Optimal acquisition schemes in high angular diffusion imaging

The recent challenge in diffusion imaging is to find acquisitionschemes and analysis approaches that can represent non-gaussiandiffusion profiles in a clinically feasible measurement time. In this workwe investigate the effect of b-value and the number of gradient vectordirections on Q-ball imaging and the Diffusion Orientation Transform(DOT) in a structured way using computational simulations, hardwarecrossing-fiber diffusion phantoms, and in-vivo brain scans. We observethat DOT is more robust to noise and independent of the b-value andnumber of gradients, whereas Q-ball dramatically improves the resultsfor higher b-values and number of gradients and at recovering larger anglesof crossing. We also show that Laplace-Beltrami regularization haswide applicability and generally improves the properties of DOT. Knowledgeof optimal acquisition schemes for HARDI can improve the utilityof diffusion weighted MR imaging in the clinical setting for the diagnosisof white matter diseases and presurgical planning