Towards an automated system to classify in vivo /sup 1/H spectra of brain tumours

In this study the authors have only considered pairs of classes and have used a very simple classification approach. However, the results are useful because they show which data points vary most between tumour types and suggest that a binary approach may be useful for discrimination. The authors' preliminary results show that it is possible to discriminate between the different classes of tumours using data point values which are extracted from the spectra after a minimum of pre-processing. These data points provided better discrimination than points selected from the tops of the peaks. This study differs from previous work in that the feature selection and normalisation procedures are completely objective. Linear discriminant analysis using selected data points seems a promising approach for the automated classification of in vivo human brain tumours.