Before revision:  We implemented a  non-dominated sorting genetic algorithm  (NSGA-II) strategy to explore the parameters space. Evolutionary optimization runs for 10 brain samples in parallel while sharing champion settings over samples, encouraging convergence of parameters in a similar locus.
After revision:  We implemented a non-dominated sorting genetic algorithm (NSGA-II) to optimize five major parameters of a global fiber-tracking algorithm over multiple brain samples in parallel while sharing champion settings over samples, encouraging convergence of parameters in a similar locus.