Fusingin vivoandex vivoNMR sources of information for brain tumor classification

In this study we classify short echo-time brain magnetic resonance spectroscopic imaging (MRSI) data by applying a model-based canonical correlation analyses algorithm and by using, as prior knowledge, multimodal sources of information coming from high-resolution magic angle spinning (HR-MAS), MRSI and magnetic resonance imaging. The potential and limitations of fusing in vivo and ex vivo nuclear magnetic resonance sources to detect brain tumors is investigated. We present various modalities for multimodal data fusion, study the effect and the impact of using multimodal information for classifying MRSI brain glial tumors data and analyze which parameters influence the classification results…