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• W1897092007 abstract "Estimating the complete set of white matter fascicles (the projectome) from diffusion data requires evaluating an enormous number of potential pathways; consequently, most algorithms use computationally efficient greedy methods to search for pathways. The limitation of this approach is that critical global parameters - such as data prediction error and white matter volume conservation - are not taken into account. We describe BlueMatter, a parallel algorithm for global projectome evaluation, which uniquely accounts for global prediction error and volume conservation. Leveraging the BlueGene/L supercomputing architecture, BlueMatter explores a massive database of 180 billion candidate fascicles. The candidates are derived from several sources, including atlases and mutliple tractography algorithms. Using BlueMatter we created the highest resolution, volume-conserved projectome of the human brain." @default.
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• W1897092007 date "2009-01-01" @default.
• W1897092007 modified "2023-09-26" @default.
• W1897092007 title "Think Global, Act Local; Projectome Estimation with BlueMatter" @default.
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• W1897092007 doi "https://doi.org/10.1007/978-3-642-04268-3_106" @default.
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