Fast nosological imaging using canonical correlation analysis of brain data obtained by two-dimensional turbo spectroscopic imaging (Articolo in rivista)

Type

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

Label

• Fast nosological imaging using canonical correlation analysis of brain data obtained by two-dimensional turbo spectroscopic imaging (Articolo in rivista) (literal)

Anno

• 2008-01-01T00:00:00+01:00 (literal)

Alternative label

• Laudadio T., Martínez-Bisbal M.C., Celda B., Van Huffel S. (2008)
  Fast nosological imaging using canonical correlation analysis of brain data obtained by two-dimensional turbo spectroscopic imaging
  in NMR in biomedicine
  (literal)

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

• Laudadio T., Martínez-Bisbal M.C., Celda B., Van Huffel S. (literal)

Pagina inizio

• 311 (literal)

Pagina fine

• 321 (literal)

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

• 21 (literal)

Rivista

• NMR in biomedicine (Rivista)

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

• Digital Object Identifier (DOI) 10.1002/nbm.1190 (literal)

Note

• ISI Web of Science (WOS) (literal)

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

• Department of Electrical Engineering, Division ESAT-SCD, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium Istituto per le Applicazioni del Calcolo M. Picone, National Research Council, (IAC-CNR), Bari, Italy Departamento de Química-Física, Facultad de Química, Universidad de Valencia, Valencia, Spain CIBER of Bioengineering, Biomaterials and Nanomedicine, ISC-III, Valencia, Spain (literal)

Titolo

• Fast nosological imaging using canonical correlation analysis of brain data obtained by two-dimensional turbo spectroscopic imaging (literal)

Abstract

• A new fast and accurate tissue typing technique has recently been successfully applied to prostate MR spectroscopic imaging (MRSI) data. This technique is based on canonical correlation analysis (CCA), a statistical method able to simultaneously exploit the spectral and spatial information characterizing the MRSI data. Here, the performance of CCA is further investigated by using brain data obtained by two-dimensional turbo spectroscopic imaging (2DTSI) from patients affected by glioblastoma. The purpose of this study is to investigate the applicability of CCA when typing tissues of heterogeneous tumors. The performance of CCA is also compared with that of ordinary correlation analysis on simulated as well as in vivo data. The results show that CCA outperforms ordinary correlation analysis in terms of robustness and accuracy. (literal)

Prodotto di

• Metodologie del Calcolo Scientifico e sviluppo di algoritmi e software ad alte prestazioni (ICT.P11.001.001) (Modulo)
• Istituto per le applicazioni del calcolo \"Mauro Picone\" (IAC) (Istituto)

Autore CNR

• TERESA LAUDADIO (Unità di personale esterno)

Insieme di parole chiave

• Parole chiave di "Fast nosological imaging using canonical correlation analysis of brain data obtained by two-dimensional turbo spectroscopic imaging" (Insieme di parole chiave)

Incoming links:

Prodotto

• Istituto per le applicazioni del calcolo \"Mauro Picone\" (IAC) (Istituto)
• Metodologie del Calcolo Scientifico e sviluppo di algoritmi e software ad alte prestazioni (ICT.P11.001.001) (Modulo)
• http://www.cnr.it/ontology/cnr/individuo/modulo/ID6943

Autore CNR di

• TERESA LAUDADIO (Unità di personale esterno)

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

• NMR in biomedicine (Rivista)

Insieme di parole chiave di

• Parole chiave di "Fast nosological imaging using canonical correlation analysis of brain data obtained by two-dimensional turbo spectroscopic imaging" (Insieme di parole chiave)