Feature Selection with Single-Layer Perceptrons for a Multicentre 1H-MRS Brain Tumour Database

A Feature Selection process with Single-Layer Perceptrons is shown to provide optimum discrimination of an international, multi-centre 1H-MRS database of brain tumors at reasonable computational cost. Results are both intuitively interpretable and very accurate. The method remains simple enough as to allow its easy integration in existing medical decision support systems.

[1]  Sabine Van Huffel,et al.  Brain tumor classification based on long echo proton MRS signals , 2004, Artif. Intell. Medicine.

[2]  Alberto Prieto,et al.  Computational and ambient intelligence , 2009, Neurocomputing.

[3]  Andy Devos.  Quantification and Classification of Magnetic Resonance Spectroscopy Data and Applications to Brain Tumour Recognition (Kwantificatie en classificatie van Magnetische Resonantie Spectroscopie data en toepassingen voor de patroonherkenning van hersentumoren) , 2005 .

[4]  Jason Weston,et al.  Gene Selection for Cancer Classification using Support Vector Machines , 2002, Machine Learning.

[5]  Margarida Julià-Sapé,et al.  Brain tumor classification by proton MR spectroscopy: comparison of diagnostic accuracy at short and long TE. , 2004, AJNR. American journal of neuroradiology.

[6]  Kenneth W. Bauer,et al.  Feature saliency measures , 1997 .

[7]  Sabine Van Huffel,et al.  A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection , 2007, Artif. Intell. Medicine.

[8]  A. W. Simonetti,et al.  Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra , 2006, NMR in biomedicine.

[9]  Sabine Van Huffel,et al.  The effect of combining two echo times in automatic brain tumor classification by MRS , 2008, NMR in biomedicine.

[10]  W El-Deredy,et al.  Tumour grading from magnetic resonance spectroscopy: a comparison of feature extraction with variable selection , 2003, Statistics in medicine.

[11]  Paulo J. G. Lisboa,et al.  Neural Networks and Other Machine Learning Methods in Cancer Research , 2007, IWANN.

[12]  Josep M. Sopena,et al.  Performing Feature Selection With Multilayer Perceptrons , 2008, IEEE Transactions on Neural Networks.