Think Global, Act Local; Projectome Estimation with BlueMatter

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.

• Type: Conference
• Year: 2009
• Where: MICCAI
• Authors: Anthony Sherbondy, Robert Dougherty, Rajagopal Ananthanarayanan, Dharmendra S. Modha, Brian A. Wandell
• Keywords: Data Prediction Error, Global Prediction Error, Matter Volume Conservation, Medical Imaging, MICCAI 2009