García Sánchez, CarlosBotella Juan, GuillermoAyuso Márquez, FermínGonzález Rodríguez, DiegoPrieto Matías, ManuelTirado Fernández, José Francisco2023-06-192023-06-1920131748-670X10.1155/2013/287089https://hdl.handle.net/20.500.14352/34960The authors would like to thank Dr. Thomas Schlossbauer from the Department of Clinical Radiology, University of Munich, Munich, Germany, for providing the breast MRI images used for this study. This work was partially supported by Projects MICINN TIN2008-0508 and TIN 2012-32180 (Spain).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 Españahttps://creativecommons.org/licenses/by/3.0/es/journal articlehttp://dx.doi.org/10.1155/2013/287089http://www.hindawi.com/open access004Determining optical-flowMotion estimationImage motionComputationPerceptionModel.Informática (Informática)Programación de ordenadores (Informática)1203.17 Informática1203.23 Lenguajes de Programación