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      <dc:title>bioNMF: a web-based tool for nonnegative matrix factorization in biology</dc:title>
      <dc:creator>Mejia Roa, E.</dc:creator>
      <dc:creator>Carmona Saez, P.</dc:creator>
      <dc:creator>Nogales, R.</dc:creator>
      <dc:creator>Vicente, C.</dc:creator>
      <dc:creator>Vázquez, M.</dc:creator>
      <dc:creator>Yang, X. Y.</dc:creator>
      <dc:creator>García, C.</dc:creator>
      <dc:creator>Tirado Fernández, José Francisco</dc:creator>
      <dc:creator>Pascual Montano, Alberto</dc:creator>
      <dc:description>© 2008 The Author(s).

This work has been partially funded by the Spanish grants BIO2007-67150-C03-02, S-Gen-0166/2006, CYTED-505 PI0058, CSD00C-07-20811 and TIN2005-5619. E.M.R. is supported by the grant FPU from the Spanish Ministry of Education. A.P.M. acknowledges the support of the Spanish Ramón y Cajal program. Funding to pay the Open Access publication charges for this article was provided by Spanish Grant. BIO2007-67150-C03-02.</dc:description>
      <dc:description>Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at present, pathologies can be detected with an earliness never before known. Its use has not only been relegated to the field of radiology but also, increasingly, to computer-based imaging processes prior to surgery. Motion analysis, in particular, plays an important role in analyzing activities or behaviors of live objects in medicine. This short paper presents several low-cost hardware implementation approaches for the new generation of tablets and/or smartphones for estimating motion compensation and segmentation in medical images. These systems have been optimized for breast cancer diagnosis using magnetic resonance imaging technology with several advantages over traditional X-ray mammography, for example, obtaining patient information during a short period. This paper also addresses the challenge of offering a medical tool that runs on widespread portable devices, both on tablets and/or smartphones to aid in patient diagnostics.</dc:description>
      <dc:date>2023-06-20T11:11:04Z</dc:date>
      <dc:date>2023-06-20T11:11:04Z</dc:date>
      <dc:date>2008-07</dc:date>
      <dc:type>journal article</dc:type>
      <dc:identifier>0305-1048</dc:identifier>
      <dc:identifier>10.1093/nar/gkn335</dc:identifier>
      <dc:identifier>https://hdl.handle.net/20.500.14352/51805</dc:identifier>
      <dc:identifier>http://dx.doi.org/10.1093/nar/gkn335</dc:identifier>
      <dc:identifier>http://nar.oxfordjournals.org/</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:relation>BIO2007-67150-C03-02</dc:relation>
      <dc:relation>S-Gen-0166/2006</dc:relation>
      <dc:relation>CYTED-505 PI0058</dc:relation>
      <dc:relation>CSD00C-07-20811</dc:relation>
      <dc:relation>TIN2005-5619</dc:relation>
      <dc:relation>BIO2007-67150-C03-02</dc:relation>
      <dc:rights>https://creativecommons.org/licenses/by-nc/3.0/es/</dc:rights>
      <dc:rights>open access</dc:rights>
      <dc:rights>Atribución-NoComercial 3.0 España</dc:rights>
      <dc:publisher>Oxford University Press</dc:publisher>
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