TY - GEN
T1 - Frequency selection for the diagnostic characterization of human brain tumours
AU - Arizmendi, Carlos
AU - Vellido, Alfredo
AU - Romero, Enrique
PY - 2009
Y1 - 2009
N2 - The diagnosis of brain tumours is an extremely sensitive and complex clinical task that must rely upon information gathered through non-invasive techniques. One such technique is magnetic resonance, in the modalities of imaging or spectroscopy. The latter provides plenty of metabolic information about the tumour tissue, but its high dimensionality makes resorting to pattern recognition techniques advisable. In this brief paper, an international database of brain tumours is analyzed resorting to an ad hoc spectral frequency selection procedure combined with nonlinear classification.
AB - The diagnosis of brain tumours is an extremely sensitive and complex clinical task that must rely upon information gathered through non-invasive techniques. One such technique is magnetic resonance, in the modalities of imaging or spectroscopy. The latter provides plenty of metabolic information about the tumour tissue, but its high dimensionality makes resorting to pattern recognition techniques advisable. In this brief paper, an international database of brain tumours is analyzed resorting to an ad hoc spectral frequency selection procedure combined with nonlinear classification.
KW - Artificial Neural Networks
KW - Brain Tumour
KW - Magnetic Resonance Spectroscopy
KW - Moving Window
UR - http://www.scopus.com/inward/record.url?scp=72749087312&partnerID=8YFLogxK
U2 - 10.3233/978-1-60750-061-2-391
DO - 10.3233/978-1-60750-061-2-391
M3 - Libros de Investigación
AN - SCOPUS:72749087312
SN - 9781607500612
T3 - Frontiers in Artificial Intelligence and Applications
SP - 391
EP - 398
BT - Frontiers in Artificial Intelligence and Applications
PB - IOS Press
ER -