Our research paper "Ensemble Tractography" by Hiromasa Takemura, Cesar F. Caiafa, Brian Wandell and Franco Pestilli, was finally accepted for publication in PLoS Computational Biology Journal.
Abstract: Diffusion Magnetic Resonance Imaging (MRI) and fiber tractography opened a new avenue for studying white matter fascicles and their tissue properties in the living human brain. There are many different fiber tractography methods, and each requires the user to set several parameters. A limitation of fiber tractography is that the results depend on the selection of algorithms and parameters. Here, we analyze an ensemble method, Ensemble Tractography (ET), that reduces the effect of algorithm and parameter selection. ET creates a large set of candidate fascicles using an ensemble of algorithms and parameter values and then selects the fascicles with strong support for the data using a global fascicle evaluation method. The results show that compared to single parameter connectomes, ET connectomes predict diffusion MRI signals better and cover a wider range of white matter volume. Importantly, ET connectomes include both short- and long-association fascicles, which are not typically found in single-parameter connectomes.