Discriminating glioblastomas from metastases in a SV1H-MRS brain tumour database

Romero Merino, Enrique; Vellido Alcacena, Alfredo; Julià Sapé, Margarida; Arús, Carles

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Romero Merino, Enrique

Vellido Alcacena, Alfredo

Julià Sapé, Margarida

Arús, Carles

Document typeConference report

Defense date2009

Rights accessOpen Access

Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain

Abstract

A Feature Selection (FS) process with a simple Machine Learning method, namely the Single-Layer Perceptron (SLP), is shown to discriminate metastases from glioblastomas with high accuracy using single voxel H-MRS from an international, multi-centre database of brain tumors. The method has low computational cost and its results are intuitively interpretable.

CitationRomero, E. [et al.]. Discriminating glioblastomas from metastases in a SV1H-MRS brain tumour database. A: Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology. "Magnetic Resonance Materials in Physics, Biology and Medicine, Vol. 22, Sup.1: Book of Abstracts ESMRMB 2009". Antalya: 2009, p. 18-19.

URIhttp://hdl.handle.net/2117/15706

Publisher versionhttp://www.springerlink.com/content/x465x44qp5g602hu/

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Discriminating glioblastomas from metastases in a SV1H-MRS brain tumour database

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