Lipid metabolite peaks in pattern recognition analysis of tumour in vivo MR spectra.
The ability to classify spectra of tumours according to their stage and type will be essential if magnetic resonance spectroscopy (MRS) is to be used as an aid in the diagnosis of cancer. MRS data are normally classified on the basis of selected peak measurements but these may be difficult to extract automatically. We present two alternative methods of feature extraction which we used to discriminate between spectra from tumours and normal tissues. Discrimination could be achieved either using features from the whole spectrum, or from a selected region containing the peaks from the phospholipid precursors in the phosphomonoester region.
Tate
A R
AR
School of Cognitive & Computing Sciences, University of Sussex, Falmer, Brighton, UK. rosemary@cogs.susx.ac.uk
Crabb
S
S
Griffiths
J R
JR
Howells
S L
SL
Mazucco
R A
RA
Rodrigues
L M
LM
Watson
D
D
D000818:Animals; D005260:Female; D050356:Lipid Metabolism; D009682:Magnetic Resonance Spectroscopy; D009374:Neoplasms, Experimental / Q000378:metabolism*; D010363:Pattern Recognition, Automated; D051381:Rats; D011915:Rats, Inbred BUF; D011920:Rats, Inbred WF; D017208:Rats, Wistar