Nonlinear dimensionality reduction combining MR imaging with non-imaging information

► We propose an extension to nonlinear dimensionality reduction with Laplacian Eigenmaps. ► MR imaging information is combined with clinical metadata. ► The representation of subjects in the low-dimensional space is interpreted as biomarker. ► We use this biomarker to classify AD subjects from healthy controls. ► We evaluate the method on the ADNI study.