2026-06-08T03:24:46Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/518052024-08-30T17:37:34Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense
author
Mejia Roa, E.
author
Carmona Saez, P.
author
Nogales, R.
author
Vicente, C.
author
Vázquez, M.
author
Yang, X. Y.
author
García, C.
author
Tirado Fernández, José Francisco
author
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
Atribución-NoComercial 3.0 España
bioNMF: a web-based tool for nonnegative matrix factorization in biology
journal article
URL
https://docta.ucm.es/bitstreams/bcc40c43-15f8-43b7-b047-5d05051b37b8/download
File
MD5
4c80fb60b56fb846edc7861dbed96787
2369554
application/pdf
tirado23libre+CC.pdf