<?xml version="1.0" encoding="ISO-8859-1"?><article 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">
<front>
<journal-meta>
<journal-id>0188-9532</journal-id>
<journal-title><![CDATA[Revista mexicana de ingeniería biomédica]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. mex. ing. bioméd]]></abbrev-journal-title>
<issn>0188-9532</issn>
<publisher>
<publisher-name><![CDATA[Sociedad Mexicana de Ingeniería Biomédica]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0188-95322017000100126</article-id>
<article-id pub-id-type="doi">10.17488/rmib.38.1.9</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Dinámica Pulmonar de Estructuras Anatómicas de Interés en Imágenes 4DCT]]></article-title>
<article-title xml:lang="en"><![CDATA[Pulmonary Dynamics of Anatomical Structures of Interest in 4DCT Images]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-Juárez]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mejía-Rodríguez]]></surname>
<given-names><![CDATA[A. R.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Arce-Santana]]></surname>
<given-names><![CDATA[E. R.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma de San Luis Potosí (UASLP) Facultad de Ciencias ]]></institution>
<addr-line><![CDATA[S.L.P. ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2017</year>
</pub-date>
<volume>38</volume>
<numero>1</numero>
<fpage>126</fpage>
<lpage>140</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0188-95322017000100126&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0188-95322017000100126&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0188-95322017000100126&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: El presente trabajo muestra una aplicación del algoritmo Chan-Vese para la segmentación semi-automática de estructuras anatómicas de interés (pulmones y tumor pulmonar) en imágenes de 4DCT de tórax, así como su reconstrucción tridimensional. La segmentación y reconstrucción se realizó en 10 imágenes de TAC, las cuales conforman un ciclo inspiración-espiración. Se calculó el desplazamiento máximo para el caso del tumor pulmonar usando las reconstrucciones del inicio de la inspiración, el inicio de la espiración, y la información del voxel. El método propuesto logra segmentar de manera apropiada las estructuras estudiadas sin importar su tamaño y forma. La reconstrucción tridimensional nos permite visualizar la dinámica de las estructuras de interés a lo largo del ciclo respiratorio. En un futuro se espera poder contar con mayor evidencia del buen desempeño del método propuesto y contar con la retroalimentación del experto clínico, ya que el conocimiento de características de estructuras anatómicas, como su dimensión y posición espacial, ayuda en la planificación de tratamientos de Radioterapia (RT), logrando optimizar las dosis de radiación hacia las células cancerosas y minimizarla en órganos sanos. Por lo tanto, la información encontrada en este trabajo puede resultar de interés para la planificación de tratamientos de RT.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: This paper presents an application of the Chan-Vese algorithm for a semi-automatic segmentation of anatomical structures of interest (lungs and lung tumor) in thorax 4DCT images, as well as its threedimensional reconstruction. Segmentations and reconstructions were performed in 10 CT images, which conform an inspiration-expiration cycle. The maximum displacement of the lung tumor was calculated using the reconstructions of the beginning of inspiration, beginning of expiration, and the voxel size information. The proposed method was able to succesfully segment the studied structures regardless of their size and shape. The threedimensional reconstruction allow us to visualize the dynamics of the structures of interest throughout the respiratory cycle. In the near future, we are expecting to be able to have more evidence of the good performance of the proposed segmentation approach, and to have feedback from a clinical expert, giving the fact that the knowledge of anatomical structures characteristics, such as their size and spatial location, may help in the planning of radiotherapy treatments (RT), optimizing the radiation dose to cancer cells and minimizing it in healthy organs. Therefore, the information found in this work may be of interest for the planning of RT treatments.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Segmentación]]></kwd>
<kwd lng="es"><![CDATA[Chan-Vese]]></kwd>
<kwd lng="es"><![CDATA[Dinámica pulmonar]]></kwd>
<kwd lng="es"><![CDATA[Imágenes 4DCT de tórax]]></kwd>
<kwd lng="en"><![CDATA[Segmentation]]></kwd>
<kwd lng="en"><![CDATA[Chan-Vese]]></kwd>
<kwd lng="en"><![CDATA[Pulmonary Dynamics]]></kwd>
<kwd lng="en"><![CDATA[4DCT thorax images]]></kwd>
</kwd-group>
</article-meta>
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