<rdf:RDF xmlns:rdf="http://www.openarchives.org/OAI/2.0/rdf/" xmlns:ow="http://www.ontoweb.org/ontology/1#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:ds="http://dspace.org/ds/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/rdf/ http://www.openarchives.org/OAI/2.0/rdf.xsd">
   <ow:Publication rdf:about="oai:digibug.ugr.es:10481/92252">
      <dc:title>Advancing Content-Based Histopathological Image Retrieval Pre-Processing: A Comparative Analysis of the Effects of Color Normalization Techniques</dc:title>
      <dc:creator>Tabatabaei, Zahra</dc:creator>
      <dc:creator>Pérez Bueno, Fernando</dc:creator>
      <dc:creator>Colomer, Adrián</dc:creator>
      <dc:creator>Oliver Moll, Javier</dc:creator>
      <dc:creator>Molina Soriano, Rafael</dc:creator>
      <dc:creator>Naranjo, Valery</dc:creator>
      <dc:subject>Color</dc:subject>
      <dc:subject>Histopathological images</dc:subject>
      <dc:subject>Content Based Image Retrieval</dc:subject>
      <dc:subject>Whole slide imaging</dc:subject>
      <dc:description>Author Keywords: color normalization; computer-aided diagnosis (CAD); content-based image retrieval&#xd;
(CBIR); histopathological images; whole-slide images (WSIs)</dc:description>
      <dc:description>Content-Based Histopathological Image Retrieval (CBHIR) is a search technique based on&#xd;
the visual content and histopathological features of whole-slide images (WSIs). CBHIR tools assist&#xd;
pathologists to obtain a faster and more accurate cancer diagnosis. Stain variation between hospitals&#xd;
hampers the performance of CBHIR tools. This paper explores the effects of color normalization&#xd;
(CN) in a recently proposed CBHIR approach to tackle this issue. In this paper, three different CN&#xd;
techniques were used on the CAMELYON17 (CAM17) data set, which is a breast cancer data set.&#xd;
CAM17 consists of images taken using different staining protocols and scanners in five hospitals. Our&#xd;
experiments reveal that a proper CN technique, which can transfer the color version into the most&#xd;
similar median values, has a positive impact on the retrieval performance of the proposed CBHIR&#xd;
framework. According to the obtained results, using CN as a pre-processing step can improve the&#xd;
accuracy of the proposed CBHIR framework to 97% (a 14% increase), compared to working with the&#xd;
original images.</dc:description>
      <dc:date>2024-06-03T09:46:51Z</dc:date>
      <dc:date>2024-06-03T09:46:51Z</dc:date>
      <dc:date>2024-03-01</dc:date>
      <dc:type>journal article</dc:type>
      <dc:identifier>Tabatabaei, Z.; Pérez Bueno, F.; Colomer, A.; Moll, J.O.; Molina, R.; Naranjo, V. Advancing Content- Based Histopathological Image Retrieval Pre-Processing: A Comparative Analysis of the Effects of Color Normalization Techniques. Appl. Sci. 2024, 14, 2063. https:// doi.org/10.3390/app14052063</dc:identifier>
      <dc:identifier>https://hdl.handle.net/10481/92252</dc:identifier>
      <dc:identifier>10.3390/app14052063</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
      <dc:rights>open access</dc:rights>
      <dc:rights>Atribución 4.0 Internacional</dc:rights>
      <dc:publisher>MDPI</dc:publisher>
   </ow:Publication>
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