Fusing in vivo and ex vivo NMR sources of information for brain tumor classification (Articolo in rivista)

Type

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

Label

• Fusing in vivo and ex vivo NMR sources of information for brain tumor classification (Articolo in rivista) (literal)

Anno

• 2011-01-01T00:00:00+01:00 (literal)

Alternative label

• Croitor-Sava A. R., Martinez-Bisbal M.C., Laudadio T., Piquer J., Celda B., Heerschap A., Sima D.M., Van Huffel S. (2011)
  Fusing in vivo and ex vivo NMR sources of information for brain tumor classification
  in Measurement science & technology (Print)
  (literal)

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

• Croitor-Sava A. R., Martinez-Bisbal M.C., Laudadio T., Piquer J., Celda B., Heerschap A., Sima D.M., Van Huffel S. (literal)

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

• 22 (literal)

Rivista

• Measurement science & technology (Rivista)

Note

• ISI Web of Science (WOS) (literal)

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

• Katholieke Univ Leuven, Dept Elect Engn, Div ESAT SCD, B-3001 Louvain, Belgium IAC CNR, Ist Applicaz Calcolo M Picone, Natl Res Council, Bari, Italy Univ Valencia, Fac Quim, Dept Quim Fis, Valencia, Spain ISC III, CIBER Bioengn Biomat & Nanomed, Valencia, Spain (literal)

Titolo

• Fusing in vivo and ex vivo NMR sources of information for brain tumor classification (literal)

Abstract

• In this study we classify short echo-time brain magnetic resonance spectroscopic imaging (MRSI) data by applying a model-based canonical correlation analyses algorithm and by using, as prior knowledge, multimodal sources of information coming from high-resolution magic angle spinning (HR-MAS), MRSI and magnetic resonance imaging. The potential and limitations of fusing in vivo and ex vivo nuclear magnetic resonance sources to detect brain tumors is investigated. We present various modalities for multimodal data fusion, study the effect and the impact of using multimodal information for classifying MRSI brain glial tumors data and analyze which parameters influence the classification results by means of extensive simulation and in vivo studies. Special attention is drawn to the possibility of considering HR-MAS data as a complementary dataset when dealing with a lack of MRSI data needed to build a classifier. Results show that HR-MAS information can have added value in the process of classifying MRSI data. (literal)

Prodotto di

• 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)

Autore CNR

• TERESA LAUDADIO (Unità di personale interno)

Insieme di parole chiave

• Keywords of "Fusing in vivo and ex vivo NMR sources of information for brain tumor classification" (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)

Autore CNR di

• TERESA LAUDADIO (Unità di personale interno)

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

• Measurement science & technology (Rivista)

Insieme di parole chiave di

• Keywords of "Fusing in vivo and ex vivo NMR sources of information for brain tumor classification" (Insieme di parole chiave)