Parallel Global Tractography

Global tractography algorithms require long computation times that are often prohibitive in the clinical setting. We propose a parallel implementation of global tractography that can take advantage of parallel computing technologies. Our method breaks the posterior density function of the configuration of fiber segments into a number of independent subposterior density functions, from which parallel sampling can be performed. Our results indicate that tractography results similar to the original global tractography algorithm proposed by Reisert et al. can be achieved using our method in a significantly reduced amount of time.

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