Automated Feature Selection for the Classification of Meningioma Cell Nuclei

Oliver Wirjadi; Thomas Breuel; Wolfgang Feiden; Yoo-Jin Kim

In: Bildverarbeitung für die Medizin. GI-Fachtagungen, Pages 76-80, Informatik aktuell, Springer, 2006.


A supervised learning method for image classification is presented which is independent of the type of images that will be processed. This is realized by constructing a large base of grey-value and colour based image features. We then rely on a decision tree to choose the features that are most relevant for a given application. We apply and evaluate our system on the classification task of meningioma cells.

OwTmbAutomFeatSelMenCellNuclei.pdf (pdf, 257 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence