2026-06-08T04:01:55Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/518052024-08-30T17:37:34Zcom_20.500.14352_14col_20.500.14352_15

Mejia Roa, E. Carmona Saez, P. Nogales, R. Vicente, C. Vázquez, M. Yang, X. Y. García, C. Tirado Fernández, José Francisco Pascual Montano, Alberto 2023-06-20T11:11:04Z 2023-06-20T11:11:04Z 2008-07 0305-1048 10.1093/nar/gkn335 https://hdl.handle.net/20.500.14352/51805 http://dx.doi.org/10.1093/nar/gkn335 http://nar.oxfordjournals.org/ 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. eng https://creativecommons.org/licenses/by-nc/3.0/es/ open access Atribución-NoComercial 3.0 España bioNMF: a web-based tool for nonnegative matrix factorization in biology journal article