TY - GEN
T1 - Diagnosis of brain tumours from magnetic resonance spectroscopy using wavelets and Neural Networks
AU - Arizmendi, Carlos
AU - Hernández-Tamames, Juan
AU - Romero, Enrique
AU - Vellido, Alfredo
AU - Del Pozo, Francisco
PY - 2010
Y1 - 2010
N2 - The diagnosis of human brain tumours from noninvasive signal measurements is a sensitive task that requires specialized expertise. In this task, radiology experts are likely to benefit from the support of computer-based systems built around robust classification processes. In this brief paper, a method that combines data pre-processing using wavelets with classification using Artificial Neural Networks is shown to yield high diagnostic classification accuracy for a broad range of brain tumour pathologies.
AB - The diagnosis of human brain tumours from noninvasive signal measurements is a sensitive task that requires specialized expertise. In this task, radiology experts are likely to benefit from the support of computer-based systems built around robust classification processes. In this brief paper, a method that combines data pre-processing using wavelets with classification using Artificial Neural Networks is shown to yield high diagnostic classification accuracy for a broad range of brain tumour pathologies.
UR - http://www.scopus.com/inward/record.url?scp=78650831964&partnerID=8YFLogxK
U2 - 10.1109/IEMBS.2010.5627627
DO - 10.1109/IEMBS.2010.5627627
M3 - Conference proceeding
C2 - 21097127
AN - SCOPUS:78650831964
SN - 9781424441235
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
SP - 6074
EP - 6077
BT - 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
T2 - 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Y2 - 31 August 2010 through 4 September 2010
ER -