Cleaning up the mess: tractography outlier removal using hierarchical QuickBundles clustering

Tracking algorithms often generate non-reproducible streamlines which often appear to be anatomical outliers. Those streamlines affect connectivity studies. We propose a probabilistic outliers removal method based on a randomized hierarchical utilization of QuickBundles. Our method offers a way to reduce the number of invalid bundles while keeping reproducible valid bundles. This allows for more robust connectivity analyses.

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