Brain tumour diagnosis with Wavelets and Support Vector Machines

In this paper, a synergy of signal processing techniques and intelligent strategies is applied in order to identify different types of human brain tumours, so that to help to confirm the histological diagnosis. The wavelet-SVM (support vector machine) classifier merges wavelet transform to reduce the size of the biomedical spectra and to extract the main features, with SVM to classify them. The influence of some of the configuration parameters of each of those techniques on the clustering is analysed. The classification results are promising specially taking into account that medical knowledge has not been considered.