bioNMF: a versatile tool for non-negative matrix factorization in biology



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Pascual Montano, Alberto and Carmona Saez, Pedro and Chagoyen, Mónica and Tirado Fernández, Francisco and Carazo, José M. and Pascual Marqui, Roberto. D. (2006) bioNMF: a versatile tool for non-negative matrix factorization in biology. BMC Bioinformatics, 7 . ISSN 1471-2105

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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.

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© 2006 Pascual-Montano et a.
This work has been partially funded by the Spanish grants CICYT BFU2004-00217/BMC, GEN2003-20235-c05-05, CYTED-505PI0058, TIN2005-5619, PR27/05-13964-BSCH and a collaborative grant between the Spanish CSIC and the Canadian NRC (CSIC-050402040003). PCS is recipient of a grant from CAM. APM acknowledges the support of the Spanish Ramón y Cajal program.

Uncontrolled Keywords:Gene expression data; Independent component analysis; Microarray data; Class discovery; Profiles; Identification; Algorithms; Features; Cancer
Subjects:Sciences > Computer science
ID Code:36321
Deposited On:01 Jun 2016 14:57
Last Modified:01 Jun 2016 14:57

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