H. Quick</author>
    <author>Stefan P. Müller</author>
    <author>Uwe Pietrzyk</author>
    <author>Thomas Beyer</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Kernspintomografie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Positronen-Emissions-Tomografie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Bildgebendes Verfahren</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Schwächung</value>
    </subject>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
  <doc>
    <id>143</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1569048-041</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>Suppl.</issue>
    <volume>52</volume>
    <type>conferencepresentation</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Visualization of Nerve Fibre Orientation in the Visual Cortex of the Human Brain by Means of Polarized Light</title>
    <parentTitle language="deu">Biomedizinische Technik</parentTitle>
    <author>Markus Axer</author>
    <author>Hubertus Axer</author>
    <author>Christoph Palm</author>
    <author>David Gräßel</author>
    <author>Karl Zilles</author>
    <author>Uwe Pietrzyk</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Sehrinde</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Nervenfaser</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Ausrichtung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Visualisierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Polarisiertes Licht</value>
    </subject>
    <collection role="ddc" number="6">Technik, Medizin, angewandte Wissenschaften</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
  <doc>
    <id>156</id>
    <completedYear/>
    <publishedYear>2005</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>597</pageFirst>
    <pageLast>598</pageLast>
    <pageNumber/>
    <edition/>
    <issue>Suppl. 1, Part 1</issue>
    <volume>50</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">3D rat brain tumor reconstruction</title>
    <parentTitle language="eng">Biomedizinische Technik</parentTitle>
    <enrichment key="ConferenceStatement">International Conference of IOMP, EFOMP and DGMP (ICMP 2005) and of 39th Annual Congress of DGBMT within VDE (BMT 2005)</enrichment>
    <author>Christoph Palm</author>
    <author>Markus Dehnhardt</author>
    <author>Andrea Vieten</author>
    <author>Uwe Pietrzyk</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Dreidimensionale Rekonstruktion</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Hirntumor</value>
    </subject>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
  <doc>
    <id>142</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>1569048-859</pageNumber>
    <edition/>
    <issue>Suppl.</issue>
    <volume>52</volume>
    <type>conferencepresentation</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Application of Fluid and Elastic Registration Methods to Histological Rat Brain Sections</title>
    <parentTitle language="deu">Biomedizinische Technik</parentTitle>
    <author>Christoph Palm</author>
    <author>William R. Crum</author>
    <author>Uwe Pietrzyk</author>
    <author>David J. Hawkes</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Registrierung &lt;Bildverarbeitung&gt;</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Gehirn</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Schnittdarstellung</value>
    </subject>
    <collection role="ddc" number="6">Technik, Medizin, angewandte Wissenschaften</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
  <doc>
    <id>350</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>66</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>2019</volume>
    <type>article</type>
    <publisherName>Oxford University Pres</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-04-22</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Large expert-curated database for benchmarking document similarity detection in biomedical literature search</title>
    <abstract language="eng">Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.</abstract>
    <parentTitle language="eng">Database</parentTitle>
    <identifier type="doi">10.1093/database/baz085</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY-SA - Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Peter Brown</author>
    <author>RELISH Consortium</author>
    <author>Yaoqi Zhou</author>
    <author>Christoph Palm</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Information Retrieval</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Indexierung &lt;Inhaltserschließung&gt;</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Literaturdatenbank</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Dokument</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Ähnlichkeitssuche</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Suchmaschine</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
  <doc>
    <id>352</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>6</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>04</issue>
    <volume>51</volume>
    <type>conferencepresentation</type>
    <publisherName>Georg Thieme Verlag</publisherName>
    <publisherPlace>Stuttgart</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-04-22</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Artificial Intelligence in Early Barrett's Cancer: The Segmentation Task</title>
    <abstract language="eng">Aims:&#13;
The delineation of outer margins of early Barrett's cancer can be challenging even for experienced endoscopists. Artificial intelligence (AI) could assist endoscopists faced with this task. As of date, there is very limited experience in this domain. In this study, we demonstrate the measure of overlap (Dice coefficient = D) between highly experienced Barrett endoscopists and an AI system in the delineation of cancer margins (segmentation task).&#13;
&#13;
Methods:&#13;
An AI system with a deep convolutional neural network (CNN) was trained and tested on high-definition endoscopic images of early Barrett's cancer (n = 33) and normal Barrett's mucosa (n = 41). The reference standard for the segmentation task were the manual delineations of tumor margins by three highly experienced Barrett endoscopists. Training of the AI system included patch generation, patch augmentation and adjustment of the CNN weights. Then, the segmentation results from patch classification and thresholding of the class probabilities. Segmentation results were evaluated using the Dice coefficient (D).&#13;
&#13;
Results:&#13;
The Dice coefficient (D) which can range between 0 (no overlap) and 1 (complete overlap) was computed only for images correctly classified by the AI-system as cancerous. At a threshold of t = 0.5, a mean value of D = 0.72 was computed.&#13;
&#13;
Conclusions:&#13;
AI with CNN performed reasonably well in the segmentation of the tumor region in Barrett's cancer, at least when compared with expert Barrett's endoscopists. AI holds a lot of promise as a tool for better visualization of tumor margins but may need further improvement and enhancement especially in real-time settings.</abstract>
    <parentTitle language="eng">Endoscopy</parentTitle>
    <identifier type="doi">10.1055/s-0039-1681187</identifier>
    <enrichment key="ConferenceStatement">ESGE Days 2019</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Alanna Ebigbo</author>
    <author>Robert Mendel</author>
    <author>Andreas Probst</author>
    <author>Johannes Manzeneder</author>
    <author>Luis Antonio de Souza Jr.</author>
    <author>João Paulo Papa</author>
    <author>Christoph Palm</author>
    <author>Helmut Messmann</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Speiseröhrenkrankheit</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Maschinelles Lernen</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Barrett's esphagus</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Deep Learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Segmentation</value>
    </subject>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="persons" number="palmbarrett">Palm, Christoph (Prof. Dr.) - Projekt Barrett</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
  </doc>
</export-example>
