Feasibility and advantages of diffusion weighted imaging atlas construction in Q-space

In the field of diffusion weighted imaging (DWI), it is common to fit one of many available models to the acquired data. A hybrid diffusion imaging (HYDI) approach even allows to reconstruct different models and measures from a single dataset. Methods for DWI atlas construction (and registration) are as plenty as the number of available models. Therefore, it would be nice if we were able to perform atlas building before model reconstruction. In this work, we present a method for atlas construction of DWI data in q-space: we developed a new multi-subject multi-channel diffeomorphic matching algorithm, which is combined with a recently proposed DWI retransformation method in q-space. We applied our method to HYDI data of 10 healthy subjects. From the resulting atlas, we also reconstructed some advanced models. We hereby demonstrate the feasibility of q-space atlas building, as well as the quality, advantages and possibilities of such an atlas.