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This paper presents a feature-selection-based data fusion method to follow up the evolution of brain tumors under therapeutic treatments with multi-spectral MRI data sequences. The fusion of MRI data is proposed to use a feature selection method to choose the most important features to classify tumor tissues and non-tumor tissues. Our system consists of three steps for each MRI examination (one examination...
<para> Despite growing interest in applying machine learning to neuroimaging analyses, few studies have gone beyond classifying sensory input to directly predicting behavioral output. With spatial resolution on the order of millimeters and temporal resolution on the order of seconds, functional magnetic resonance imaging (fMRI) is a promising technology for such applications. However, fMRI data's...
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