Classification of pathological human brain lesions using magnetic resonance spectroscopy at 3T

Abstract

Magnetic Resonance Spectroscopy is a powerful non-invasive diagnostic tool that is used in conjunction with MRI techniques to provide identification and quantification of biologically important compounds in soft tissue. However in diagnostic applications the underlying relations of the measured metabolites' values that the clinician has to take into account are too complex to be coded into simple decision rules. Moreover magnetic field homogeneity effects, measurement noise and sensor calibration issues induce distortion into the obtained spectra. In this work we focus on utilizing a state of the art support vector machine classification system to undertake the task of brain tumor classification. We aim at providing the human expert with easily interpretable probabilistic metrics to assist in the time, volume and accuracy demanding diagnostic process.