In this pair, we describe experiments designed to validate some techniques used for spatial normalization of diffusion tensor (DT) images. In particular, we have previously described the problems involved in applying transformations to these images and proposed several techniques for addressing this problem. DTs contain orientational information, which must be handled appropriately when a DT image is transformed. In this paper, we review the previously proposed techniques for estimating the appropriate reorientation of each DT that should accompany a given transformation of the image. We describe the design of some synthetic data sets and some experiments, which use this data to test the effectiveness of the techniques under affine transformations of DT images. Results confirm that one particular technique, which takes into account the more complex reorientational effects of shearing and stretching transformations, is the most effective.