We propose a novel Spatial Multi-category Angle-based Classifier (SMAC) for the efficient identification of biomarkers in the imaging data. The proposed SMAC not only utilizes the spatial structure of high-dimensional imaging data, but also handles both binary and multi-category classification problems. Besides, the SMAC also include the functions to deal with imaging based regression problems, with spatial and sparse penalty available.