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A proper classification is a key factor for the successful visualization of 3D medical data. In direct volume rendering applications, the data is classified by means of a transfer function mapping each voxel characteristics to optical properties such as color and opacity, thus highlighting certain regions over others. In a medical scenario, the structures of interest that must be highlighted may vary strongly depending on the application. Therefore, easy and intuitive user interaction is crucial to achieve a meaningful classification for a given patient's scan. In this paper, we focus on a novel approach that combines direct visualization and interaction with 3D data in a medical augmented reality (AR) environment. The proposed method takes into account regions of interest directly defined by the physician in the patient's anatomy and employs this information to automatically generate an adequate transfer function. Illustrative results demonstrate the utility of this interactive visualization paradigm for medical applications.