There are numerous medical conditions which may benefit from hyperspectral imaging. The imagers used for these conditions will need to have the performance validated to ensure consistency, gain acceptance and clear regulatory hurdles. NIST has been developing a Digital Light Processing (DLP)-based Hyperspectral Image Projector (HIP) for providing scenes with full spectral content in order to evaluate multispectral and hyperspectral imagers. In order for the scene to be projected, a dimensionality reduction is performed in order to project spectra efficiently. The number of eigenspectra needed to best represent a scene is an important part in the recombining of the image. This paper studies the spectral diversity between different medical scenes collected by a DLP* based hyperspectral imager. Knowledge gained from this study will help guide the methods used for hyperspectral image projection of medical scenes in the future.