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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">bsuir</journal-id><journal-title-group><journal-title xml:lang="ru">Доклады БГУИР</journal-title><trans-title-group xml:lang="en"><trans-title>Doklady BGUIR</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1729-7648</issn><issn pub-type="epub">2708-0382</issn><publisher><publisher-name>БГУИР</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">bsuir-1014</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Статьи</subject></subj-group></article-categories><title-group><article-title>МЕТОДИКА ОБРАБОТКИ МНОГОМЕРНЫХ ДАННЫХ МИКРОСКОПИЧЕСКИХ ИЗОБРАЖЕНИЙ ЭНДОКРИННЫХ КАРЦИНОМ</article-title><trans-title-group xml:lang="en"><trans-title>A technique for the processing of multidimensional data of microscopic images of endocrine cancers</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Спринджук</surname><given-names>М. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Sprindzuk</surname><given-names>M. V.</given-names></name></name-alternatives><email xlink:type="simple">bioinformatics_bel@yahoo.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Лыньков</surname><given-names>Л. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Lynkou</surname><given-names>L. M.</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff xml:lang="ru" id="aff-1"><institution>Объединенный институт проблем информатики НАН Беларуси, Республика Беларусь</institution><country>Belarus</country></aff><aff xml:lang="ru" id="aff-2"><institution>Белорусский государственный университет информатики и радиоэлектроники, Республика Беларусь</institution><country>Belarus</country></aff><pub-date pub-type="collection"><year>2018</year></pub-date><pub-date pub-type="epub"><day>03</day><month>06</month><year>2019</year></pub-date><volume>0</volume><issue>5</issue><fpage>72</fpage><lpage>76</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Спринджук М.В., Лыньков Л.М., 2019</copyright-statement><copyright-year>2019</copyright-year><copyright-holder xml:lang="ru">Спринджук М.В., Лыньков Л.М.</copyright-holder><copyright-holder xml:lang="en">Sprindzuk M.V., Lynkou L.M.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://doklady.bsuir.by/jour/article/view/1014">https://doklady.bsuir.by/jour/article/view/1014</self-uri><abstract><p>Приводится описание практической методики обработки многомерных данных на примере данных текстуры изображений, получаемых с микроскопических изображений карцином яичников.</p></abstract><trans-abstract xml:lang="en"><p>Practical technique for processing of multi-dimensional data using the example of image texture data obtained from microscopic ovarian cancer images is described.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>обработка многомерных данных</kwd><kwd>обработка изображений</kwd><kwd>биомедицинские большие данные</kwd><kwd>карцинома яичника</kwd></kwd-group><kwd-group xml:lang="en"><kwd>multidimensional data processing</kwd><kwd>image processing</kwd><kwd>biomedical big data</kwd><kwd>ovarian carcinoma</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">The prognostic value of adaptive nuclear texture features from patient gray level entropy matrices in early stage ovarian cancer / B. 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