Mejia Roa, E.Carmona Saez, P.Nogales, R.Vicente, C.Vázquez, M.Yang, X. Y.García, C.Tirado Fernández, José FranciscoPascual Montano, Alberto2023-06-202023-06-202008-070305-104810.1093/nar/gkn335https://hdl.handle.net/20.500.14352/51805© 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.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.engAtribución-NoComercial 3.0 Españahttps://creativecommons.org/licenses/by-nc/3.0/es/journal articlehttp://dx.doi.org/10.1093/nar/gkn335http://nar.oxfordjournals.org/open access004Gene-expression dataTensor factorizationDiscoveryIdentificationAlgorithms.Informática (Informática)1203.17 Informática