Spatial normalisation of high angular resolution diffusion images (HARDI) is an important prerequisite for group-level analysis of tissue microstructure. In this study, we extend a technique for non-linear registration of orientation density functions by including other non-WM tissue types into the metric driving the registration, and investigate the benefits this provides in terms of overall alignment. Our results show that including additional non-WM tissue types in the registration metric improves the performance of the registration, as assessed by visual inspection (sharper features), and in simulations (slight reduction in residuals)
