<?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>S0188-95322023000400140</article-id>
<article-id pub-id-type="doi">10.17488/rmib.44.4.10</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[A U-Net with Statistical Shape Restrictions Applied to the Segmentation of the Left Ventricle in Echocardiographic Images]]></article-title>
<article-title xml:lang="es"><![CDATA[U-Net con Restricciones Estadísticas de Forma, Aplicada a la Segmentación del Ventrículo Izquierdo en Imágenes de Ecocardiograma]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Galicia-Gómez]]></surname>
<given-names><![CDATA[Eduardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Torres-Robles]]></surname>
<given-names><![CDATA[Fabían]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pérez González]]></surname>
<given-names><![CDATA[Jorge]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Escalante-Ramírez]]></surname>
<given-names><![CDATA[Boris]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Arámbula Cosío]]></surname>
<given-names><![CDATA[Fernando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional Autónoma de México Posgrado en Ciencia e Ingeniería de la Computación ]]></institution>
<addr-line><![CDATA[Ciudad de México ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional Autónoma de México Instituto de Física Laboratorio de Física Medica]]></institution>
<addr-line><![CDATA[Ciudad de México ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Nacional Autónoma de México Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas ]]></institution>
<addr-line><![CDATA[Yucatán ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Universidad Nacional Autónoma de México Facultad de Ingeniería ]]></institution>
<addr-line><![CDATA[Ciudad de México ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2023</year>
</pub-date>
<volume>44</volume>
<numero>spe1</numero>
<fpage>140</fpage>
<lpage>151</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0188-95322023000400140&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0188-95322023000400140&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0188-95322023000400140&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This paper aims to introduce an innovative approach to semantic segmentation by leveraging a convolutional neural network (CNN) for predicting the shape and pose parameters of the left ventricle (LV). Our approach involves a modified U-Net architecture with a regression layer as the final stage, as opposed to the traditional classification layer. This modification allows us to predict all the shape and pose parameters of a statistical shape model, including rotation, translation, scale, and deformation. The adapted U-Net is trained using data from a point distribution model (PDM) of the LV. The experimental results demonstrate a mean Dice coefficient of 0.82 on good quality images, and 0.66 including mean and low-quality images. Our approach successfully overcomes a common issue encountered in CNN-based semantic segmentation. Unlike the inaccurate pixel classification that often leads to unwanted blobs, our CNN generates statistically valid shapes. These shapes hold significant potential in initializing other methods, such as active shape models (ASMs). Our novel CNN-based approach provides a novel solution for semantic segmentation, offering shapes and pose parameters that can enhance the accuracy and reliability of subsequent medical image analysis methods.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Este artículo tiene como objetivo introducir un enfoque innovador para la segmentación semántica utilizando una red neuronal convolucional (CNN) para predecir los parámetros de forma y posición del ventrículo izquierdo (VI). Nuestro enfoque implica una arquitectura U-Net modificada con una capa de regresión como etapa final, en contraposición a la capa de clasificación tradicional. Esta modificación nos permite predecir todos los parámetros de un modelo estadístico de formas que incluyen rotación, traslación, escala y deformación. La red convolucional se entrena utilizando datos de un modelo de distribución de puntos (PDM) del VI. Los resultados experimentales muestran un coeficiente Dice promedio de 0.82 para imágenes de buena calidad y de 0.66 cuando se incluyen imágenes de calidad media y baja. Nuestro enfoque supera con éxito un problema común en la segmentación semántica basada en CNNs. A diferencia de la clasificación inexacta de píxeles que a menudo conduce a elementos no deseados (blobs), nuestra CNN genera formas estadísticamente válidas. Estas formas tienen un gran potencial para inicializar otros métodos, como los modelos de forma activa (ASMs). En resumen, nuestro enfoque basado en CNN proporciona una solución innovadora para la segmentación semántica, ofreciendo formas y parámetros de posición que pueden mejorar la precisión y confiabilidad de otros métodos de análisis del VI.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[convolutional neural networks]]></kwd>
<kwd lng="en"><![CDATA[echocardiography]]></kwd>
<kwd lng="en"><![CDATA[left ventricle segmentation]]></kwd>
<kwd lng="en"><![CDATA[statistical shape analysis]]></kwd>
<kwd lng="es"><![CDATA[análisis estadístico de forma]]></kwd>
<kwd lng="es"><![CDATA[ecocardiografía]]></kwd>
<kwd lng="es"><![CDATA[redes neuronales convolucionales]]></kwd>
<kwd lng="es"><![CDATA[segmentación del ventrículo izquierdo]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>[1]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Paragios]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Deriche]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Geodesic active regions and level set methods for supervised texture segmentation]]></article-title>
<source><![CDATA[Int. J. Comput. Vis.]]></source>
<year>2002</year>
<volume>46</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>223-47</page-range></nlm-citation>
</ref>
<ref id="B2">
<label>[2]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Paragios]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A level set approach for shape-driven segmentation and tracking of the left ventricle]]></article-title>
<source><![CDATA[IEEE Trans. Med. Imag.]]></source>
<year>2003</year>
<volume>22</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>773-6</page-range></nlm-citation>
</ref>
<ref id="B3">
<label>[3]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Nascimento]]></surname>
<given-names><![CDATA[J. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Marques]]></surname>
<given-names><![CDATA[J. S.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Robust shape tracking with multiple models in ultrasound images]]></article-title>
<source><![CDATA[IEEE Trans. Image Process.]]></source>
<year>2008</year>
<volume>17</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>392-406</page-range></nlm-citation>
</ref>
<ref id="B4">
<label>[4]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zagrodsky]]></surname>
<given-names><![CDATA[V.]]></given-names>
</name>
<name>
<surname><![CDATA[Walimbe]]></surname>
<given-names><![CDATA[V.]]></given-names>
</name>
<name>
<surname><![CDATA[Castro-Pareja]]></surname>
<given-names><![CDATA[C. R.]]></given-names>
</name>
<name>
<surname><![CDATA[Qin]]></surname>
<given-names><![CDATA[J. X.]]></given-names>
</name>
<name>
<surname><![CDATA[Song]]></surname>
<given-names><![CDATA[J.-M.]]></given-names>
</name>
<name>
<surname><![CDATA[Shekhar]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Registration-assisted segmentation of real-time 3-D echocardiographic data using deformable models]]></article-title>
<source><![CDATA[IEEE Trans. Med. Imaging.]]></source>
<year>2005</year>
<volume>24</volume>
<numero>9</numero>
<issue>9</issue>
<page-range>1089-99</page-range></nlm-citation>
</ref>
<ref id="B5">
<label>[5]</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Georgescu]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhou]]></surname>
<given-names><![CDATA[X. S.]]></given-names>
</name>
<name>
<surname><![CDATA[Comaniciu]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Gupta]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<source><![CDATA[Database-guided segmentation of anatomical structures with complex appearance]]></source>
<year>2005</year>
<volume>2</volume>
<conf-name><![CDATA[ Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)]]></conf-name>
<conf-date>2005</conf-date>
<conf-loc>San Diego, CA, USA </conf-loc>
<page-range>429-36</page-range></nlm-citation>
</ref>
<ref id="B6">
<label>[6]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mitchell]]></surname>
<given-names><![CDATA[S. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Lelieveldt]]></surname>
<given-names><![CDATA[B. P. F.]]></given-names>
</name>
<name>
<surname><![CDATA[Geest]]></surname>
<given-names><![CDATA[R. J. van der]]></given-names>
</name>
<name>
<surname><![CDATA[Bosch]]></surname>
<given-names><![CDATA[H. G.]]></given-names>
</name>
<name>
<surname><![CDATA[Reiber]]></surname>
<given-names><![CDATA[J. H. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Sonka]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Multistage hybrid active appearance model matching: Segmentation of left and right ventricles in cardiac MR images]]></article-title>
<source><![CDATA[IEEE Trans. Med. Imag.]]></source>
<year>2001</year>
<volume>20</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>415-23</page-range></nlm-citation>
</ref>
<ref id="B7">
<label>[7]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bernard]]></surname>
<given-names><![CDATA[O.]]></given-names>
</name>
<name>
<surname><![CDATA[Bosch]]></surname>
<given-names><![CDATA[J. G.]]></given-names>
</name>
<name>
<surname><![CDATA[Heyde]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Alessandrini]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography]]></article-title>
<source><![CDATA[IEEE Trans. Med. Imaging]]></source>
<year>2016</year>
<volume>35</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>967-77</page-range></nlm-citation>
</ref>
<ref id="B8">
<label>[8]</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Leclerc]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Grenier]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Espinosa]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Bernard]]></surname>
<given-names><![CDATA[O.]]></given-names>
</name>
</person-group>
<source><![CDATA[A fully automatic and multi-structural segmentation of the left ventricle and the myocardium on highly heterogeneous 2D echocardiographic data]]></source>
<year>2017</year>
<conf-name><![CDATA[ International Ultrasonics Symposium (IUS)]]></conf-name>
<conf-date>2017</conf-date>
<conf-loc>Washington, DC, USA </conf-loc>
<page-range>1-4</page-range></nlm-citation>
</ref>
<ref id="B9">
<label>[9]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cootes]]></surname>
<given-names><![CDATA[T. F.]]></given-names>
</name>
<name>
<surname><![CDATA[Taylor]]></surname>
<given-names><![CDATA[C. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Cooper]]></surname>
<given-names><![CDATA[D. H.]]></given-names>
</name>
<name>
<surname><![CDATA[Graham]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Active shape models their training and application]]></article-title>
<source><![CDATA[Comput. Vis. Image Underst.]]></source>
<year>1995</year>
<volume>61</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>38-59</page-range></nlm-citation>
</ref>
<ref id="B10">
<label>[10]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ali]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Beheshti]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Janabi-Sharifi]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Echocardiogram segmentation using active shape model and mean squared eigenvalue error]]></article-title>
<source><![CDATA[Biomed. Signal Process. Control]]></source>
<year>2021</year>
<volume>69</volume>
</nlm-citation>
</ref>
<ref id="B11">
<label>[11]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Shoaib]]></surname>
<given-names><![CDATA[M. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Huang Chuah]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Ali]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Hasikin]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[An Overview of Deep Learning Methods for Left Ventricle Segmentation]]></article-title>
<source><![CDATA[Comput. Intell. Neurosci.]]></source>
<year>2023</year>
<volume>2023</volume>
</nlm-citation>
</ref>
<ref id="B12">
<label>[12]</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Savioli]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Vieira]]></surname>
<given-names><![CDATA[M. S.]]></given-names>
</name>
<name>
<surname><![CDATA[Lamata]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Montana]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<source><![CDATA[Automated Segmentation on the Entire Cardiac Cycle Using a Deep Learning Work - Flow]]></source>
<year>2018</year>
<conf-name><![CDATA[ FifthInternational Conference on Social Networks Analysis, Management and Security (SNAMS)]]></conf-name>
<conf-date>2018</conf-date>
<conf-loc>Valencia, Spain </conf-loc>
<page-range>153-8</page-range></nlm-citation>
</ref>
<ref id="B13">
<label>[13]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zou]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[Q.]]></given-names>
</name>
<name>
<surname><![CDATA[Luo]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A novel approach for left ventricle segmentation in tagged MRI]]></article-title>
<source><![CDATA[Comput. Electr. Eng.]]></source>
<year>2021</year>
<volume>95</volume>
</nlm-citation>
</ref>
<ref id="B14">
<label>[14]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wech]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Ankenbrand]]></surname>
<given-names><![CDATA[M. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Bley]]></surname>
<given-names><![CDATA[T. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Heidenreich]]></surname>
<given-names><![CDATA[J. F.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A data-driven semantic segmentation model for direct cardiac functional analysis based on undersampled radial MR cine series]]></article-title>
<source><![CDATA[Magn. Reason. Med.]]></source>
<year>2022</year>
<volume>87</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>972-83</page-range></nlm-citation>
</ref>
<ref id="B15">
<label>[15]</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Veni]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Moradi]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Bulu]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Narayan]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Syeda-Mahmood]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
</person-group>
<source><![CDATA[Echocardiography segmentation based on a shape-guided deformable model driven by a fully convolutional network prior]]></source>
<year>2018</year>
<conf-name><![CDATA[ 15International Symposium on Biomedical Imaging (ISBI 2018)]]></conf-name>
<conf-date>2018</conf-date>
<conf-loc>Washington, DC, USA </conf-loc>
<page-range>898-902</page-range></nlm-citation>
</ref>
<ref id="B16">
<label>[16]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hsu]]></surname>
<given-names><![CDATA[W.-Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Automatic Left Ventricle Recognition, Segmentation and Tracking in Cardiac Ultrasound Image Sequences]]></article-title>
<source><![CDATA[IEEE Access]]></source>
<year>2019</year>
<volume>7</volume>
<page-range>140524-33</page-range></nlm-citation>
</ref>
<ref id="B17">
<label>[17]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Lu]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Monkam]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhu]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
<name>
<surname><![CDATA[Wu]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[LVSnake: Accurate and robust left ventricle contour localization for myocardial infarction detection]]></article-title>
<source><![CDATA[Biomed. Signal Process. Control]]></source>
<year>2023</year>
<volume>85</volume>
</nlm-citation>
</ref>
<ref id="B18">
<label>[18]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Peng]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Jiang]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Pi]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Bao]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhou]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep Snake for Real-Time Instance Segmentation]]></article-title>
<source><![CDATA[arXiv]]></source>
<year>2020</year>
</nlm-citation>
</ref>
<ref id="B19">
<label>[19]</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ronneberger]]></surname>
<given-names><![CDATA[O.]]></given-names>
</name>
<name>
<surname><![CDATA[Fischer]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Brox]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
</person-group>
<source><![CDATA[U-Net: Convolutional Networks for Biomedical Image Segmentation]]></source>
<year>2015</year>
<conf-name><![CDATA[ Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015]]></conf-name>
<conf-loc>Munich, Germany </conf-loc>
<page-range>234-41</page-range></nlm-citation>
</ref>
<ref id="B20">
<label>[20]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Leclerc]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Smistad]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
<name>
<surname><![CDATA[Pedrosa]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Østvik]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography]]></article-title>
<source><![CDATA[IEEE Trans. Med. Imaging]]></source>
<year>2019</year>
<volume>38</volume>
<numero>9</numero>
<issue>9</issue>
<page-range>2198-210</page-range></nlm-citation>
</ref>
<ref id="B21">
<label>[21]</label><nlm-citation citation-type="book">
<source><![CDATA[EchoNet-Dynamic: a Large New Cardiac Motion Video Data Resource for Medical Machine Learning]]></source>
<year>2019</year>
<publisher-name><![CDATA[github]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B22">
<label>[22]</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Galicia Gomez]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
<name>
<surname><![CDATA[Torres Robles]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Escalante Ramirez]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Olveres]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Arámbula Cosío]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
</person-group>
<source><![CDATA[Full multi resolution active shape model for left ventricle segmentation]]></source>
<year>2021</year>
<conf-name><![CDATA[ 17International Symposium on Medical Information Processing and Analysis]]></conf-name>
<conf-loc>Campinas, Brazil </conf-loc>
</nlm-citation>
</ref>
<ref id="B23">
<label>[23]</label><nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Stegmann]]></surname>
<given-names><![CDATA[M. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Delgado Gomez]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
</person-group>
<source><![CDATA[A Brief Introduction to Statistical Shape Analysis]]></source>
<year>2002</year>
</nlm-citation>
</ref>
<ref id="B24">
<label>[24]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cervantes-Guzmán]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[McPherson]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Olveres]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Moreno-García]]></surname>
<given-names><![CDATA[C. F.]]></given-names>
</name>
<name>
<surname><![CDATA[Torres Robles]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Elyan]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
<name>
<surname><![CDATA[Escalante-Ramírez]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Robust cardiac segmentation corrected with heuristics]]></article-title>
<source><![CDATA[PLoS One]]></source>
<year>2023</year>
<volume>18</volume>
<numero>10</numero>
<issue>10</issue>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
