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In Metaheuristics for Multiobjective Optimisation (Springer-Verlag). 535, 3–38 (2003) 25. K Deb, A Pratap, S Agarwal, T Meyarivan, A fast elitist multi-objective genetic algorithm: Nsga-ii. IEEE Trans. Evol. Comput. 6, 182–197 (2000) 26. M Otte, HH Nagel, Estimation of optical flow based on higher-order spatiotemporal derivatives in interlaced and non-interlaced image sequences. Artif. Intell. 78(1), 5–43 (1995) 27. B McCane, K Novins, D Crannitch, B Galvin, On benchmarking optical flow. Comput. Vis. Image Underst. 84(1), 126–143 (2001)1687-618010.1186/1687-6180-2013-23https://hdl.handle.net/20.500.14352/35015© Springer International Publishing AG The present study had been supported by Spanish Projects CICYT-TIN 2008/508, CICYT-TIN 2012-32180 and Ingenio Consolider ESP00C-07-20811.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 3.0 Españajournal articlehttp://dx.doi.org/10.1186/1687-6180-2013-23http://www.asp.eurasipjournals.com/open access004ArchitectureAlgorithm.Informática (Informática)1203.17 Informática