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Pattern recognition of 31 P magnetic resonance spectroscopy tumour spectra obtained in vivo
Author(s) -
Howells S. L.,
Maxwell R. J.,
Howe F. A.,
Peet A. C.,
Stubbs M.,
Rodrigues L. M.,
Robinson S. P.,
Baluch S.,
Griffiths J. R.
Publication year - 1993
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.1940060402
Subject(s) - in vivo , spectral line , nuclear magnetic resonance , nuclear magnetic resonance spectroscopy , spectroscopy , pattern recognition (psychology) , chemistry , artificial intelligence , biology , physics , computer science , genetics , quantum mechanics , astronomy
Pattern recognition has been applied to the analysis of in vivo 31 P NMR spectra. Using four different classes of tumour and three types of normal tissue, cluster analysis and artificial neural networks were successful in separating and classifying the majority of samples analysed. Although the phosphomonoester and P i , regions appeared to be the most important spectral features, data representing the entire 31 P spectrum were required for best separation of the tumour and tissue classes.