Blind source separation and automatic tissue typing of microdiffraction data by hierarchical nonnegative matrix factorization (Articolo in rivista)

Type

• Prodotto della ricerca (Classe)
• Articolo in rivista (Classe)

Label

• Blind source separation and automatic tissue typing of microdiffraction data by hierarchical nonnegative matrix factorization (Articolo in rivista) (literal)

Anno

• 2013-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.1107/S0021889813021729 (literal)

Alternative label

• M. Ladisa, A. Lamura, T. Laudadio (2013)
  Blind source separation and automatic tissue typing of microdiffraction data by hierarchical nonnegative matrix factorization
  in Journal of applied crystallography
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• M. Ladisa, A. Lamura, T. Laudadio (literal)

Pagina inizio

• 1467 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 46 (literal)

Rivista

• Journal of applied crystallography (Rivista)

Note

• ISI Web of Science (WOS) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• IC CNR, IAC CNR Bari, IAC CNR Bari (literal)

Titolo

• Blind source separation and automatic tissue typing of microdiffraction data by hierarchical nonnegative matrix factorization (literal)

Abstract

• In this article a nonnegative blind source separation technique, known as nonnegative matrix factorization, is applied to microdiffraction data in order to extract characteristic patterns and to determine their spatial distribution in tissue typing problems occurring in bone-tissue engineering. In contrast to other blind source separation methods, nonnegative matrix factorization only requires nonnegative constraints on the extracted sources and corresponding weights, which makes it suitable for the analysis of data occurring in a variety of applications. In particular, here nonnegative matrix factorization is hierarchically applied to two-dimensional meshes of X-ray diffraction data measured in bone samples with implanted tissue. Such data are characterized by nonnegative profiles and their analysis provides significant information about the structure of possibly new deposited bone tissue. A simulation and real data studies show that the proposed method is able to retrieve the patterns of interest and to provide a reliable and accurate segmentation of the given X-ray diffraction data. (literal)

Prodotto di

• Metodologie del Calcolo Scientifico e sviluppo di algoritmi e software ad alte prestazioni (ICT.P11.001.001) (Modulo)
• Dinamica dei sistemi complessi fluidodinamici e biologici (MD.P02.002.001) (Modulo)
• Institute of Crystallography (IC) (Istituto)
• Istituto per le applicazioni del calcolo \"Mauro Picone\" (IAC) (Istituto)
• Many-Body Quantum Field Theory: Phenomenology and Applications to Crystals (ICT.P11.001.002) (Modulo)

Autore CNR

• ANTONIO LAMURA (Persona)
• TERESA LAUDADIO (Unità di personale interno)
• MASSIMO LADISA (Unità di personale interno)

Incoming links:

Autore CNR di

• ANTONIO LAMURA (Persona)
• MASSIMO LADISA (Unità di personale interno)
• TERESA LAUDADIO (Unità di personale interno)

Prodotto

• Istituto per le applicazioni del calcolo \"Mauro Picone\" (IAC) (Istituto)
• Institute of Crystallography (IC) (Istituto)
• Dinamica dei sistemi complessi fluidodinamici e biologici (MD.P02.002.001) (Modulo)
• Many-Body Quantum Field Theory: Phenomenology and Applications to Crystals (ICT.P11.001.002) (Modulo)
• Metodologie del Calcolo Scientifico e sviluppo di algoritmi e software ad alte prestazioni (ICT.P11.001.001) (Modulo)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• Journal of applied crystallography (Rivista)